Articles | Volume 21, issue 9
https://doi.org/10.5194/acp-21-6663-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-6663-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 May 2021
Research article |
| 04 May 2021
| 04 May 2021
Linking global terrestrial CO2 fluxes and environmental drivers: inferences from the Orbiting Carbon Observatory 2 satellite and terrestrial biospheric models
Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
Junjie Liu
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Daven K. Henze
Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, USA
Deborah N. Huntzinger
School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA
Kelley C. Wells
Department of Soil, Water, and Climate, University of Minnesota Twin Cities, St. Paul, MN, USA
Stephen Sitch
College of Life and Environmental Sciences, University of Exeter, Exeter, UK
Pierre Friedlingstein
College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
Emilie Joetzjer
Centre National de Recherche Météorologique, Unité mixte de recherche 3589 Meteo-France/CNRS, 42 Avenue Gaspard Coriolis, 31100 Toulouse, France
Vladislav Bastrikov
Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre-Simon Laplace, CEA-CNRS-UVSQ, CE Orme des Merisiers, 91191 Gif-sur-Yvette CEDEX, France
Daniel S. Goll
Université Paris-Saclay, CEA-CNRS-UVSQ, LSCE/IPSL, Gif-sur-Yvette, France
Vanessa Haverd
CSIRO Oceans and Atmosphere, G.P.O. Box 1700, Canberra, ACT 2601, Australia
Atul K. Jain
Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
Etsushi Kato
Institute of Applied Energy (IAE), Minato-ku, Tokyo 105-0003, Japan
Sebastian Lienert
Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Danica L. Lombardozzi
Terrestrial Sciences Section, Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA
Patrick C. McGuire
Department of Meteorology, Department of Geography and Environmental Science, National Centre for Atmospheric Science, University of Reading, Reading, UK
Joe R. Melton
Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
Julia E. M. S. Nabel
Max Planck Institute for Meteorology, Hamburg, Germany
Benjamin Poulter
NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD, USA
Hanqin Tian
International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, 602 Duncan Drive, Auburn, AL, USA
Andrew J. Wiltshire
Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK
Sönke Zaehle
Max Planck Institute for Biogeochemistry, P.O. Box 600164, Hans-Knöll-Str. 10, 07745 Jena, Germany
Scot M. Miller
Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-103, https://doi.org/10.5194/essd-2024-103, 2024
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Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot Miller, and Arvind Saibaba
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-90, https://doi.org/10.5194/gmd-2024-90, 2024
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Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
K. Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
EGUsphere, https://doi.org/10.5194/egusphere-2024-1431, https://doi.org/10.5194/egusphere-2024-1431, 2024
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The study aimed to improve the representation of spring wheat and rice in the CLM5. The modified CLM5 model performed significantly better than the default model in simulating crop phenology, yield, carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific parameters for accurately simulating vegetation processes and land surface processes.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kelley Wells, Dylan Millet, Jared Brewer, Vivienne Payne, Karen Cady-Pereira, Rick Pernak, Susan Kulawik, Corinne Vigouroux, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Tomoo Nagahama, Ivan Ortega, Mathias Palm, Kimberly Strong, Matthias Schneider, Dan Smale, Ralf Sussmann, and Minqiang Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2024-1551, https://doi.org/10.5194/egusphere-2024-1551, 2024
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Atmospheric volatile organic compounds affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new long-term (2012–2023) measurements of four key VOCs: methanol, ethene, ethyne, and hydrogen cyanide (HCN) from the Cross-track Infrared Sounder. The measurements reflect emissions from major forests, wildfires, and industry, and provide new information to advance understanding of these sources and their changes over time.
Yitong Yao, Philippe Ciais, Emilie Joetzjer, Wei Li, Lei Zhu, Yujie Wang, Christian Frankenberg, and Nicolas Viovy
Earth Syst. Dynam., 15, 763–778, https://doi.org/10.5194/esd-15-763-2024, https://doi.org/10.5194/esd-15-763-2024, 2024
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Elevated CO2 concentration (eCO2) is critical for shaping the future path of forest carbon uptake, while uncertainties remain about concurrent carbon loss. Here, we found that eCO2 might amplify competition-induced carbon loss, while the extent of drought-induced carbon loss hinges on the balance between heightened biomass density and water-saving benefits. This is the first time that such carbon loss responses to ongoing climate change have been quantified separately over the Amazon rainforest.
Rebecca M. Varney, Pierre Friedlingstein, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 21, 2759–2776, https://doi.org/10.5194/bg-21-2759-2024, https://doi.org/10.5194/bg-21-2759-2024, 2024
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Soil carbon is the largest store of carbon on the land surface of Earth and is known to be particularly sensitive to climate change. Understanding this future response is vital to successfully meeting Paris Agreement targets, which rely heavily on carbon uptake by the land surface. In this study, the individual responses of soil carbon are quantified and compared amongst CMIP6 Earth system models used within the most recent IPCC report, and the role of soils in the land response is highlighted.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Xi Yi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1584, https://doi.org/10.5194/egusphere-2024-1584, 2024
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 per year in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter Raymond, Pierre Regnier, Joseph G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihito Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joel Thanwerdas, Hanquin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido van der Werf, Doug E. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-115, https://doi.org/10.5194/essd-2024-115, 2024
Revised manuscript has not been submitted
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesize and update the budget of the sources and sinks of CH4. This edition benefits from important progresses in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
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This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Omar V. Müller, Patrick C. McGuire, Pier Luigi Vidale, and Ed Hawkins
Hydrol. Earth Syst. Sci., 28, 2179–2201, https://doi.org/10.5194/hess-28-2179-2024, https://doi.org/10.5194/hess-28-2179-2024, 2024
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This work evaluates how rivers are projected to change in the near future compared to the recent past in the context of a warming world. We show that important rivers of the world will notably change their flows, mainly during peaks, exceeding the variations that rivers used to exhibit. Such large changes may produce more frequent floods, alter hydropower generation, and potentially affect the ocean's circulation.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
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Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Luke D. Schiferl, Clayton Elder, Olli Peltola, Annett Bartsch, Amanda Armstrong, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-84, https://doi.org/10.5194/essd-2024-84, 2024
Revised manuscript under review for ESSD
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We present daily methane fluxes of northern wetlands at 10-km resolution during 2016–2022 (WetCH4) derived from a novel machine-learning framework with improved accuracy. We estimated an average annual CH4 emissions of 20.8 ±2.1 Tg CH4 yr-1. Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variations coming from West Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-43, https://doi.org/10.5194/essd-2024-43, 2024
Preprint under review for ESSD
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We have developed a new map that reveals how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2,500 gauges and a wealth of climate and environmental information. The map is a critical step in understanding and predicting how carbon moves through our environment, hence a useful tool for tackling climate challenges.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
EGUsphere, https://doi.org/10.5194/egusphere-2024-277, https://doi.org/10.5194/egusphere-2024-277, 2024
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This study investigates present day carbon cycle variables in CMIP5 and CMIP6 simulations. A significant improvement in the simulation of photosynthesis in models with nitrogen cycle is found, as well as only small differences between emission and concentration based simulations. Thus, we recommend the use of emission driven simulations in CMIP7 as default setup, and to view the nitrogen cycle as a necessary part of all future carbon cycle models.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
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Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Yona Silvy, Thomas L. Frölicher, Jens Terhaar, Fortunat Joos, Friedrich A. Burger, Fabrice Lacroix, Myles Allen, Raffaele Bernadello, Laurent Bopp, Victor Brovkin, Jonathan R. Buzan, Patricia Cadule, Martin Dix, John Dunne, Pierre Friedlingstein, Goran Georgievski, Tomohiro Hajima, Stuart Jenkins, Michio Kawamiya, Nancy Y. Kiang, Vladimir Lapin, Donghyun Lee, Paul Lerner, Nadine Mengis, Estela A. Monteiro, David Paynter, Glen P. Peters, Anastasia Romanou, Jörg Schwinger, Sarah Sparrow, Eric Stofferahn, Jerry Tjiputra, Etienne Tourigny, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-488, https://doi.org/10.5194/egusphere-2024-488, 2024
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We apply the Adaptive Emission Reduction Approach with Earth System Models to provide simulations in which all ESMs converge at 1.5 °C and 2 °C warming levels. These simulations provide compatible emission pathways for a given warming level, uncovering uncertainty ranges previously missing in the CMIP scenarios. This new type of target-based emission-driven simulations offers a more coherent assessment across ESMs for studying both the carbon cycle and impacts under climate stabilization.
Camilla Therese Mathison, Eleanor Burke, Eszter Kovacs, Gregory Munday, Chris Huntingford, Chris Jones, Chris Smith, Norman Steinert, Andy Wiltshire, Laila Gohar, and Rebecca Varney
EGUsphere, https://doi.org/10.5194/egusphere-2023-2932, https://doi.org/10.5194/egusphere-2023-2932, 2024
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emission scenarios and rapidly provide regional impacts information. PRIME allows large ensembles to be run on multi-centennial timescales including analysis of many important variables for impacts assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios giving confidence in using PRIME for novel scenarios.
Jonathan Hobbs, Matthias Katzfuss, Hai Nguyen, Vineet Yadav, and Junjie Liu
Geosci. Model Dev., 17, 1133–1151, https://doi.org/10.5194/gmd-17-1133-2024, https://doi.org/10.5194/gmd-17-1133-2024, 2024
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The cycling of carbon among the land, oceans, and atmosphere is a closely monitored process in the global climate system. These exchanges between the atmosphere and the surface can be quantified using a combination of atmospheric carbon dioxide observations and computer models. This study presents a statistical method for investigating the similarities and differences in the estimated surface–atmosphere carbon exchange when different computer model assumptions are invoked.
Tomohiro Hajima, Michio Kawamiya, Akihiko Ito, Kaoru Tachiiri, Chris Jones, Vivek Arora, Victor Brovkin, Roland Séférian, Spencer Liddicoat, Pierre Friedlingstein, and Elena Shevliakova
EGUsphere, https://doi.org/10.5194/egusphere-2024-188, https://doi.org/10.5194/egusphere-2024-188, 2024
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This study analyzes atmospheric CO2 concentrations and global carbon budgets simulated by multiple Earth system models, using several types of simulations. We successfully identified problems of global carbon budget in each model. We also found urgent issues that should be solved in the latest generation of models, land use change CO2 emissions.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Wolfgang Alexander Obermeier, Clemens Schwingshackl, Ana Bastos, Giulia Conchedda, Thomas Gasser, Giacomo Grassi, Richard A. Houghton, Francesco Nicola Tubiello, Stephen Sitch, and Julia Pongratz
Earth Syst. Sci. Data, 16, 605–645, https://doi.org/10.5194/essd-16-605-2024, https://doi.org/10.5194/essd-16-605-2024, 2024
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We provide and compare country-level estimates of land-use CO2 fluxes from a variety and large number of models, bottom-up estimates, and country reports for the period 1950–2021. Although net fluxes are small in many countries, they are often composed of large compensating emissions and removals. In many countries, the estimates agree well once their individual characteristics are accounted for, but in other countries, including some of the largest emitters, substantial uncertainties exist.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Mueller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2023-2873, https://doi.org/10.5194/egusphere-2023-2873, 2024
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Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in Northern Europe using ecosystem models, atmospheric inversions and up-scaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions and up-scaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
Christian Rödenbeck, Karina E. Adcock, Markus Eritt, Maksym Gachkivskyi, Christoph Gerbig, Samuel Hammer, Armin Jordan, Ralph F. Keeling, Ingeborg Levin, Fabian Maier, Andrew C. Manning, Heiko Moossen, Saqr Munassar, Penelope A. Pickers, Michael Rothe, Yasunori Tohjima, and Sönke Zaehle
Atmos. Chem. Phys., 23, 15767–15782, https://doi.org/10.5194/acp-23-15767-2023, https://doi.org/10.5194/acp-23-15767-2023, 2023
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The carbon dioxide content of the Earth atmosphere is increasing due to human emissions from burning of fossil fuels, causing global climate change. The strength of the fossil-fuel emissions is estimated by inventories based on energy data, but independent validation of these inventories has been recommended by the Intergovernmental Panel on Climate Change. Here we investigate the potential to validate inventories based on measurements of small changes in the atmospheric oxygen content.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
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Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Chenwei Xiao, Sönke Zaehle, Hui Yang, Jean-Pierre Wigneron, Christiane Schmullius, and Ana Bastos
Earth Syst. Dynam., 14, 1211–1237, https://doi.org/10.5194/esd-14-1211-2023, https://doi.org/10.5194/esd-14-1211-2023, 2023
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Ecosystem resistance reflects their susceptibility during adverse conditions and can be changed by land management. We estimate ecosystem resistance to drought and temperature globally. We find a higher resistance to drought in forests compared to croplands and an evident loss of resistance to drought when primary forests are converted to secondary forests or they are harvested. Old-growth trees tend to be more resistant in some forests and crops benefit from irrigation during drought periods.
Zi Huang, Jiaoyue Wang, Longfei Bing, Yijiao Qiu, Rui Guo, Ying Yu, Mingjing Ma, Le Niu, Dan Tong, Robbie M. Andrew, Pierre Friedlingstein, Josep G. Canadell, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 15, 4947–4958, https://doi.org/10.5194/essd-15-4947-2023, https://doi.org/10.5194/essd-15-4947-2023, 2023
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This is about global and regional cement process carbon emissions and CO2 uptake calculations from 1930 to 2019. The global cement production is rising to 4.4 Gt, causing processing carbon emission of 1.81 Gt (95% CI: 1.75–1.88 Gt CO2) in 2021. Plus, in 2021, cement’s carbon accumulated uptake (22.9 Gt, 95% CI: 19.6–22.6 Gt CO2) has offset 55.2% of cement process CO2 emissions (41.5 Gt, 95% CI: 38.7–47.1 Gt CO2) since 1930.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Danica L. Lombardozzi, William R. Wieder, Negin Sobhani, Gordon B. Bonan, David Durden, Dawn Lenz, Michael SanClements, Samantha Weintraub-Leff, Edward Ayres, Christopher R. Florian, Kyla Dahlin, Sanjiv Kumar, Abigail L. S. Swann, Claire M. Zarakas, Charles Vardeman, and Valerio Pascucci
Geosci. Model Dev., 16, 5979–6000, https://doi.org/10.5194/gmd-16-5979-2023, https://doi.org/10.5194/gmd-16-5979-2023, 2023
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We present a novel cyberinfrastructure system that uses National Ecological Observatory Network measurements to run Community Terrestrial System Model point simulations in a containerized system. The simple interface and tutorials expand access to data and models used in Earth system research by removing technical barriers and facilitating research, educational opportunities, and community engagement. The NCAR–NEON system enables convergence of climate and ecological sciences.
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca Baier, and Luciana V. Gatti
EGUsphere, https://doi.org/10.5194/egusphere-2023-2258, https://doi.org/10.5194/egusphere-2023-2258, 2023
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Multi-inverse modeling inter-comparison projects offer a chance to assess uncertainties in inversion estimates arising from various sources. This study proposes a method to quantify errors of regional terrestrial biosphere CO2 flux estimates from an inverse model ensemble by using airborne CO2 measurements. Our observation-based error estimates exceed the ensemble spread of flux estimates in regions with high anthropogenic emission regions, suggesting systematic biases in inversion estimates.
Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Ying-Ping Wang, Julian Helfenstein, Yuanyuan Huang, and Enqing Hou
Biogeosciences, 20, 4147–4163, https://doi.org/10.5194/bg-20-4147-2023, https://doi.org/10.5194/bg-20-4147-2023, 2023
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We identified total soil P concentration as the most important predictor of all soil P pool concentrations, except for primary mineral P concentration, which is primarily controlled by soil pH and only secondarily by total soil P concentration. We predicted soil P pools’ distributions in natural systems, which can inform assessments of the role of natural P availability for ecosystem productivity, climate change mitigation, and the functioning of the Earth system.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, Simon Jones, Andy J. Wiltshire, and Peter M. Cox
Biogeosciences, 20, 3767–3790, https://doi.org/10.5194/bg-20-3767-2023, https://doi.org/10.5194/bg-20-3767-2023, 2023
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This study evaluates soil carbon projections during the 21st century in CMIP6 Earth system models. In general, we find a reduced spread of changes in global soil carbon in CMIP6 compared to the previous CMIP5 generation. The reduced CMIP6 spread arises from an emergent relationship between soil carbon changes due to change in plant productivity and soil carbon changes due to changes in turnover time. We show that this relationship is consistent with false priming under transient climate change.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, Almut Arneth, Stefanie Falk, Atul K. Jain, Fortunat Joos, Daniel Kennedy, Jürgen Knauer, Stephen Sitch, Michael O'Sullivan, Naiqing Pan, Qing Sun, Hanqin Tian, Nicolas Vuichard, and Sönke Zaehle
Earth Syst. Dynam., 14, 767–795, https://doi.org/10.5194/esd-14-767-2023, https://doi.org/10.5194/esd-14-767-2023, 2023
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Nitrogen (N) is an essential limiting nutrient to terrestrial carbon (C) sequestration. We evaluate N cycling in an ensemble of terrestrial biosphere models. We find that variability in N processes across models is large. Models tended to overestimate C storage per unit N in vegetation and soil, which could have consequences for projecting the future terrestrial C sink. However, N cycling measurements are highly uncertain, and more are necessary to guide the development of N cycling in models.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag
EGUsphere, https://doi.org/10.5194/egusphere-2023-1167, https://doi.org/10.5194/egusphere-2023-1167, 2023
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Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.
Nina Raoult, Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, and Vladislav Bastrikov
The Cryosphere, 17, 2705–2724, https://doi.org/10.5194/tc-17-2705-2023, https://doi.org/10.5194/tc-17-2705-2023, 2023
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Greenland ice sheet melting due to global warming could significantly impact global sea-level rise. The ice sheet's albedo, i.e. how reflective the surface is, affects the melting speed. The ORCHIDEE computer model is used to simulate albedo and snowmelt to make predictions. However, the albedo in ORCHIDEE is lower than that observed using satellites. To correct this, we change model parameters (e.g. the rate of snow decay) to reduce the difference between simulated and observed values.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
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This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Aparnna Ravi, Dhanyalekshmi Pillai, Christoph Gerbig, Stephen Sitch, Sönke Zaehle, Vishnu Thilakan, and Chandra Shekhar Jha
EGUsphere, https://doi.org/10.5194/egusphere-2023-817, https://doi.org/10.5194/egusphere-2023-817, 2023
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We derive high-resolution terrestrial CO2 fluxes over India from 2012 to 2020. This is achieved by utilizing satellite-based vegetation indices and meteorological data in a data-driven biospheric model. The model simulations are improved by incorporating soil variables and SIF retrievals from satellite instruments and relate them to ecosystem productivity across different biomes. The derived flux products better explain the flux variability compared to other existing model estimates.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Kandice L. Harper, Céline Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, and Pierre Defourny
Earth Syst. Sci. Data, 15, 1465–1499, https://doi.org/10.5194/essd-15-1465-2023, https://doi.org/10.5194/essd-15-1465-2023, 2023
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We built a spatially explicit annual plant-functional-type (PFT) dataset for 1992–2020 exhibiting intra-class spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of percentage cover are produced: bare soil, water, permanent snow/ice, built, managed grasses, natural grasses, and trees and shrubs, each split into leaf type and seasonality. Model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new set.
Forwood Wiser, Bryan K. Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
Geosci. Model Dev., 16, 1801–1821, https://doi.org/10.5194/gmd-16-1801-2023, https://doi.org/10.5194/gmd-16-1801-2023, 2023
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We developed a reduced model of atmospheric isoprene oxidation, AMORE-Isoprene 1.0. It was created using a new Automated Model Reduction (AMORE) method designed to simplify complex chemical mechanisms with minimal manual adjustments to the output. AMORE-Isoprene 1.0 has improved accuracy and similar size to other reduced isoprene mechanisms. When included in the CRACMM mechanism, it improved the accuracy of EPA’s CMAQ model predictions for the northeastern USA compared to observations.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Xiaoyong Li, Hanqin Tian, Chaoqun Lu, and Shufen Pan
Earth Syst. Sci. Data, 15, 1005–1035, https://doi.org/10.5194/essd-15-1005-2023, https://doi.org/10.5194/essd-15-1005-2023, 2023
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We reconstructed land use and land cover (LULC) history for the conterminous United States during 1630–2020 by integrating multi-source data. The results show the widespread expansion of cropland and urban land and the shrinking of natural vegetation in the past four centuries. Forest planting and regeneration accelerated forest recovery since the 1920s. The datasets can be used to assess the LULC impacts on the ecosystem's carbon, nitrogen, and water cycles.
Andrew F. Feldman, Zhen Zhang, Yasuko Yoshida, Abhishek Chatterjee, and Benjamin Poulter
Atmos. Chem. Phys., 23, 1545–1563, https://doi.org/10.5194/acp-23-1545-2023, https://doi.org/10.5194/acp-23-1545-2023, 2023
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We investigate the conditions under which satellite-retrieved column carbon dioxide concentrations directly hold information about surface carbon dioxide fluxes, without the use of inversion models. We show that OCO-2 column carbon dioxide retrievals, available at 1–3 month latency, can be used to directly detect and roughly estimate extreme biospheric CO2 fluxes. As such, these OCO-2 retrievals have value for rapidly monitoring extreme conditions in the terrestrial biosphere.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
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In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Benjamin Sapper, Daven Henze, Manjula Canagaratna, and Harald Stark
EGUsphere, https://doi.org/10.5194/egusphere-2022-1221, https://doi.org/10.5194/egusphere-2022-1221, 2022
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Positive Matrix Factorization (PMF) has been used by atmospheric scientists to extract underlying factors present in large datasets. This paper presents a new technique for weighted PMF that drastically reduces the computational costs of previously developed algorithms. We use this technique to deliver interpretative factors and solution diagnostics from an atmospheric chemistry dataset.
Rainer Schneck, Veronika Gayler, Julia E. M. S. Nabel, Thomas Raddatz, Christian H. Reick, and Reiner Schnur
Geosci. Model Dev., 15, 8581–8611, https://doi.org/10.5194/gmd-15-8581-2022, https://doi.org/10.5194/gmd-15-8581-2022, 2022
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The versions of ICON-A and ICON-Land/JSBACHv4 used for this study constitute the first milestone in the development of the new ICON Earth System Model ICON-ESM. JSBACHv4 is the successor of JSBACHv3, and most of the parameterizations of JSBACHv4 are re-implementations from JSBACHv3. We assess and compare the performance of JSBACHv4 and JSBACHv3. Overall, the JSBACHv4 results are as good as JSBACHv3, but both models reveal the same main shortcomings, e.g. the depiction of the leaf area index.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
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Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
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Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
Stephanie Woodward, Alistair A. Sellar, Yongming Tang, Marc Stringer, Andrew Yool, Eddy Robertson, and Andy Wiltshire
Atmos. Chem. Phys., 22, 14503–14528, https://doi.org/10.5194/acp-22-14503-2022, https://doi.org/10.5194/acp-22-14503-2022, 2022
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We describe the dust scheme in the UKESM1 Earth system model and show generally good agreement with observations. Comparing with the closely related HadGEM3-GC3.1 model, we show that dust differences are not only due to inter-model differences but also to the dust size distribution. Under climate change, HadGEM3-GC3.1 dust hardly changes, but UKESM1 dust decreases because that model includes the vegetation response which, in our models, has a bigger impact on dust than climate change itself.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Flossie Brown, Gerd A. Folberth, Stephen Sitch, Susanne Bauer, Marijn Bauters, Pascal Boeckx, Alexander W. Cheesman, Makoto Deushi, Inês Dos Santos Vieira, Corinne Galy-Lacaux, James Haywood, James Keeble, Lina M. Mercado, Fiona M. O'Connor, Naga Oshima, Kostas Tsigaridis, and Hans Verbeeck
Atmos. Chem. Phys., 22, 12331–12352, https://doi.org/10.5194/acp-22-12331-2022, https://doi.org/10.5194/acp-22-12331-2022, 2022
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Surface ozone can decrease plant productivity and impair human health. In this study, we evaluate the change in surface ozone due to climate change over South America and Africa using Earth system models. We find that if the climate were to change according to the worst-case scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of ozone exposure, but other areas will experience a climate benefit.
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
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The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Taraka Davies-Barnard, Sönke Zaehle, and Pierre Friedlingstein
Biogeosciences, 19, 3491–3503, https://doi.org/10.5194/bg-19-3491-2022, https://doi.org/10.5194/bg-19-3491-2022, 2022
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Biological nitrogen fixation is the largest natural input of new nitrogen onto land. Earth system models mainly represent global total terrestrial biological nitrogen fixation within observational uncertainties but overestimate tropical fixation. The model range of increase in biological nitrogen fixation in the SSP3-7.0 scenario is 3 % to 87 %. While biological nitrogen fixation is a key source of new nitrogen, its predictive power for net primary productivity in models is limited.
Taewon Cho, Julianne Chung, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 15, 5547–5565, https://doi.org/10.5194/gmd-15-5547-2022, https://doi.org/10.5194/gmd-15-5547-2022, 2022
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Atmospheric inverse modeling describes the process of estimating greenhouse gas fluxes or air pollution emissions at the Earth's surface using observations of these gases collected in the atmosphere. The launch of new satellites, the expansion of surface observation networks, and a desire for more detailed maps of surface fluxes have yielded numerous computational and statistical challenges. This article describes computationally efficient methods for large-scale atmospheric inverse modeling.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
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In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, https://doi.org/10.5194/gmd-15-4709-2022, 2022
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Peat-ML is a high-resolution global peatland extent map generated using machine learning techniques. Peatlands are important in the global carbon and water cycles, but their extent is poorly known. We generated Peat-ML using drivers of peatland formation including climate, soil, geomorphology, and vegetation data, and we train the model with regional peatland maps. Our accuracy estimation approaches suggest Peat-ML is of similar or higher quality than other available peatland mapping products.
Colm Sweeney, Abhishek Chatterjee, Sonja Wolter, Kathryn McKain, Robert Bogue, Stephen Conley, Tim Newberger, Lei Hu, Lesley Ott, Benjamin Poulter, Luke Schiferl, Brad Weir, Zhen Zhang, and Charles E. Miller
Atmos. Chem. Phys., 22, 6347–6364, https://doi.org/10.5194/acp-22-6347-2022, https://doi.org/10.5194/acp-22-6347-2022, 2022
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The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of aircraft profiles for independent evaluation of model-derived emissions and uptake of atmospheric CO2, CH4, and CO from land and ocean. Comparison with the Goddard Earth Observing System (GEOS) modeling system suggests that fluxes of CO2 are very consistent with observations, while those of CH4 have some regional and seasonal biases, and that CO comparison is complicated by transport errors.
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
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To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ruqi Yang, Jun Wang, Ning Zeng, Stephen Sitch, Wenhan Tang, Matthew Joseph McGrath, Qixiang Cai, Di Liu, Danica Lombardozzi, Hanqin Tian, Atul K. Jain, and Pengfei Han
Earth Syst. Dynam., 13, 833–849, https://doi.org/10.5194/esd-13-833-2022, https://doi.org/10.5194/esd-13-833-2022, 2022
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We comprehensively investigate historical GPP trends based on five kinds of GPP datasets and analyze the causes for any discrepancies among them. Results show contrasting behaviors between modeled and satellite-based GPP trends, and their inconsistencies are likely caused by the contrasting performance between satellite-derived and modeled leaf area index (LAI). Thus, the uncertainty in satellite-based GPP induced by LAI undermines its role in assessing the performance of DGVM simulations.
Mathilda Hancock, Stephen Sitch, Fabian Jörg Fischer, Jérôme Chave, Michael O'Sullivan, Dominic Fawcett, and Lina María Mercado
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-87, https://doi.org/10.5194/bg-2022-87, 2022
Publication in BG not foreseen
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Global vegetation models often underestimate the spatial variability of carbon stored in the Amazon forest. This paper demonstrates that including spatially varying tree mortality rates, as opposed to a homogeneous rate, in one model, significantly improves its simulations of the forest carbon store. To overcome the limited resolution of tree mortality data, this research presents a simple method of calculating mortality rates across Amazonia using a dependence on wood density.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Elisabeth Tschumi, Sebastian Lienert, Karin van der Wiel, Fortunat Joos, and Jakob Zscheischler
Biogeosciences, 19, 1979–1993, https://doi.org/10.5194/bg-19-1979-2022, https://doi.org/10.5194/bg-19-1979-2022, 2022
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Droughts and heatwaves are expected to occur more often in the future, but their effects on land vegetation and the carbon cycle are poorly understood. We use six climate scenarios with differing extreme occurrences and a vegetation model to analyse these effects. Tree coverage and associated plant productivity increase under a climate with no extremes. Frequent co-occurring droughts and heatwaves decrease plant productivity more than the combined effects of single droughts or heatwaves.
Elodie Salmon, Fabrice Jégou, Bertrand Guenet, Line Jourdain, Chunjing Qiu, Vladislav Bastrikov, Christophe Guimbaud, Dan Zhu, Philippe Ciais, Philippe Peylin, Sébastien Gogo, Fatima Laggoun-Défarge, Mika Aurela, M. Syndonia Bret-Harte, Jiquan Chen, Bogdan H. Chojnicki, Housen Chu, Colin W. Edgar, Eugenie S. Euskirchen, Lawrence B. Flanagan, Krzysztof Fortuniak, David Holl, Janina Klatt, Olaf Kolle, Natalia Kowalska, Lars Kutzbach, Annalea Lohila, Lutz Merbold, Włodzimierz Pawlak, Torsten Sachs, and Klaudia Ziemblińska
Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
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A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Guillaume Marie, B. Sebastiaan Luyssaert, Cecile Dardel, Thuy Le Toan, Alexandre Bouvet, Stéphane Mermoz, Ludovic Villard, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 15, 2599–2617, https://doi.org/10.5194/gmd-15-2599-2022, https://doi.org/10.5194/gmd-15-2599-2022, 2022
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Most Earth system models make use of vegetation maps to initialize a simulation at global scale. Satellite-based biomass map estimates for Africa were used to estimate cover fractions for the 15 land cover classes. This study successfully demonstrates that satellite-based biomass maps can be used to better constrain vegetation maps. Applying this approach at the global scale would increase confidence in assessments of present-day biomass stocks.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
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Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Hélène Peiro, Sean Crowell, Andrew Schuh, David F. Baker, Chris O'Dell, Andrew R. Jacobson, Frédéric Chevallier, Junjie Liu, Annmarie Eldering, David Crisp, Feng Deng, Brad Weir, Sourish Basu, Matthew S. Johnson, Sajeev Philip, and Ian Baker
Atmos. Chem. Phys., 22, 1097–1130, https://doi.org/10.5194/acp-22-1097-2022, https://doi.org/10.5194/acp-22-1097-2022, 2022
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Satellite CO2 observations are constantly improved. We study an ensemble of different atmospheric models (inversions) from 2015 to 2018 using separate ground-based data or two versions of the OCO-2 satellite. Our study aims to determine if different satellite data corrections can yield different estimates of carbon cycle flux. A difference in the carbon budget between the two versions is found over tropical Africa, which seems to show the impact of corrections applied in satellite data.
Xueying Yu, Dylan B. Millet, and Daven K. Henze
Geosci. Model Dev., 14, 7775–7793, https://doi.org/10.5194/gmd-14-7775-2021, https://doi.org/10.5194/gmd-14-7775-2021, 2021
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We conduct observing system simulation experiments to test how well inverse analyses of high-resolution satellite data from sensors such as TROPOMI can quantify methane emissions. Inversions can improve monthly flux estimates at 25 km even with a spatially biased prior or model transport errors, but results are strongly degraded when both are present. We further evaluate a set of alternate formalisms to overcome limitations of the widely used scale factor approach that arise for missing sources.
Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Yingping Wang, Julian Helfenstein, Yuanyuan Huang, Kailiang Yu, Zhiqiang Wang, Yongchuan Yang, and Enqing Hou
Earth Syst. Sci. Data, 13, 5831–5846, https://doi.org/10.5194/essd-13-5831-2021, https://doi.org/10.5194/essd-13-5831-2021, 2021
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Our database of globally distributed natural soil total P (STP) concentration showed concentration ranged from 1.4 to 9630.0 (mean 570.0) mg kg−1. Global predictions of STP concentration increased with latitude. Global STP stocks (excluding Antarctica) were estimated to be 26.8 and 62.2 Pg in the topsoil and subsoil, respectively. Our global map of STP concentration can be used to constrain Earth system models representing the P cycle and to inform quantification of global soil P availability.
Keith B. Rodgers, Sun-Seon Lee, Nan Rosenbloom, Axel Timmermann, Gokhan Danabasoglu, Clara Deser, Jim Edwards, Ji-Eun Kim, Isla R. Simpson, Karl Stein, Malte F. Stuecker, Ryohei Yamaguchi, Tamás Bódai, Eui-Seok Chung, Lei Huang, Who M. Kim, Jean-François Lamarque, Danica L. Lombardozzi, William R. Wieder, and Stephen G. Yeager
Earth Syst. Dynam., 12, 1393–1411, https://doi.org/10.5194/esd-12-1393-2021, https://doi.org/10.5194/esd-12-1393-2021, 2021
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A large ensemble of simulations with 100 members has been conducted with the state-of-the-art CESM2 Earth system model, using historical and SSP3-7.0 forcing. Our main finding is that there are significant changes in the variance of the Earth system in response to anthropogenic forcing, with these changes spanning a broad range of variables important to impacts for human populations and ecosystems.
István Dunkl, Aaron Spring, Pierre Friedlingstein, and Victor Brovkin
Earth Syst. Dynam., 12, 1413–1426, https://doi.org/10.5194/esd-12-1413-2021, https://doi.org/10.5194/esd-12-1413-2021, 2021
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The variability in atmospheric CO2 is largely controlled by terrestrial carbon fluxes. These land–atmosphere fluxes are predictable for around 2 years, but the mechanisms providing the predictability are not well understood. By decomposing the predictability of carbon fluxes into individual contributors we were able to explain the spatial and seasonal patterns and the interannual variability of CO2 flux predictability.
Yohanna Villalobos, Peter J. Rayner, Jeremy D. Silver, Steven Thomas, Vanessa Haverd, Jürgen Knauer, Zoë M. Loh, Nicholas M. Deutscher, David W. T. Griffith, and David F. Pollard
Atmos. Chem. Phys., 21, 17453–17494, https://doi.org/10.5194/acp-21-17453-2021, https://doi.org/10.5194/acp-21-17453-2021, 2021
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Semi-arid ecosystems such as those in Australia are evolving and might play an essential role in the future of climate change. We use carbon dioxide concentrations derived from the OCO-2 satellite instrument and a regional transport model to understand if Australia was a carbon sink or source of CO2 in 2015. Our research's main findings suggest that Australia acted as a carbon sink of about −0.41 ± 0.08 petagrams of carbon in 2015, driven primarily by savanna and sparsely vegetated ecosystems.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
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We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
Simon Besnard, Sujan Koirala, Maurizio Santoro, Ulrich Weber, Jacob Nelson, Jonas Gütter, Bruno Herault, Justin Kassi, Anny N'Guessan, Christopher Neigh, Benjamin Poulter, Tao Zhang, and Nuno Carvalhais
Earth Syst. Sci. Data, 13, 4881–4896, https://doi.org/10.5194/essd-13-4881-2021, https://doi.org/10.5194/essd-13-4881-2021, 2021
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Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. Yet, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. In this paper, we introduced a new global distribution of forest age inferred from forest inventory, remote sensing and climate data in support of a better understanding of the global dynamics in the forest water and carbon cycles.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Claude-Michel Nzotungicimpaye, Kirsten Zickfeld, Andrew H. MacDougall, Joe R. Melton, Claire C. Treat, Michael Eby, and Lance F. W. Lesack
Geosci. Model Dev., 14, 6215–6240, https://doi.org/10.5194/gmd-14-6215-2021, https://doi.org/10.5194/gmd-14-6215-2021, 2021
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In this paper, we describe a new wetland methane model (WETMETH) developed for use in Earth system models. WETMETH consists of simple formulations to represent methane production and oxidation in wetlands. We also present an evaluation of the model performance as embedded in the University of Victoria Earth System Climate Model (UVic ESCM). WETMETH is capable of reproducing mean annual methane emissions consistent with present-day estimates from the regional to the global scale.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Jina Jeong, Jonathan Barichivich, Philippe Peylin, Vanessa Haverd, Matthew Joseph McGrath, Nicolas Vuichard, Michael Neil Evans, Flurin Babst, and Sebastiaan Luyssaert
Geosci. Model Dev., 14, 5891–5913, https://doi.org/10.5194/gmd-14-5891-2021, https://doi.org/10.5194/gmd-14-5891-2021, 2021
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We have proposed and evaluated the use of four benchmarks that leverage tree-ring width observations to provide more nuanced verification targets for land-surface models (LSMs), which currently lack a long-term benchmark for forest ecosystem functioning. Using relatively unbiased European biomass network datasets, we identify the extent to which presumed biases in the much larger International Tree-Ring Data Bank might degrade the validation of LSMs.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
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Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
Yuanyuan Huang, Phillipe Ciais, Maurizio Santoro, David Makowski, Jerome Chave, Dmitry Schepaschenko, Rose Z. Abramoff, Daniel S. Goll, Hui Yang, Ye Chen, Wei Wei, and Shilong Piao
Earth Syst. Sci. Data, 13, 4263–4274, https://doi.org/10.5194/essd-13-4263-2021, https://doi.org/10.5194/essd-13-4263-2021, 2021
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Roots play a key role in our Earth system. Here we combine 10 307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially explicit global high-resolution (~ 1 km) root biomass dataset. In total, 142 ± 25 (95 % CI) Pg of live dry-matter biomass is stored belowground, representing a global average root : shoot biomass ratio of 0.25 ± 0.10.
Louise Chini, George Hurtt, Ritvik Sahajpal, Steve Frolking, Kees Klein Goldewijk, Stephen Sitch, Raphael Ganzenmüller, Lei Ma, Lesley Ott, Julia Pongratz, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 4175–4189, https://doi.org/10.5194/essd-13-4175-2021, https://doi.org/10.5194/essd-13-4175-2021, 2021
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Carbon emissions from land-use change are a large and uncertain component of the global carbon cycle. The Land-Use Harmonization 2 (LUH2) dataset was developed as an input to carbon and climate simulations and has been updated annually for the Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2 updates and describe the 2019 version which used new cropland and grazing land data inputs for the globally important region of Brazil.
Xiaoling Liu, August L. Weinbren, He Chang, Jovan M. Tadić, Marikate E. Mountain, Michael E. Trudeau, Arlyn E. Andrews, Zichong Chen, and Scot M. Miller
Geosci. Model Dev., 14, 4683–4696, https://doi.org/10.5194/gmd-14-4683-2021, https://doi.org/10.5194/gmd-14-4683-2021, 2021
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Observations of greenhouse gases have become far more numerous in recent years due to new satellite observations. The sheer size of these datasets makes it challenging to incorporate these data into statistical models and use these data to estimate greenhouse gas sources and sinks. In this paper, we develop an approach to reduce the size of these datasets while preserving the most information possible. We subsequently test this approach using satellite observations of carbon dioxide.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Benjamin A. Nault, Duseong S. Jo, Brian C. McDonald, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Jason C. Schroder, James Allan, Donald R. Blake, Manjula R. Canagaratna, Hugh Coe, Matthew M. Coggon, Peter F. DeCarlo, Glenn S. Diskin, Rachel Dunmore, Frank Flocke, Alan Fried, Jessica B. Gilman, Georgios Gkatzelis, Jacqui F. Hamilton, Thomas F. Hanisco, Patrick L. Hayes, Daven K. Henze, Alma Hodzic, James Hopkins, Min Hu, L. Greggory Huey, B. Thomas Jobson, William C. Kuster, Alastair Lewis, Meng Li, Jin Liao, M. Omar Nawaz, Ilana B. Pollack, Jeffrey Peischl, Bernhard Rappenglück, Claire E. Reeves, Dirk Richter, James M. Roberts, Thomas B. Ryerson, Min Shao, Jacob M. Sommers, James Walega, Carsten Warneke, Petter Weibring, Glenn M. Wolfe, Dominique E. Young, Bin Yuan, Qiang Zhang, Joost A. de Gouw, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 11201–11224, https://doi.org/10.5194/acp-21-11201-2021, https://doi.org/10.5194/acp-21-11201-2021, 2021
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Secondary organic aerosol (SOA) is an important aspect of poor air quality for urban regions around the world, where a large fraction of the population lives. However, there is still large uncertainty in predicting SOA in urban regions. Here, we used data from 11 urban campaigns and show that the variability in SOA production in these regions is predictable and is explained by key emissions. These results are used to estimate the premature mortality associated with SOA in urban regions.
Ana Bastos, Kerstin Hartung, Tobias B. Nützel, Julia E. M. S. Nabel, Richard A. Houghton, and Julia Pongratz
Earth Syst. Dynam., 12, 745–762, https://doi.org/10.5194/esd-12-745-2021, https://doi.org/10.5194/esd-12-745-2021, 2021
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Fluxes from land-use change and management (FLUC) are a large source of uncertainty in global and regional carbon budgets. Here, we evaluate the impact of different model parameterisations on FLUC. We show that carbon stock densities and allocation of carbon following transitions contribute more to uncertainty in FLUC than response-curve time constants. Uncertainty in FLUC could thus, in principle, be reduced by available Earth-observation data on carbon densities at a global scale.
Kerstin Hartung, Ana Bastos, Louise Chini, Raphael Ganzenmüller, Felix Havermann, George C. Hurtt, Tammas Loughran, Julia E. M. S. Nabel, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Earth Syst. Dynam., 12, 763–782, https://doi.org/10.5194/esd-12-763-2021, https://doi.org/10.5194/esd-12-763-2021, 2021
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In this study, we model the relative importance of several contributors to the land-use and land-cover change (LULCC) flux based on a LULCC dataset including uncertainty estimates. The uncertainty of LULCC is as relevant as applying wood harvest and gross transitions for the cumulative LULCC flux over the industrial period. However, LULCC uncertainty matters less than the other two factors for the LULCC flux in 2014; historical LULCC uncertainty is negligible for estimates of future scenarios.
Brad Weir, Lesley E. Ott, George J. Collatz, Stephan R. Kawa, Benjamin Poulter, Abhishek Chatterjee, Tomohiro Oda, and Steven Pawson
Atmos. Chem. Phys., 21, 9609–9628, https://doi.org/10.5194/acp-21-9609-2021, https://doi.org/10.5194/acp-21-9609-2021, 2021
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We present a collection of carbon surface fluxes, the Low-order Flux Inversion (LoFI), derived from satellite observations of the Earth's surface and calibrated to match long-term inventories and atmospheric and oceanic records. Simulations using LoFI reproduce background atmospheric carbon dioxide measurements with comparable skill to the leading surface flux products. Available both retrospectively and as a forecast, LoFI enables the study of the carbon cycle as it occurs.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Martin Keller, Daven K. Henze, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Atmos. Chem. Phys., 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021, https://doi.org/10.5194/acp-21-9545-2021, 2021
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We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
Na Zhao, Xinyi Dong, Kan Huang, Joshua S. Fu, Marianne Tronstad Lund, Kengo Sudo, Daven Henze, Tom Kucsera, Yun Fat Lam, Mian Chin, and Simone Tilmes
Atmos. Chem. Phys., 21, 8637–8654, https://doi.org/10.5194/acp-21-8637-2021, https://doi.org/10.5194/acp-21-8637-2021, 2021
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Black carbon acts as a strong climate forcer, especially in vulnerable pristine regions such as the Arctic. This work utilizes ensemble modeling results from the task force Hemispheric Transport of Air Pollution Phase 2 to investigate the responses of Arctic black carbon and surface temperature to various source emission reductions. East Asia contributed the most to Arctic black carbon. The response of Arctic temperature to black carbon was substantially more sensitive than the global average.
Leah Birch, Christopher R. Schwalm, Sue Natali, Danica Lombardozzi, Gretchen Keppel-Aleks, Jennifer Watts, Xin Lin, Donatella Zona, Walter Oechel, Torsten Sachs, Thomas Andrew Black, and Brendan M. Rogers
Geosci. Model Dev., 14, 3361–3382, https://doi.org/10.5194/gmd-14-3361-2021, https://doi.org/10.5194/gmd-14-3361-2021, 2021
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The high-latitude landscape or Arctic–boreal zone has been warming rapidly, impacting the carbon balance both regionally and globally. Given the possible global effects of climate change, it is important to have accurate climate model simulations. We assess the simulation of the Arctic–boreal carbon cycle in the Community Land Model (CLM 5.0). We find biases in both the timing and magnitude photosynthesis. We then use observational data to improve the simulation of the carbon cycle.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Gesa Meyer, Elyn R. Humphreys, Joe R. Melton, Alex J. Cannon, and Peter M. Lafleur
Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, https://doi.org/10.5194/bg-18-3263-2021, 2021
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Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
Martina Franz and Sönke Zaehle
Biogeosciences, 18, 3219–3241, https://doi.org/10.5194/bg-18-3219-2021, https://doi.org/10.5194/bg-18-3219-2021, 2021
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The combined effects of ozone and nitrogen deposition on the terrestrial carbon uptake and storage has been unclear. Our simulations, from 1850 to 2099, show that ozone-related damage considerably reduced gross primary production and carbon storage in the past. The growth-stimulating effect induced by nitrogen deposition is offset until the 2050s. Accounting for nitrogen deposition without considering ozone effects might lead to an overestimation of terrestrial carbon uptake and storage.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
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We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Leonardo Calle and Benjamin Poulter
Geosci. Model Dev., 14, 2575–2601, https://doi.org/10.5194/gmd-14-2575-2021, https://doi.org/10.5194/gmd-14-2575-2021, 2021
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We developed a model to simulate and track the age of ecosystems on Earth. We found that the effect of ecosystem age on net primary production and ecosystem respiration is as important as climate in large areas of every vegetated continent. The LPJ-wsl v2.0 age-class model simulates dynamic age-class distributions on Earth and represents another step forward towards understanding the role of demography in global ecosystems.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
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We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Christian Seiler, Joe R. Melton, Vivek K. Arora, and Libo Wang
Geosci. Model Dev., 14, 2371–2417, https://doi.org/10.5194/gmd-14-2371-2021, https://doi.org/10.5194/gmd-14-2371-2021, 2021
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This study evaluates how well the CLASSIC land surface model reproduces the energy, water, and carbon cycle when compared against a wide range of global observations. Special attention is paid to how uncertainties in the data used to drive and evaluate the model affect model skill. Our results show the importance of incorporating uncertainties when evaluating land surface models and that failing to do so may potentially misguide future model development.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
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Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Hiroki Mizuochi, Agnès Ducharne, Frédérique Cheruy, Josefine Ghattas, Amen Al-Yaari, Jean-Pierre Wigneron, Vladislav Bastrikov, Philippe Peylin, Fabienne Maignan, and Nicolas Vuichard
Hydrol. Earth Syst. Sci., 25, 2199–2221, https://doi.org/10.5194/hess-25-2199-2021, https://doi.org/10.5194/hess-25-2199-2021, 2021
Daniele Peano, Deborah Hemming, Stefano Materia, Christine Delire, Yuanchao Fan, Emilie Joetzjer, Hanna Lee, Julia E. M. S. Nabel, Taejin Park, Philippe Peylin, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Biogeosciences, 18, 2405–2428, https://doi.org/10.5194/bg-18-2405-2021, https://doi.org/10.5194/bg-18-2405-2021, 2021
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Global climate models are the scientist’s tools used for studying past, present, and future climate conditions. This work examines the ability of a group of our tools in reproducing and capturing the right timing and length of the season when plants show their green leaves. This season, indeed, is fundamental for CO2 exchanges between land, atmosphere, and climate. This work shows that discrepancies compared to observations remain, demanding further polishing of these tools.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, https://doi.org/10.5194/gmd-14-1987-2021, 2021
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We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Zihao Bian, Hanqin Tian, Qichun Yang, Rongting Xu, Shufen Pan, and Bowen Zhang
Earth Syst. Sci. Data, 13, 515–527, https://doi.org/10.5194/essd-13-515-2021, https://doi.org/10.5194/essd-13-515-2021, 2021
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The estimation of manure nutrient production and application is critical for the efficient use of manure nutrients. This study developed four manure nitrogen and phosphorus datasets with high spatial resolution and a long time period (1860–2017) in the US. The datasets can provide useful information for stakeholders and scientists who focus on agriculture, nutrient budget, and biogeochemical cycle.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
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Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Fiona M. O'Connor, N. Luke Abraham, Mohit Dalvi, Gerd A. Folberth, Paul T. Griffiths, Catherine Hardacre, Ben T. Johnson, Ron Kahana, James Keeble, Byeonghyeon Kim, Olaf Morgenstern, Jane P. Mulcahy, Mark Richardson, Eddy Robertson, Jeongbyn Seo, Sungbo Shim, João C. Teixeira, Steven T. Turnock, Jonny Williams, Andrew J. Wiltshire, Stephanie Woodward, and Guang Zeng
Atmos. Chem. Phys., 21, 1211–1243, https://doi.org/10.5194/acp-21-1211-2021, https://doi.org/10.5194/acp-21-1211-2021, 2021
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This paper calculates how changes in emissions and/or concentrations of different atmospheric constituents since the pre-industrial era have altered the Earth's energy budget at the present day using a metric called effective radiative forcing. The impact of land use change is also assessed. We find that individual contributions do not add linearly, and different Earth system interactions can affect the magnitude of the calculated effective radiative forcing.
Camilla Mathison, Andrew J. Challinor, Chetan Deva, Pete Falloon, Sébastien Garrigues, Sophie Moulin, Karina Williams, and Andy Wiltshire
Geosci. Model Dev., 14, 437–471, https://doi.org/10.5194/gmd-14-437-2021, https://doi.org/10.5194/gmd-14-437-2021, 2021
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Sequential cropping (also known as multiple or double cropping) is a common cropping system, particularly in tropical regions. Typically, land surface models only simulate a single crop per year. To understand how sequential crops influence surface fluxes, we implement sequential cropping in JULES to simulate all the crops grown within a year at a given location in a seamless way. We demonstrate the method using a site in Avignon, four locations in India and a regional run for two Indian states.
Xueying Yu, Dylan B. Millet, Kelley C. Wells, Daven K. Henze, Hansen Cao, Timothy J. Griffis, Eric A. Kort, Genevieve Plant, Malte J. Deventer, Randall K. Kolka, D. Tyler Roman, Kenneth J. Davis, Ankur R. Desai, Bianca C. Baier, Kathryn McKain, Alan C. Czarnetzki, and A. Anthony Bloom
Atmos. Chem. Phys., 21, 951–971, https://doi.org/10.5194/acp-21-951-2021, https://doi.org/10.5194/acp-21-951-2021, 2021
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Methane concentrations have doubled since 1750. The US Upper Midwest is a key region contributing to such trends, but sources are poorly understood. We collected and analyzed aircraft data to resolve spatial and timing biases in wetland and livestock emission estimates and uncover errors in inventory treatment of manure management. We highlight the importance of intensive agriculture for the regional and US methane budgets and the potential for methane mitigation through improved management.
Sudhanshu Pandey, Sander Houweling, Alba Lorente, Tobias Borsdorff, Maria Tsivlidou, A. Anthony Bloom, Benjamin Poulter, Zhen Zhang, and Ilse Aben
Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, https://doi.org/10.5194/bg-18-557-2021, 2021
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We use atmospheric methane observations from the novel TROPOspheric Monitoring Instrument (TROPOMI; Sentinel-5p) to estimate methane emissions from South Sudan's wetlands. Our emission estimates are an order of magnitude larger than the estimate of process-based wetland models. We find that this underestimation by the models is likely due to their misrepresentation of the wetlands' inundation extent and temperature dependences.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, and David S. Schimel
Biogeosciences, 17, 6393–6422, https://doi.org/10.5194/bg-17-6393-2020, https://doi.org/10.5194/bg-17-6393-2020, 2020
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We use a model of the 2001–2015 tropical land carbon cycle, with satellite measurements of land and atmospheric carbon, to disentangle lagged and concurrent effects (due to past and concurrent meteorological events, respectively) on annual land–atmosphere carbon exchanges. The variability of lagged effects explains most 2001–2015 inter-annual carbon flux variations. We conclude that concurrent and lagged effects need to be accurately resolved to better predict the world's land carbon sink.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Bettina K. Gier, Michael Buchwitz, Maximilian Reuter, Peter M. Cox, Pierre Friedlingstein, and Veronika Eyring
Biogeosciences, 17, 6115–6144, https://doi.org/10.5194/bg-17-6115-2020, https://doi.org/10.5194/bg-17-6115-2020, 2020
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Models from Coupled Model Intercomparison Project (CMIP) phases 5 and 6 are compared to a satellite data product of column-averaged CO2 mole fractions (XCO2). The previously believed discrepancy of the negative trend in seasonal cycle amplitude in the satellite product, which is not seen in in situ data nor in the models, is attributed to a sampling characteristic. Furthermore, CMIP6 models are shown to have made progress in reproducing the observed XCO2 time series compared to CMIP5.
Felix Leung, Karina Williams, Stephen Sitch, Amos P. K. Tai, Andy Wiltshire, Jemma Gornall, Elizabeth A. Ainsworth, Timothy Arkebauer, and David Scoby
Geosci. Model Dev., 13, 6201–6213, https://doi.org/10.5194/gmd-13-6201-2020, https://doi.org/10.5194/gmd-13-6201-2020, 2020
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Ground-level ozone (O3) is detrimental to plant productivity and crop yield. Currently, the Joint UK Land Environment Simulator (JULES) includes a representation of crops (JULES-crop). The parameters for O3 damage in soybean in JULES-crop were calibrated against photosynthesis measurements from the Soybean Free Air Concentration Enrichment (SoyFACE). The result shows good performance for yield, and it helps contribute to understanding of the impacts of climate and air pollution on food security.
Yonghong Yi, John S. Kimball, Jennifer D. Watts, Susan M. Natali, Donatella Zona, Junjie Liu, Masahito Ueyama, Hideki Kobayashi, Walter Oechel, and Charles E. Miller
Biogeosciences, 17, 5861–5882, https://doi.org/10.5194/bg-17-5861-2020, https://doi.org/10.5194/bg-17-5861-2020, 2020
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We developed a 1 km satellite-data-driven permafrost carbon model to evaluate soil respiration sensitivity to recent snow cover changes in Alaska. Results show earlier snowmelt enhances growing-season soil respiration and reduces annual carbon uptake, while early cold-season soil respiration is linked to the number of snow-free days after the land surface freezes. Our results also show nonnegligible influences of subgrid variability in surface conditions on model-simulated CO2 seasonal cycles.
Tea Thum, Julia E. M. S. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, Tiina Markkanen, Julia Pongratz, Yukio Yoshida, and Sönke Zaehle
Biogeosciences, 17, 5721–5743, https://doi.org/10.5194/bg-17-5721-2020, https://doi.org/10.5194/bg-17-5721-2020, 2020
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Global vegetation models are important tools in estimating the impacts of global climate change. The fate of soil carbon is of the upmost importance as its emissions will enhance the atmospheric carbon dioxide concentration. To evaluate the skill of global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources. We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations.
George C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed O. Kaplan, Jennifer Kennedy, Tamás Krisztin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. van Vuuren, and Xin Zhang
Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, https://doi.org/10.5194/gmd-13-5425-2020, 2020
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To estimate the effects of human land use activities on the carbon–climate system, a new set of global gridded land use forcing datasets was developed to link historical land use data to eight future scenarios in a standard format required by climate models. This new generation of land use harmonization (LUH2) includes updated inputs, higher spatial resolution, more detailed land use transitions, and the addition of important agricultural management layers; it will be used for CMIP6 simulations.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Zhen Qu, Daven K. Henze, Owen R. Cooper, and Jessica L. Neu
Atmos. Chem. Phys., 20, 13109–13130, https://doi.org/10.5194/acp-20-13109-2020, https://doi.org/10.5194/acp-20-13109-2020, 2020
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We use satellite observations and chemical transport modeling to quantify sources of NOx, a major air pollutant, over the past decade. We find improved simulations of the magnitude, seasonality, and trends of NO2 and ozone concentrations using these derived emissions. Changes in ozone pollution driven by human and natural sources are identified in different regions. This work shows the benefits of remote-sensing data and inverse modeling for more accurate ozone simulations.
Yiqi Zheng, Joel A. Thornton, Nga Lee Ng, Hansen Cao, Daven K. Henze, Erin E. McDuffie, Weiwei Hu, Jose L. Jimenez, Eloise A. Marais, Eric Edgerton, and Jingqiu Mao
Atmos. Chem. Phys., 20, 13091–13107, https://doi.org/10.5194/acp-20-13091-2020, https://doi.org/10.5194/acp-20-13091-2020, 2020
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This study aims to address a challenge in biosphere–atmosphere interactions: to what extent can biogenic organic aerosol (OA) be modified through human activities? From three surface network observations, we show OA is weakly dependent on sulfate and aerosol acidity in the summer southeast US, on both long-term trends and monthly variability. The results are in strong contrast to a global model, GEOS-Chem, suggesting the need to revisit the representation of aqueous-phase secondary OA formation.
Rachel L. Tunnicliffe, Anita L. Ganesan, Robert J. Parker, Hartmut Boesch, Nicola Gedney, Benjamin Poulter, Zhen Zhang, Jošt V. Lavrič, David Walter, Matthew Rigby, Stephan Henne, Dickon Young, and Simon O'Doherty
Atmos. Chem. Phys., 20, 13041–13067, https://doi.org/10.5194/acp-20-13041-2020, https://doi.org/10.5194/acp-20-13041-2020, 2020
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This study quantifies Brazil’s emissions of a potent atmospheric greenhouse gas, methane. This is in the field of atmospheric modelling and uses remotely sensed data and surface measurements of methane concentrations as well as an atmospheric transport model to interpret the data. Because of Brazil’s large emissions from wetlands, agriculture and biomass burning, these emissions affect global methane concentrations and thus are of global significance.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
Tokuta Yokohata, Tsuguki Kinoshita, Gen Sakurai, Yadu Pokhrel, Akihiko Ito, Masashi Okada, Yusuke Satoh, Etsushi Kato, Tomoko Nitta, Shinichiro Fujimori, Farshid Felfelani, Yoshimitsu Masaki, Toshichika Iizumi, Motoki Nishimori, Naota Hanasaki, Kiyoshi Takahashi, Yoshiki Yamagata, and Seita Emori
Geosci. Model Dev., 13, 4713–4747, https://doi.org/10.5194/gmd-13-4713-2020, https://doi.org/10.5194/gmd-13-4713-2020, 2020
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The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balances, human water management, and crop growth incorporates a land-use decision-making model based on economic activities. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand.
Arthur P. K. Argles, Jonathan R. Moore, Chris Huntingford, Andrew J. Wiltshire, Anna B. Harper, Chris D. Jones, and Peter M. Cox
Geosci. Model Dev., 13, 4067–4089, https://doi.org/10.5194/gmd-13-4067-2020, https://doi.org/10.5194/gmd-13-4067-2020, 2020
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The Robust Ecosystem Demography (RED) model simulates cohorts of vegetation through mass classes. RED establishes a framework for representing demographic changes through competition, growth, and mortality across the size distribution of a forest. The steady state of the model can be solved analytically, enabling initialization. When driven by mean growth rates from a land-surface model, RED is able to fit the observed global vegetation map, giving a map of implicit mortality rates.
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris D. Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Olivier Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Emilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, Rachel M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry F. Tjiputra, Andy Wiltshire, Tongwen Wu, and Tilo Ziehn
Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, https://doi.org/10.5194/bg-17-4173-2020, 2020
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Since the preindustrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans. Comparison of different earth system models with the carbon cycle allows us to assess how carbon uptake by land and ocean differs among models. This yields an estimate of uncertainty in our understanding of how land and ocean respond to increasing atmospheric CO2. This paper summarizes results from two such model intercomparison projects that use an idealized scenario.
Christopher J. Smith, Ryan J. Kramer, Gunnar Myhre, Kari Alterskjær, William Collins, Adriana Sima, Olivier Boucher, Jean-Louis Dufresne, Pierre Nabat, Martine Michou, Seiji Yukimoto, Jason Cole, David Paynter, Hideo Shiogama, Fiona M. O'Connor, Eddy Robertson, Andy Wiltshire, Timothy Andrews, Cécile Hannay, Ron Miller, Larissa Nazarenko, Alf Kirkevåg, Dirk Olivié, Stephanie Fiedler, Anna Lewinschal, Chloe Mackallah, Martin Dix, Robert Pincus, and Piers M. Forster
Atmos. Chem. Phys., 20, 9591–9618, https://doi.org/10.5194/acp-20-9591-2020, https://doi.org/10.5194/acp-20-9591-2020, 2020
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The spread in effective radiative forcing for both CO2 and aerosols is narrower in the latest CMIP6 (Coupled Model Intercomparison Project) generation than in CMIP5. For the case of CO2 it is likely that model radiation parameterisations have improved. Tropospheric and stratospheric radiative adjustments to the forcing behave differently for different forcing agents, and there is still significant diversity in how clouds respond to forcings, particularly for total anthropogenic forcing.
Thomas A. M. Pugh, Tim Rademacher, Sarah L. Shafer, Jörg Steinkamp, Jonathan Barichivich, Brian Beckage, Vanessa Haverd, Anna Harper, Jens Heinke, Kazuya Nishina, Anja Rammig, Hisashi Sato, Almut Arneth, Stijn Hantson, Thomas Hickler, Markus Kautz, Benjamin Quesada, Benjamin Smith, and Kirsten Thonicke
Biogeosciences, 17, 3961–3989, https://doi.org/10.5194/bg-17-3961-2020, https://doi.org/10.5194/bg-17-3961-2020, 2020
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The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle. Estimates from six contemporary models found this time to range from 12.2 to 23.5 years for the global mean for 1985–2014. Future projections do not give consistent results, but 13 model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce large current uncertainty.
Shilpa Gahlot, Tzu-Shun Lin, Atul K. Jain, Somnath Baidya Roy, Vinay K. Sehgal, and Rajkumar Dhakar
Earth Syst. Dynam., 11, 641–652, https://doi.org/10.5194/esd-11-641-2020, https://doi.org/10.5194/esd-11-641-2020, 2020
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Spring wheat, a staple for millions of people in India and the world, is vulnerable to changing environmental and management factors. Using a new spring wheat model, we find that over the 1980–2016 period elevated CO2 levels, irrigation, and nitrogen fertilizers led to an increase of 30 %, 12 %, and 15 % in countrywide production, respectively. In contrast, rising temperatures have reduced production by 18 %. These effects vary across the country, thereby affecting production at regional scales.
Pierre St-Laurent, Marjorie A. M. Friedrichs, Raymond G. Najjar, Elizabeth H. Shadwick, Hanqin Tian, and Yuanzhi Yao
Biogeosciences, 17, 3779–3796, https://doi.org/10.5194/bg-17-3779-2020, https://doi.org/10.5194/bg-17-3779-2020, 2020
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Over the past century, estuaries have experienced global (atmospheric CO2 concentrations and temperature) and regional changes (river inputs, land use), but their relative impact remains poorly known. In the Chesapeake Bay, we find that global and regional changes have worked together to enhance how much atmospheric CO2 is taken up by the estuary. The increased uptake is roughly equally due to the global and regional changes, providing crucial perspective for managers of the bay's watershed.
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, https://doi.org/10.5194/gmd-13-3299-2020, 2020
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Global fire–vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes. Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
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Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
Fortunat Joos, Renato Spahni, Benjamin D. Stocker, Sebastian Lienert, Jurek Müller, Hubertus Fischer, Jochen Schmitt, I. Colin Prentice, Bette Otto-Bliesner, and Zhengyu Liu
Biogeosciences, 17, 3511–3543, https://doi.org/10.5194/bg-17-3511-2020, https://doi.org/10.5194/bg-17-3511-2020, 2020
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Results of the first globally resolved simulations of terrestrial carbon and nitrogen (N) cycling and N2O emissions over the past 21 000 years are compared with reconstructed N2O emissions. Modelled and reconstructed emissions increased strongly during past abrupt warming events. This evidence appears consistent with a dynamic response of biological N fixation to increasing N demand by ecosystems, thereby reducing N limitation of plant productivity and supporting a land sink for atmospheric CO2.
Shunliu Zhao, Matthew G. Russell, Amir Hakami, Shannon L. Capps, Matthew D. Turner, Daven K. Henze, Peter B. Percell, Jaroslav Resler, Huizhong Shen, Armistead G. Russell, Athanasios Nenes, Amanda J. Pappin, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Charles O. Stanier, and Tianfeng Chai
Geosci. Model Dev., 13, 2925–2944, https://doi.org/10.5194/gmd-13-2925-2020, https://doi.org/10.5194/gmd-13-2925-2020, 2020
Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup
Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, https://doi.org/10.5194/gmd-13-2825-2020, 2020
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We transitioned the CLASS-CTEM land surface model to an open-source community model format by modernizing the code base to make the model easier to use and understand, providing a complete software environment to run the model within, developing a benchmarking suite for model evaluation, and creating an infrastructure to support community involvement. The new model, the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC), is now available for the community to use and develop.
Matthew J. Cooper, Randall V. Martin, Daven K. Henze, and Dylan B. A. Jones
Atmos. Chem. Phys., 20, 7231–7241, https://doi.org/10.5194/acp-20-7231-2020, https://doi.org/10.5194/acp-20-7231-2020, 2020
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Comparisons between satellite-retrieved and model-simulated NO2 columns are affected by differences between the model vertical profile and the assumed profile used in the retrieval process. We examine how such differences impact NOx emission estimates from satellite observations. Larger differences between the simulated and assumed profile shape correspond to larger emission errors. This reveals the importance of using consistent profile information when comparing satellite columns to models.
Andrew H. MacDougall, Thomas L. Frölicher, Chris D. Jones, Joeri Rogelj, H. Damon Matthews, Kirsten Zickfeld, Vivek K. Arora, Noah J. Barrett, Victor Brovkin, Friedrich A. Burger, Micheal Eby, Alexey V. Eliseev, Tomohiro Hajima, Philip B. Holden, Aurich Jeltsch-Thömmes, Charles Koven, Nadine Mengis, Laurie Menviel, Martine Michou, Igor I. Mokhov, Akira Oka, Jörg Schwinger, Roland Séférian, Gary Shaffer, Andrei Sokolov, Kaoru Tachiiri, Jerry Tjiputra, Andrew Wiltshire, and Tilo Ziehn
Biogeosciences, 17, 2987–3016, https://doi.org/10.5194/bg-17-2987-2020, https://doi.org/10.5194/bg-17-2987-2020, 2020
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The Zero Emissions Commitment (ZEC) is the change in global temperature expected to occur following the complete cessation of CO2 emissions. Here we use 18 climate models to assess the value of ZEC. For our experiment we find that ZEC 50 years after emissions cease is between −0.36 to +0.29 °C. The most likely value of ZEC is assessed to be close to zero. However, substantial continued warming for decades or centuries following cessation of CO2 emission cannot be ruled out.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
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Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Yi Wang, Jun Wang, Xiaoguang Xu, Daven K. Henze, Zhen Qu, and Kai Yang
Atmos. Chem. Phys., 20, 6631–6650, https://doi.org/10.5194/acp-20-6631-2020, https://doi.org/10.5194/acp-20-6631-2020, 2020
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The use of OMPS satellite observations to inverse-model SO2 and NO2 emissions is presented through the GEOS-Chem adjoint modeling framework. The work is illustrated over China. The robustness of the results is studied through separate and joint inversions of SO2 and NO2 and the consideration of NH3 uncertainty. Independent validation is performed with OMI SO2 and NO2 data. It is shown that simultaneous inversion of NO2 and SO2 from OMPS provides an effective way to rapidly update emissions.
Yi Wang, Jun Wang, Meng Zhou, Daven K. Henze, Cui Ge, and Wei Wang
Atmos. Chem. Phys., 20, 6651–6670, https://doi.org/10.5194/acp-20-6651-2020, https://doi.org/10.5194/acp-20-6651-2020, 2020
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We developed four different methods to downscale SO2 and NO2 emissions derived from OMPS satellite observations (in Part 1) for regional air quality modeling at a spatial resolution that is finer than satellite observations. The VIIRS (city lights), TROPOMI, and OMI satellite data as well as surface data are used to evaluate the model. The method of using the top-down emissions from the past month for the air quality forecast in the present month is also shown to have practical merit.
Doug McNeall, Jonny Williams, Richard Betts, Ben Booth, Peter Challenor, Peter Good, and Andy Wiltshire
Geosci. Model Dev., 13, 2487–2509, https://doi.org/10.5194/gmd-13-2487-2020, https://doi.org/10.5194/gmd-13-2487-2020, 2020
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In the climate model FAMOUS, matching the modelled Amazon rainforest to observations required different land surface parameter settings than for other forests. It was unclear if this discrepancy was due to a bias in the modelled climate or an error in the land surface component of the model. Correcting the climate of the model with a statistical model corrects the simulation of the Amazon forest, suggesting that the land surface component of the model is not the source of the discrepancy.
Sojin Lee, Chul Han Song, Kyung Man Han, Daven K. Henze, Kyunghwa Lee, Jinhyeok Yu, Jung-Hun Woo, Jia Jung, Yunsoo Choi, Pablo E. Saide, and Gregory R. Carmichael
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-116, https://doi.org/10.5194/gmd-2020-116, 2020
Revised manuscript not accepted
Ana Maria Roxana Petrescu, Glen P. Peters, Greet Janssens-Maenhout, Philippe Ciais, Francesco N. Tubiello, Giacomo Grassi, Gert-Jan Nabuurs, Adrian Leip, Gema Carmona-Garcia, Wilfried Winiwarter, Lena Höglund-Isaksson, Dirk Günther, Efisio Solazzo, Anja Kiesow, Ana Bastos, Julia Pongratz, Julia E. M. S. Nabel, Giulia Conchedda, Roberto Pilli, Robbie M. Andrew, Mart-Jan Schelhaas, and Albertus J. Dolman
Earth Syst. Sci. Data, 12, 961–1001, https://doi.org/10.5194/essd-12-961-2020, https://doi.org/10.5194/essd-12-961-2020, 2020
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up GHG anthropogenic emissions from agriculture, forestry and other land use (AFOLU) in the EU28. The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models, aiming at reconciling GHG budgets with official country-level UNFCCC inventories. We provide comprehensive emission assessments in support to policy, facilitating real-time verification procedures.
Wagner de Oliveira Garcia, Thorben Amann, Jens Hartmann, Kristine Karstens, Alexander Popp, Lena R. Boysen, Pete Smith, and Daniel Goll
Biogeosciences, 17, 2107–2133, https://doi.org/10.5194/bg-17-2107-2020, https://doi.org/10.5194/bg-17-2107-2020, 2020
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Biomass-based terrestrial negative emission technologies (tNETS) have high potential to sequester CO2. Many CO2 uptake estimates do not include the effect of nutrient deficiencies in soils on biomass production. We show that nutrients can be partly resupplied by enhanced weathering (EW) rock powder application, increasing the effectiveness of tNETs. Depending on the deployed amounts of rock powder, EW could also improve soil hydrology, adding a new dimension to the coupling of tNETs with EW.
Scot M. Miller, Arvind K. Saibaba, Michael E. Trudeau, Marikate E. Mountain, and Arlyn E. Andrews
Geosci. Model Dev., 13, 1771–1785, https://doi.org/10.5194/gmd-13-1771-2020, https://doi.org/10.5194/gmd-13-1771-2020, 2020
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New observations of greenhouse gases from satellites and aircraft provide an unprecedented window into global carbon sources and sinks. However, these new datasets also present enormous computational challenges due to the sheer number of observations. In this article, we discuss the challenges of estimating greenhouse gas source and sinks using very large atmospheric datasets and evaluate several strategies for overcoming these challenges.
Tzu-Shun Lin, Yang Song, Atul K. Jain, Peter Lawrence, and Haroon S. Kheshgi
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-68, https://doi.org/10.5194/bg-2020-68, 2020
Preprint withdrawn
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ISAM model was used to estimate soybean and maize crop yields over 1901–2100 driven by changes in environmental factors and management factors. Over the 20th century, each of these factors contributes to the increase in global crop yield with increasing nitrogen fertilizer application the strongest of these drivers for maize and increasing [CO2] the strongest for soybean. Over the 21st century, changing climate drives yield lower, while rising [CO2] drives yield higher for both crops.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, https://doi.org/10.5194/hess-24-1485-2020, 2020
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Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Binghao Jia, Xin Luo, Ximing Cai, Atul Jain, Deborah N. Huntzinger, Zhenghui Xie, Ning Zeng, Jiafu Mao, Xiaoying Shi, Akihiko Ito, Yaxing Wei, Hanqin Tian, Benjamin Poulter, Dan Hayes, and Kevin Schaefer
Earth Syst. Dynam., 11, 235–249, https://doi.org/10.5194/esd-11-235-2020, https://doi.org/10.5194/esd-11-235-2020, 2020
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We quantitatively examined the relative contributions of climate change, land
use and land cover change, and elevated CO2 to interannual variations and seasonal cycle amplitude of gross primary productivity (GPP) in China based on multi-model ensemble simulations. The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
Lin Yu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 13, 783–803, https://doi.org/10.5194/gmd-13-783-2020, https://doi.org/10.5194/gmd-13-783-2020, 2020
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In this paper, we have developed a new soil organic carbon model that describes the formation and turnover of soil organic matter in a more mechanistic manner. With this model, we are able to better represent how microorganisms and nutrient processes influence the below-ground carbon storage and better explain some observed features of soil organic matter. We hope this model can increase our confidence in predictions of future climate change, particularly on how soil can mitigate the process.
Xu Yue, Hong Liao, Huijun Wang, Tianyi Zhang, Nadine Unger, Stephen Sitch, Zhaozhong Feng, and Jia Yang
Atmos. Chem. Phys., 20, 2353–2366, https://doi.org/10.5194/acp-20-2353-2020, https://doi.org/10.5194/acp-20-2353-2020, 2020
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We explore ecosystem responses in China to 1.5 °C global warming under stabilized versus transient pathways. Remarkably, GPP shows 30 % higher enhancement in the stabilized than the transient pathway because of the lower ozone (smaller damages to photosynthesis) and fewer aerosols (higher light availability) in the former pathway. Our analyses suggest that an associated reduction of CO2 and pollution emissions brings more benefits to ecosystems in China via 1.5 °C global warming.
Andrew J. Wiltshire, Maria Carolina Duran Rojas, John M. Edwards, Nicola Gedney, Anna B. Harper, Andrew J. Hartley, Margaret A. Hendry, Eddy Robertson, and Kerry Smout-Day
Geosci. Model Dev., 13, 483–505, https://doi.org/10.5194/gmd-13-483-2020, https://doi.org/10.5194/gmd-13-483-2020, 2020
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We present the Global Land (GL) configuration of the Joint UK Land Environment Simulator (JULES). JULES-GL7 can be used to simulate the exchange of heat, water and momentum over land and is therefore applicable for helping understand past and future changes, and forms the land component of the HadGEM3-GC3.1 climate model. The configuration is freely available subject to licence restrictions.
Julian Helfenstein, Chiara Pistocchi, Astrid Oberson, Federica Tamburini, Daniel S. Goll, and Emmanuel Frossard
Biogeosciences, 17, 441–454, https://doi.org/10.5194/bg-17-441-2020, https://doi.org/10.5194/bg-17-441-2020, 2020
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In this article we provide estimates of mean residence times of phosphorus in inorganic soil phosphorus pools. These values improve our understanding of the dynamics of phosphorus cycling and can be used to improve global land surface models.
Julia E. M. S. Nabel, Kim Naudts, and Julia Pongratz
Geosci. Model Dev., 13, 185–200, https://doi.org/10.5194/gmd-13-185-2020, https://doi.org/10.5194/gmd-13-185-2020, 2020
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Models need to account for forest age structures when investigating land use influences on land–atmosphere feedbacks. We present a consolidated scheme to introduce forest age classes, combining age-dependent simulations of important processes with the possibility to trace forest age, and describe its implementation in JSBACH4, the land surface model of the ICON Earth system model. We evaluate simulations with and without age classes demonstrating the benefit of forest age classes in JSBACH4.
Yufei Zou, Yuhang Wang, Yun Qian, Hanqin Tian, Jia Yang, and Ernesto Alvarado
Atmos. Chem. Phys., 20, 995–1020, https://doi.org/10.5194/acp-20-995-2020, https://doi.org/10.5194/acp-20-995-2020, 2020
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Fire is a natural phenomenon that has a long history of interactions with the environment and human activity. The complex interactions were less represented in previous fire and climate models. Here we use a new global fire model with improved modeling capability to study how fire responds and contributes to climate change. The modeling results show increased global fire activity in the future driven by climate change, which in turn modulates local and remote climate and ecosystems.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 20, 323–331, https://doi.org/10.5194/acp-20-323-2020, https://doi.org/10.5194/acp-20-323-2020, 2020
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere. The satellite measures radiation, and these measurements are then converted to an estimate of atmospheric CO2. This conversion or retrieval algorithm has improved markedly since the satellite launch. We find that these improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Cheng Chen, Oleg Dubovik, Daven K. Henze, Mian Chin, Tatyana Lapyonok, Gregory L. Schuster, Fabrice Ducos, David Fuertes, Pavel Litvinov, Lei Li, Anton Lopatin, Qiaoyun Hu, and Benjamin Torres
Atmos. Chem. Phys., 19, 14585–14606, https://doi.org/10.5194/acp-19-14585-2019, https://doi.org/10.5194/acp-19-14585-2019, 2019
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Global BC, OC and DD aerosol emissions are inverted from POLDER/PARASOL observations for the year 2010 based on the GEOS-Chem inverse modeling framework. The retrieved emissions are 18.4 Tg yr−1 BC, 109.9 Tg yr−1 OC and 731.6 Tg yr−1 DD, which indicate an increase of 166.7 % for BC and 184.0 % for OC, while a decrease of 42.4 % for DD with respect to GEOS-Chem a priori emission inventories is seen. Global annul mean AOD and AAOD resulting from retrieved emissions are 0.119 and 0.0071 at 550 nm.
Nicolas Vuichard, Palmira Messina, Sebastiaan Luyssaert, Bertrand Guenet, Sönke Zaehle, Josefine Ghattas, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 12, 4751–4779, https://doi.org/10.5194/gmd-12-4751-2019, https://doi.org/10.5194/gmd-12-4751-2019, 2019
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In this research, we present a new version of the global terrestrial ecosystem model ORCHIDEE in which carbon and nitrogen cycles are coupled. We evaluate its skills at simulating primary production at 78 sites and at a global scale. Based on a set of additional simulations in which carbon and nitrogen cycles are coupled and uncoupled, we show that the functional responses of the model with carbon–nitrogen interactions better agree with our current understanding of photosynthesis.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
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To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Sajeev Philip, Matthew S. Johnson, Christopher Potter, Vanessa Genovesse, David F. Baker, Katherine D. Haynes, Daven K. Henze, Junjie Liu, and Benjamin Poulter
Atmos. Chem. Phys., 19, 13267–13287, https://doi.org/10.5194/acp-19-13267-2019, https://doi.org/10.5194/acp-19-13267-2019, 2019
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This research was conducted to quantify the impact of different prior global biosphere models on the estimate of terrestrial CO2 fluxes when assimilating Orbiting Carbon Observatory-2 (OCO-2) satellite observations. To determine the prior model impact, we apply observing system simulation experiments (OSSEs). Even with the substantial spatiotemporal coverage of OCO-2 data, residual differences in posterior CO2 flux estimates remain due to the choice of prior flux mean and uncertainties.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
Publication in AMT not foreseen
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This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Joe R. Melton, Diana L. Verseghy, Reinel Sospedra-Alfonso, and Stephan Gruber
Geosci. Model Dev., 12, 4443–4467, https://doi.org/10.5194/gmd-12-4443-2019, https://doi.org/10.5194/gmd-12-4443-2019, 2019
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Soils in cold regions store large amounts of carbon that could be released to the atmosphere if the soils thaw. To best simulate these soils, we explored different configurations and parameterizations of the CLASS-CTEM model and compared to observations. The revised model with a deeper soil column, new soil depth dataset, and inclusion of moss simulated greatly improved annual thaw depths and ground temperatures. We estimate subgrid-scale features limit further improvements against observations.
Hubertus Fischer, Jochen Schmitt, Michael Bock, Barbara Seth, Fortunat Joos, Renato Spahni, Sebastian Lienert, Gianna Battaglia, Benjamin D. Stocker, Adrian Schilt, and Edward J. Brook
Biogeosciences, 16, 3997–4021, https://doi.org/10.5194/bg-16-3997-2019, https://doi.org/10.5194/bg-16-3997-2019, 2019
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N2O concentrations were subject to strong variations accompanying glacial–interglacial but also rapid climate changes over the last 21 kyr. The sources of these N2O changes can be identified by measuring the isotopic composition of N2O in ice cores and using the distinct isotopic composition of terrestrial and marine N2O. We show that both marine and terrestrial sources increased from the last glacial to the Holocene but that only terrestrial emissions responded quickly to rapid climate changes.
Fang Li, Maria Val Martin, Meinrat O. Andreae, Almut Arneth, Stijn Hantson, Johannes W. Kaiser, Gitta Lasslop, Chao Yue, Dominique Bachelet, Matthew Forrest, Erik Kluzek, Xiaohong Liu, Stephane Mangeon, Joe R. Melton, Daniel S. Ward, Anton Darmenov, Thomas Hickler, Charles Ichoku, Brian I. Magi, Stephen Sitch, Guido R. van der Werf, Christine Wiedinmyer, and Sam S. Rabin
Atmos. Chem. Phys., 19, 12545–12567, https://doi.org/10.5194/acp-19-12545-2019, https://doi.org/10.5194/acp-19-12545-2019, 2019
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Fire emissions are critical for atmospheric composition, climate, carbon cycle, and air quality. We provide the first global multi-model fire emission reconstructions for 1700–2012, including carbon and 33 species of trace gases and aerosols, based on the nine state-of-the-art global fire models that participated in FireMIP. We also provide information on the recent status and limitations of the model-based reconstructions and identify the main uncertainty sources in their long-term changes.
Lina Teckentrup, Sandy P. Harrison, Stijn Hantson, Angelika Heil, Joe R. Melton, Matthew Forrest, Fang Li, Chao Yue, Almut Arneth, Thomas Hickler, Stephen Sitch, and Gitta Lasslop
Biogeosciences, 16, 3883–3910, https://doi.org/10.5194/bg-16-3883-2019, https://doi.org/10.5194/bg-16-3883-2019, 2019
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This study compares simulated burned area of seven global vegetation models provided by the Fire Model Intercomparison Project (FireMIP) since 1900. We investigate the influence of five forcing factors: atmospheric CO2, population density, land–use change, lightning and climate.
We find that the anthropogenic factors lead to the largest spread between models. Trends due to climate are mostly not significant but climate strongly influences the inter-annual variability of burned area.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, https://doi.org/10.5194/gmd-12-4075-2019, 2019
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We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.
Bruno Ringeval, Marko Kvakić, Laurent Augusto, Philippe Ciais, Daniel Goll, Nathaniel D. Mueller, Christoph Müller, Thomas Nesme, Nicolas Vuichard, Xuhui Wang, and Sylvain Pellerin
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-298, https://doi.org/10.5194/bg-2019-298, 2019
Preprint withdrawn
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Crossed fertilization additions lead to the definition of nutrient interaction categories. However, the implications of such categories in terms of nutrient interaction modeling are not clear. We developed a theoretical analysis of nitrogen and phosphorus fertilization experiments, then applied it to current estimates of nutrient limitation in cropland. We found that a true co-limitation could affect up to 42 % of the global maize area when using a given formalism of nutrient interaction.
Olli Peltola, Timo Vesala, Yao Gao, Olle Räty, Pavel Alekseychik, Mika Aurela, Bogdan Chojnicki, Ankur R. Desai, Albertus J. Dolman, Eugenie S. Euskirchen, Thomas Friborg, Mathias Göckede, Manuel Helbig, Elyn Humphreys, Robert B. Jackson, Georg Jocher, Fortunat Joos, Janina Klatt, Sara H. Knox, Natalia Kowalska, Lars Kutzbach, Sebastian Lienert, Annalea Lohila, Ivan Mammarella, Daniel F. Nadeau, Mats B. Nilsson, Walter C. Oechel, Matthias Peichl, Thomas Pypker, William Quinton, Janne Rinne, Torsten Sachs, Mateusz Samson, Hans Peter Schmid, Oliver Sonnentag, Christian Wille, Donatella Zona, and Tuula Aalto
Earth Syst. Sci. Data, 11, 1263–1289, https://doi.org/10.5194/essd-11-1263-2019, https://doi.org/10.5194/essd-11-1263-2019, 2019
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Here we develop a monthly gridded dataset of northern (> 45 N) wetland methane (CH4) emissions. The data product is derived using a random forest machine-learning technique and eddy covariance CH4 fluxes from 25 wetland sites. Annual CH4 emissions from these wetlands calculated from the derived data product are comparable to prior studies focusing on these areas. This product is an independent estimate of northern wetland CH4 emissions and hence could be used, e.g. for process model evaluation.
Karel Castro-Morales, Gregor Schürmann, Christoph Köstler, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Biogeosciences, 16, 3009–3032, https://doi.org/10.5194/bg-16-3009-2019, https://doi.org/10.5194/bg-16-3009-2019, 2019
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To obtain nearly 30 years of global terrestrial carbon fluxes, we simultaneously incorporated in a land surface model three different time periods of two observational data sets: absorbed photosynthetic active radiation and atmospheric CO2 concentrations. One decade of data is enough to improve the modeled long-term trends and seasonal amplitudes of the assimilated variables, particularly in boreal regions. This model has the potential to provide short-term predictions of land carbon fluxes.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Susan J. Cheng, Peter G. Hess, William R. Wieder, R. Quinn Thomas, Knute J. Nadelhoffer, Julius Vira, Danica L. Lombardozzi, Per Gundersen, Ivan J. Fernandez, Patrick Schleppi, Marie-Cécile Gruselle, Filip Moldan, and Christine L. Goodale
Biogeosciences, 16, 2771–2793, https://doi.org/10.5194/bg-16-2771-2019, https://doi.org/10.5194/bg-16-2771-2019, 2019
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Nitrogen deposition and fertilizer can change how much carbon is stored in plants and soils. Understanding how much added nitrogen is recovered in plants or soils is critical to estimating the size of the future land carbon sink. We compared how nitrogen additions are recovered in modeled soil and plant stocks against data from long-term nitrogen addition experiments. We found that the model simulates recovery of added nitrogen into soils through a different process than found in the field.
Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
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Earth system models for producing climate projections under given forcings include additional processes and feedbacks that traditional physical climate models do not consider. We present an overview of climate feedbacks for key Earth system components and discuss the evaluation of these feedbacks. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research.
Alexandra G. Konings, A. Anthony Bloom, Junjie Liu, Nicholas C. Parazoo, David S. Schimel, and Kevin W. Bowman
Biogeosciences, 16, 2269–2284, https://doi.org/10.5194/bg-16-2269-2019, https://doi.org/10.5194/bg-16-2269-2019, 2019
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We estimate heterotrophic respiration (Rh) – the respiration from microbes in the soil – using satellite estimates of the net carbon flux and other quantities. Rh is an important carbon flux but is rarely studied by itself. Our method is the first to estimate how Rh varies in both space and time. The resulting new estimate of Rh is compared to the best currently available alternative, which is based on interpolating field measurements globally. The two estimates disagree and are both uncertain.
Mingkai Jiang, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Medlyn
Geosci. Model Dev., 12, 2069–2089, https://doi.org/10.5194/gmd-12-2069-2019, https://doi.org/10.5194/gmd-12-2069-2019, 2019
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Here we used a simple analytical framework developed by Comins and McMurtrie (1993) to investigate how different model assumptions affected plant responses to elevated CO2. This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.
Zainab Q. Hakim, Scott Archer-Nicholls, Gufran Beig, Gerd A. Folberth, Kengo Sudo, Nathan Luke Abraham, Sachin Ghude, Daven K. Henze, and Alexander T. Archibald
Atmos. Chem. Phys., 19, 6437–6458, https://doi.org/10.5194/acp-19-6437-2019, https://doi.org/10.5194/acp-19-6437-2019, 2019
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Surface ozone is an important air pollutant and recent work has calculated that large numbers of people die prematurely because of exposure to high levels of surface ozone in India. However, these calculations require model simulations of ozone as key inputs.
Here we perform the most thorough evaluation of global model surface ozone over India to date. These analyses of model simulations and observations highlight some successes and shortcomings and the need for further process-based studies.
Leonardo Calle, Benjamin Poulter, and Prabir K. Patra
Atmos. Meas. Tech., 12, 2611–2629, https://doi.org/10.5194/amt-12-2611-2019, https://doi.org/10.5194/amt-12-2611-2019, 2019
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Satellite observations of atmospheric carbon dioxide offer extraordinary insights into terrestrial ecosystem activity on Earth. The algorithm we present provides researchers with a great deal more information from these satellite data than has been available in the past. We hope the application of this algorithm and analyses tools provides insight into atmospheric dynamics of carbon dioxide and helps inform the development of global ecosystem models in the future.
Minqiang Zhou, Bavo Langerock, Kelley C. Wells, Dylan B. Millet, Corinne Vigouroux, Mahesh Kumar Sha, Christian Hermans, Jean-Marc Metzger, Rigel Kivi, Pauli Heikkinen, Dan Smale, David F. Pollard, Nicholas Jones, Nicholas M. Deutscher, Thomas Blumenstock, Matthias Schneider, Mathias Palm, Justus Notholt, James W. Hannigan, and Martine De Mazière
Atmos. Meas. Tech., 12, 1393–1408, https://doi.org/10.5194/amt-12-1393-2019, https://doi.org/10.5194/amt-12-1393-2019, 2019
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N2O is an important atmospheric gas which is observed by two ground-based FTIR networks (TCCON and NDACC). The difference between NDACC and TCCON XN2O measurements is discussed. It is found that the bias between the two networks is within their combined uncertainties. However, TCCON measurements are affected by a priori profiles. In addition, the TCCON and NDACC N2O measurements are compared with the GEOS-Chem model simulations.
Sarah Shannon, Robin Smith, Andy Wiltshire, Tony Payne, Matthias Huss, Richard Betts, John Caesar, Aris Koutroulis, Darren Jones, and Stephan Harrison
The Cryosphere, 13, 325–350, https://doi.org/10.5194/tc-13-325-2019, https://doi.org/10.5194/tc-13-325-2019, 2019
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We present global glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding 2 °C global average warming. The ice loss contribution to sea level rise for all glaciers excluding those on the peripheral of the Antarctic ice sheet is 215.2 ± 21.3 mm. Such large ice losses will have consequences for sea level rise and for water supply in glacier-fed river systems.
Rongting Xu, Hanqin Tian, Shufen Pan, Shree R. S. Dangal, Jian Chen, Jinfeng Chang, Yonglong Lu, Ute Maria Skiba, Francesco N. Tubiello, and Bowen Zhang
Earth Syst. Sci. Data, 11, 175–187, https://doi.org/10.5194/essd-11-175-2019, https://doi.org/10.5194/essd-11-175-2019, 2019
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We provide three gridded datasets of synthetic nitrogen (N) fertilizer and manure N inputs in global pastures and rangelands at a resolution of 0.5° × 0.5° for the period 1860–2016 (i.e., annual manure N deposition (by grazing animals) rate, synthetic N fertilizer use rate and manure N application rate). These three datasets could fill data gaps of N inputs in global and regional grasslands and serve as input drivers for earth system models.
Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman, and Kenneth J. Davis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-342, https://doi.org/10.5194/gmd-2018-342, 2019
Revised manuscript not accepted
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This paper describes a mass-conserving framework for computing time-varying lateral boundary conditions from global model carbon dioxide concentrations for introduction into the WRF-Chem regional model. The goal is to create a laboratory environment in which carbon dioxide transport uncertainties may be explored separately from inversion-derived flux uncertainties. The software is currently available on GitHub at https://github.com/psu-inversion/WRF_Boundary_Coupling.
Florent F. Malavelle, Jim M. Haywood, Lina M. Mercado, Gerd A. Folberth, Nicolas Bellouin, Stephen Sitch, and Paulo Artaxo
Atmos. Chem. Phys., 19, 1301–1326, https://doi.org/10.5194/acp-19-1301-2019, https://doi.org/10.5194/acp-19-1301-2019, 2019
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Diffuse light can increase the efficiency of vegetation photosynthesis. Diffuse light results from scattering by either clouds or aerosols in the atmosphere. During the dry season biomass burning (BB) on the edges of the Amazon rainforest contributes significantly to the aerosol burden over the entire region. We show that despite a modest effect of change in light conditions, the overall impact of BB aerosols on the vegetation is still important when indirect climate feedbacks are considered.
Rasoul Yousefpour, Julia E. M. S. Nabel, and Julia Pongratz
Biogeosciences, 16, 241–254, https://doi.org/10.5194/bg-16-241-2019, https://doi.org/10.5194/bg-16-241-2019, 2019
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Global forest resources are accounted for to establish their potential to sink carbon in woody biomass. Climate prediction models realize the effects of future global forest utilization rates, defined by population demand and its evolution over time. However, forest management approaches consider the supply side to realize a sustainable forest carbon stock and adapt the harvest rates to novel climate conditions. This study simulates such an adaptive sustained
yield approach.
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
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Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Chantelle Burton, Richard Betts, Manoel Cardoso, Ted R. Feldpausch, Anna Harper, Chris D. Jones, Douglas I. Kelley, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 12, 179–193, https://doi.org/10.5194/gmd-12-179-2019, https://doi.org/10.5194/gmd-12-179-2019, 2019
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Fire and land-use change are important disturbances within the Earth system, and their inclusion in models is critical to enable the correct simulation of vegetation cover. Here we describe developments to the land surface model JULES to represent explicit land-use change and fire and to assess the effects of each process on present day vegetation compared to observations. Using historical land-use data and the fire model INFERNO, overall model results are improved by the developments.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Vladislav Bastrikov, Natasha MacBean, Cédric Bacour, Diego Santaren, Sylvain Kuppel, and Philippe Peylin
Geosci. Model Dev., 11, 4739–4754, https://doi.org/10.5194/gmd-11-4739-2018, https://doi.org/10.5194/gmd-11-4739-2018, 2018
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In this study, we compare different methods for optimising parameters of the ORCHIDEE land surface model (LSM) using in situ observations. We use two minimisation methods - local gradient-based and global random search - applied either at each individual site or a group of sites characterised by one plant functional type. We demonstrate the advantages and challenges of different techniques and provide some advice on using it for the LSM parameters optimisation.
Haicheng Zhang, Daniel S. Goll, Stefano Manzoni, Philippe Ciais, Bertrand Guenet, and Yuanyuan Huang
Geosci. Model Dev., 11, 4779–4796, https://doi.org/10.5194/gmd-11-4779-2018, https://doi.org/10.5194/gmd-11-4779-2018, 2018
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Carbon use efficiency (CUE) of decomposers depends strongly on the organic matter quality (C : N ratio) and soil nutrient availability rather than a fixed value. A soil biogeochemical model with flexible CUE can better capture the differences in respiration rate of litter with contrasting C : N ratios and under different levels of mineral N availability than the model with fixed CUE, and well represent the effect of varying litter quality (N content) on SOM formation across temporal scales.
Martina Franz, Rocio Alonso, Almut Arneth, Patrick Büker, Susana Elvira, Giacomo Gerosa, Lisa Emberson, Zhaozhong Feng, Didier Le Thiec, Riccardo Marzuoli, Elina Oksanen, Johan Uddling, Matthew Wilkinson, and Sönke Zaehle
Biogeosciences, 15, 6941–6957, https://doi.org/10.5194/bg-15-6941-2018, https://doi.org/10.5194/bg-15-6941-2018, 2018
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Four published ozone damage functions previously used in terrestrial biosphere models were evaluated regarding their ability to simulate observed biomass dose–response relationships using the O-CN model. Neither damage function was able to reproduce the observed ozone-induced biomass reductions. Calibrating a plant-functional-type-specific relationship between accumulated ozone uptake and leaf-level photosynthesis did lead to a good agreement between observed and modelled ozone damage.
Ali Asaadi, Vivek K. Arora, Joe R. Melton, and Paul Bartlett
Biogeosciences, 15, 6885–6907, https://doi.org/10.5194/bg-15-6885-2018, https://doi.org/10.5194/bg-15-6885-2018, 2018
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Non-structural carbohydrates (NSCs), which play a central role in a plant's life processes and its response to environmental conditions, are typically not included in terrestrial biogeochemistry models used in Earth system models (ESMs). In this study, we include NSC pools in the framework of the land component of the Canadian ESM and show how they help address the long-standing problem of delayed leaf phenology.
Jacob K. Hedelius, Junjie Liu, Tomohiro Oda, Shamil Maksyutov, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Jianming Liang, Kevin R. Gurney, Debra Wunch, and Paul O. Wennberg
Atmos. Chem. Phys., 18, 16271–16291, https://doi.org/10.5194/acp-18-16271-2018, https://doi.org/10.5194/acp-18-16271-2018, 2018
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Human activities can cause concentrated emissions of greenhouse gases and other pollutants from cities. There is ongoing effort to convert new satellite observations of pollutants into fluxes for many cities. Here we present a method for determining the flux of three species (CO2, CH4, and CO) from the greater LA area using satellite (CO2 only) and ground-based (all three species) observations. We run tests to estimate uncertainty and find the direct net CO2 flux is 104 ± 26 Tg CO2 yr−1.
HyeJin Kim, Isabel M. D. Rosa, Rob Alkemade, Paul Leadley, George Hurtt, Alexander Popp, Detlef P. van Vuuren, Peter Anthoni, Almut Arneth, Daniele Baisero, Emma Caton, Rebecca Chaplin-Kramer, Louise Chini, Adriana De Palma, Fulvio Di Fulvio, Moreno Di Marco, Felipe Espinoza, Simon Ferrier, Shinichiro Fujimori, Ricardo E. Gonzalez, Maya Gueguen, Carlos Guerra, Mike Harfoot, Thomas D. Harwood, Tomoko Hasegawa, Vanessa Haverd, Petr Havlík, Stefanie Hellweg, Samantha L. L. Hill, Akiko Hirata, Andrew J. Hoskins, Jan H. Janse, Walter Jetz, Justin A. Johnson, Andreas Krause, David Leclère, Ines S. Martins, Tetsuya Matsui, Cory Merow, Michael Obersteiner, Haruka Ohashi, Benjamin Poulter, Andy Purvis, Benjamin Quesada, Carlo Rondinini, Aafke M. Schipper, Richard Sharp, Kiyoshi Takahashi, Wilfried Thuiller, Nicolas Titeux, Piero Visconti, Christopher Ware, Florian Wolf, and Henrique M. Pereira
Geosci. Model Dev., 11, 4537–4562, https://doi.org/10.5194/gmd-11-4537-2018, https://doi.org/10.5194/gmd-11-4537-2018, 2018
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This paper lays out the protocol for the Biodiversity and Ecosystem Services Scenario-based Intercomparison of Models (BES-SIM) that projects the global impacts of land use and climate change on biodiversity and ecosystem services over the coming decades, compared to the 20th century. BES-SIM uses harmonized scenarios and input data and a set of common output metrics at multiple scales, and identifies model uncertainties and research gaps.
Xinyi Dong, Joshua S. Fu, Qingzhao Zhu, Jian Sun, Jiani Tan, Terry Keating, Takashi Sekiya, Kengo Sudo, Louisa Emmons, Simone Tilmes, Jan Eiof Jonson, Michael Schulz, Huisheng Bian, Mian Chin, Yanko Davila, Daven Henze, Toshihiko Takemura, Anna Maria Katarina Benedictow, and Kan Huang
Atmos. Chem. Phys., 18, 15581–15600, https://doi.org/10.5194/acp-18-15581-2018, https://doi.org/10.5194/acp-18-15581-2018, 2018
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We have applied the HTAP phase II multi-model data to investigate the long-range transport impacts on surface concentration and column density of PM from Europe and Russia, Belarus, and Ukraine to eastern Asia, with a special focus on the long-range transport contribution during haze episodes in China. We found that long-range transport plays a more important role in elevating the background concentration of surface PM during the haze days.
Hansen Cao, Tzung-May Fu, Lin Zhang, Daven K. Henze, Christopher Chan Miller, Christophe Lerot, Gonzalo González Abad, Isabelle De Smedt, Qiang Zhang, Michel van Roozendael, François Hendrick, Kelly Chance, Jie Li, Junyu Zheng, and Yuanhong Zhao
Atmos. Chem. Phys., 18, 15017–15046, https://doi.org/10.5194/acp-18-15017-2018, https://doi.org/10.5194/acp-18-15017-2018, 2018
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Our top-down estimates for annual total Chinese NMVOC emissions was 30.7 to 49.5 Tg y−1, including 16.4 to 23.6 Tg y−1 from anthropogenic sources, 12.2 to 22.8 Tg y−1 from biogenic sources, and 2.08 to 3.13 Tg y−1 from biomass burning. Our four inversions consistently showed that the emissions of Chinese anthropogenic NMVOC precursors of glyoxal were larger than the a priori estimates. The glyoxal and formaldehyde constraints helped distinguish the NMVOC species from different sources.
Jan Eiof Jonson, Michael Schulz, Louisa Emmons, Johannes Flemming, Daven Henze, Kengo Sudo, Marianne Tronstad Lund, Meiyun Lin, Anna Benedictow, Brigitte Koffi, Frank Dentener, Terry Keating, Rigel Kivi, and Yanko Davila
Atmos. Chem. Phys., 18, 13655–13672, https://doi.org/10.5194/acp-18-13655-2018, https://doi.org/10.5194/acp-18-13655-2018, 2018
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Focusing on Europe, this HTAP 2 study computes ozone in several global models when reducing anthropogenic emissions by 20 % in different world regions. The differences in model results are explored
by use of a novel stepwise approach combining a tracer, CO and ozone. For ozone the contributions from the rest of the world are larger than from Europe, with the largest contributions from North America and eastern Asia. Contributions do, however, depend on the choice of ozone metric.
Yilong Wang, Philippe Ciais, Daniel Goll, Yuanyuan Huang, Yiqi Luo, Ying-Ping Wang, A. Anthony Bloom, Grégoire Broquet, Jens Hartmann, Shushi Peng, Josep Penuelas, Shilong Piao, Jordi Sardans, Benjamin D. Stocker, Rong Wang, Sönke Zaehle, and Sophie Zechmeister-Boltenstern
Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, https://doi.org/10.5194/gmd-11-3903-2018, 2018
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We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.
Johannes Meyerholt and Sönke Zaehle
Biogeosciences, 15, 5677–5698, https://doi.org/10.5194/bg-15-5677-2018, https://doi.org/10.5194/bg-15-5677-2018, 2018
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Terrestrial biosphere models employ various representations of ecosystem nitrogen loss, some based on soil N availability, some based on net N mineralization. We show in local and global simulations that this variety leads to pronounced uncertainty in the predicted magnitude and sign of ecosystem N loss change under elevated CO2. Suprisingly, this uncertainty barely affects predicted carbon storage responses to elevated CO2, illustrating the need for new benchmarks especially in the boreal zone.
Eunjee Lee, Fan-Wei Zeng, Randal D. Koster, Brad Weir, Lesley E. Ott, and Benjamin Poulter
Biogeosciences, 15, 5635–5652, https://doi.org/10.5194/bg-15-5635-2018, https://doi.org/10.5194/bg-15-5635-2018, 2018
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Land carbon fluxes are controlled in part by the responses of terrestrial ecosystems to atmospheric conditions near the Earth's surface. This study offers a comprehensive evaluation of the consequences of multiple facets of spatiotemporal variability in atmospheric CO2 for carbon cycle dynamics. Globally, consideration of the diurnal CO2 variability reduces the gross primary production and net land carbon uptake. The relative contributions of other variability vary regionally and seasonally.
Chris Huntingford, Rebecca J. Oliver, Lina M. Mercado, and Stephen Sitch
Biogeosciences, 15, 5415–5422, https://doi.org/10.5194/bg-15-5415-2018, https://doi.org/10.5194/bg-15-5415-2018, 2018
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Raised ozone levels impact plant stomatal opening and thus photosynthesis. Most models describe this as a suppression of stomata opening. Field evidence suggests more complexity, as ozone damage may make stomatal response
sluggish. In some circumstances, this causes stomata to be more open – a concern during drought conditions – by increasing transpiration. To guide interpretation and modelling of field measurements, we present an equation for sluggish effects, via a single tau parameter.
Cheng Chen, Oleg Dubovik, Daven K. Henze, Tatyana Lapyonak, Mian Chin, Fabrice Ducos, Pavel Litvinov, Xin Huang, and Lei Li
Atmos. Chem. Phys., 18, 12551–12580, https://doi.org/10.5194/acp-18-12551-2018, https://doi.org/10.5194/acp-18-12551-2018, 2018
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This paper introduces a method to use satellite-observed spectral AOD and AAOD to derive three types of aerosol emission sources simultaneously based on inverse modelling at a high spatial and temporal resolution. This study shows it is possible to estimate aerosol emissions and improve the atmospheric aerosol simulation using detailed aerosol optical and microphysical information from satellite observations.
Vivek K. Arora, Joe R. Melton, and David Plummer
Biogeosciences, 15, 4683–4709, https://doi.org/10.5194/bg-15-4683-2018, https://doi.org/10.5194/bg-15-4683-2018, 2018
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Earth system models (ESMs) project future changes in climate in response to changes in anthropogenic emissions of greenhouse gases (GHGs). However, before this can be achieved the natural fluxes of a given GHG must also be modelled. This paper evaluates the natural methane fluxes simulated by the CLASS-CTEM model (which is the land component of the Canadian ESM) against observations to show that the simulated methane emissions from wetlands and fires, and soil uptake of methane are realistic.
Vanessa Haverd, Benjamin Smith, Lars Nieradzik, Peter R. Briggs, William Woodgate, Cathy M. Trudinger, Josep G. Canadell, and Matthias Cuntz
Geosci. Model Dev., 11, 2995–3026, https://doi.org/10.5194/gmd-11-2995-2018, https://doi.org/10.5194/gmd-11-2995-2018, 2018
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CABLE is a terrestrial biosphere model that can be applied stand-alone and provides for land surface–atmosphere exchange within a climate model. We extend CABLE for regional and global carbon–climate simulations, accounting for land use and land cover change mediated by tree demography. A novel algorithm to simulate the coordination of rate-limiting photosynthetic processes is also implemented. Simulations satisfy multiple observational constraints on the global land carbon cycle.
Ciao-Kai Liang, J. Jason West, Raquel A. Silva, Huisheng Bian, Mian Chin, Yanko Davila, Frank J. Dentener, Louisa Emmons, Johannes Flemming, Gerd Folberth, Daven Henze, Ulas Im, Jan Eiof Jonson, Terry J. Keating, Tom Kucsera, Allen Lenzen, Meiyun Lin, Marianne Tronstad Lund, Xiaohua Pan, Rokjin J. Park, R. Bradley Pierce, Takashi Sekiya, Kengo Sudo, and Toshihiko Takemura
Atmos. Chem. Phys., 18, 10497–10520, https://doi.org/10.5194/acp-18-10497-2018, https://doi.org/10.5194/acp-18-10497-2018, 2018
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Emissions from one continent affect air quality and health elsewhere. Here we quantify the effects of intercontinental PM2.5 and ozone transport on human health using a new multi-model ensemble, evaluating the health effects of emissions from six world regions and three emission source sectors. Emissions from one region have significant health impacts outside of that source region; similarly, foreign emissions contribute significantly to air-pollution-related deaths in several world regions.
Fuxing Wang, Jan Polcher, Philippe Peylin, and Vladislav Bastrikov
Hydrol. Earth Syst. Sci., 22, 3863–3882, https://doi.org/10.5194/hess-22-3863-2018, https://doi.org/10.5194/hess-22-3863-2018, 2018
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This work improves river discharge estimation by taking advantages of observation and model simulations. The new estimation takes into account both gauged and un-gauged rivers, and it compensates model systematic errors and missing processes (e.g., human water usage). This improved estimation is important not only for water resources management and ecosystem health over continent but also for ocean dynamics and salinity.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
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Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Emilie Joetzjer, Fabienne Maignan, Jérôme Chave, Daniel Goll, Ben Poulter, Jonathan Barichivich, Isabelle Maréchaux, Sebastiaan Luyssaert, Matthieu Guimberteau, Kim Naudts, Damien Bonal, and Philippe Ciais
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-308, https://doi.org/10.5194/bg-2018-308, 2018
Revised manuscript not accepted
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This study explores the relative contributions of tree demographic, canopy structure and hydraulic processes on the Amazonian carbon and water cycles using large-scale process-based model. Our results imply that explicit coupling of the water and carbon cycles improves the representation of biogeochemical cycles and their spatial variability. Representing the variation in the ecological functioning of Amazonia should be the next step to improve the performance and predictive ability of models.
Rebecca J. Oliver, Lina M. Mercado, Stephen Sitch, David Simpson, Belinda E. Medlyn, Yan-Shih Lin, and Gerd A. Folberth
Biogeosciences, 15, 4245–4269, https://doi.org/10.5194/bg-15-4245-2018, https://doi.org/10.5194/bg-15-4245-2018, 2018
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Potential gains in terrestrial carbon sequestration over Europe from elevated CO2 can be partially offset by concurrent rises in tropospheric O3. The land surface model JULES was run in a factorial suite of experiments showing that by 2050 simulated GPP was reduced by 4 to 9 % due to plant O3 damage. Large regional variations exist with larger impacts identified for temperate compared to boreal regions. Plant O3 damage was greatest over the twentieth century and declined into the future.
Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, and Carolina Duran-Rojas
Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, https://doi.org/10.5194/gmd-11-2857-2018, 2018
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Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES is a DGVM that represents the land surface in the UK Earth System Model. We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets. JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements.
Gregory Duveiller, Giovanni Forzieri, Eddy Robertson, Wei Li, Goran Georgievski, Peter Lawrence, Andy Wiltshire, Philippe Ciais, Julia Pongratz, Stephen Sitch, Almut Arneth, and Alessandro Cescatti
Earth Syst. Sci. Data, 10, 1265–1279, https://doi.org/10.5194/essd-10-1265-2018, https://doi.org/10.5194/essd-10-1265-2018, 2018
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Changing the vegetation cover of the Earth's surface can alter the local energy balance, which can result in a local warming or cooling depending on the specific vegetation transition, its timing and location, as well as on the background climate. While models can theoretically simulate these effects, their skill is not well documented across space and time. Here we provide a dedicated framework to evaluate such models against measurements derived from satellite observations.
Werner von Bloh, Sibyll Schaphoff, Christoph Müller, Susanne Rolinski, Katharina Waha, and Sönke Zaehle
Geosci. Model Dev., 11, 2789–2812, https://doi.org/10.5194/gmd-11-2789-2018, https://doi.org/10.5194/gmd-11-2789-2018, 2018
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The dynamics of the terrestrial carbon cycle are of central importance for Earth system science. Nutrient limitations, especially from nitrogen, are important constraints on vegetation growth and the terrestrial carbon cycle. We extended the well-established global vegetation, hydrology, and crop model LPJmL with a nitrogen cycle. We find significant improvement in global patterns of crop productivity. Regional differences in crop productivity can now be largely reproduced by the model.
Steven T. Turnock, Oliver Wild, Frank J. Dentener, Yanko Davila, Louisa K. Emmons, Johannes Flemming, Gerd A. Folberth, Daven K. Henze, Jan E. Jonson, Terry J. Keating, Sudo Kengo, Meiyun Lin, Marianne Lund, Simone Tilmes, and Fiona M. O'Connor
Atmos. Chem. Phys., 18, 8953–8978, https://doi.org/10.5194/acp-18-8953-2018, https://doi.org/10.5194/acp-18-8953-2018, 2018
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A simple parameterisation was developed in this study to provide a rapid assessment of the impacts and uncertainties associated with future emission control strategies by predicting changes to surface ozone air quality and near-term climate forcing of ozone. Future emissions scenarios based on currently implemented legislation are shown to worsen surface ozone air quality and enhance near-term climate warming, with changes in methane becoming increasingly important in the future.
Stefano Galmarini, Ioannis Kioutsioukis, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Roberto Bellasio, Anna M. K. Benedictow, Roberto Bianconi, Johannes Bieser, Joergen Brandt, Jesper H. Christensen, Augustin Colette, Gabriele Curci, Yanko Davila, Xinyi Dong, Johannes Flemming, Xavier Francis, Andrea Fraser, Joshua Fu, Daven K. Henze, Christian Hogrefe, Ulas Im, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Jan Eiof Jonson, Nutthida Kitwiroon, Astrid Manders, Rohit Mathur, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marie Prank, Martin Schultz, Rajeet S. Sokhi, Kengo Sudo, Paolo Tuccella, Toshihiko Takemura, Takashi Sekiya, and Alper Unal
Atmos. Chem. Phys., 18, 8727–8744, https://doi.org/10.5194/acp-18-8727-2018, https://doi.org/10.5194/acp-18-8727-2018, 2018
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An ensemble of model results relating to ozone concentrations in Europe in 2010 has been produced and studied. The novelty consists in the fact that the ensemble is made of results of models working at two different scales (regional and global), therefore contributing in detail two different parts of the atmospheric spectrum. The ensemble defined as a hybrid has been studied in detail and shown to bring additional value to the assessment of air quality.
Wei Li, Chao Yue, Philippe Ciais, Jinfeng Chang, Daniel Goll, Dan Zhu, Shushi Peng, and Albert Jornet-Puig
Geosci. Model Dev., 11, 2249–2272, https://doi.org/10.5194/gmd-11-2249-2018, https://doi.org/10.5194/gmd-11-2249-2018, 2018
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We implemented four major lignocellulosic bioenergy crops in ORCHIDEE. We added new PFTs, did new parameterizations of photosynthesis, carbon allocation, and phenology based on a compilation of field measurements, and added a specific harvest module. The resulting ORCHIDEE-MICT-BIOENERGY model is evaluated at 296 locations where field measurements of harvested biomass are available, and the new model can generally reproduce the global bioenergy crop yield observations.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Ye Huang, Bertrand Guenet, Philippe Ciais, Ivan A. Janssens, Jennifer L. Soong, Yilong Wang, Daniel Goll, Evgenia Blagodatskaya, and Yuanyuan Huang
Geosci. Model Dev., 11, 2111–2138, https://doi.org/10.5194/gmd-11-2111-2018, https://doi.org/10.5194/gmd-11-2111-2018, 2018
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ORCHIMIC is a modeling effort trying to improve the representation of SOC dynamics in Earth system models (ESM). It has a structure that can be easily incorporated into CENTURY-based ESMs. In ORCHIMIC, key microbial dynamics (i.e., enzyme production, enzymatic decomposition and microbial dormancy) are included. The ORCHIMIC model can also reproduce the observed temporal dynamics of respiration and priming effects; thus it is an improved tool for climate projections and SOC response predictions.
Sourish Basu, David F. Baker, Frédéric Chevallier, Prabir K. Patra, Junjie Liu, and John B. Miller
Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, https://doi.org/10.5194/acp-18-7189-2018, 2018
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CO2 measurements from the global surface network and CO2 estimates from satellites such as the Orbiting Carbon Observatory 2 (OCO-2) are currently used to quantify the surface sources and sinks of CO2, using what we know about atmospheric transport of gases. In this work, we quantify the uncertainties in those surface source/sink estimates that stem from errors in our atmospheric transport models, using an observing system simulation experiment (OSSE).
Scot M. Miller, Anna M. Michalak, Vineet Yadav, and Jovan M. Tadić
Atmos. Chem. Phys., 18, 6785–6799, https://doi.org/10.5194/acp-18-6785-2018, https://doi.org/10.5194/acp-18-6785-2018, 2018
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes CO2 in the atmosphere globally. We evaluate the extent to which current OCO-2 observations can inform scientific understanding of the biospheric carbon balance. We find that current observations are best-equipped to constrain the biospheric carbon balance across continental or hemispheric regions and provide limited information on smaller regions.
Jiani Tan, Joshua S. Fu, Frank Dentener, Jian Sun, Louisa Emmons, Simone Tilmes, Kengo Sudo, Johannes Flemming, Jan Eiof Jonson, Sylvie Gravel, Huisheng Bian, Yanko Davila, Daven K. Henze, Marianne T. Lund, Tom Kucsera, Toshihiko Takemura, and Terry Keating
Atmos. Chem. Phys., 18, 6847–6866, https://doi.org/10.5194/acp-18-6847-2018, https://doi.org/10.5194/acp-18-6847-2018, 2018
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We study the distributions of sulfur and nitrogen deposition, which are associated with current environmental issues such as formation of acid rain and ecosystem eutrophication and result in widespread problems such as loss of environmental diversity, harming the crop yield and even food insecurity. According to our study, both the amount and distribution of sulfate and nitrogen deposition have changed significantly in the last decade, particularly in East Asia, South Asia and Southeast Asia.
Sebastian Lienert and Fortunat Joos
Biogeosciences, 15, 2909–2930, https://doi.org/10.5194/bg-15-2909-2018, https://doi.org/10.5194/bg-15-2909-2018, 2018
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Deforestation, shifting cultivation and wood harvesting cause large carbon emissions, altering climate. We apply a dynamic global vegetation model in a probabilistic framework. Diverse observations are assimilated to establish an optimally performing model and a large ensemble of model versions. Land-use carbon emissions are reported for individual countries, regions and the world. We find that parameter-related uncertainties are on the same order of magnitude as process-related effects.
Karel Castro-Morales, Thomas Kleinen, Sonja Kaiser, Sönke Zaehle, Fanny Kittler, Min Jung Kwon, Christian Beer, and Mathias Göckede
Biogeosciences, 15, 2691–2722, https://doi.org/10.5194/bg-15-2691-2018, https://doi.org/10.5194/bg-15-2691-2018, 2018
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We present year-round methane emissions from wetlands in Northeast Siberia that were simulated with a land surface model. Ground-based flux measurements from the same area were used for evaluation of the model results, finding a best agreement with the observations in the summertime emissions that take place in this region predominantly through plants. During winter, methane emissions through the snow contribute 4 % of the total annual methane budget, but these are still underestimated.
Christian Rödenbeck, Sönke Zaehle, Ralph Keeling, and Martin Heimann
Biogeosciences, 15, 2481–2498, https://doi.org/10.5194/bg-15-2481-2018, https://doi.org/10.5194/bg-15-2481-2018, 2018
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In this paper we investigate how the CO2 exchange between the land vegetation and the atmosphere varies from year to year. We quantify the relation between variations in the CO2 exchange and variations in air temperature. For this quantification, we use long-term measurements of CO2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature. The results help us to understand the mechanisms of CO2 exchange.
Stephan Harrison, Jeffrey S. Kargel, Christian Huggel, John Reynolds, Dan H. Shugar, Richard A. Betts, Adam Emmer, Neil Glasser, Umesh K. Haritashya, Jan Klimeš, Liam Reinhardt, Yvonne Schaub, Andy Wiltshire, Dhananjay Regmi, and Vít Vilímek
The Cryosphere, 12, 1195–1209, https://doi.org/10.5194/tc-12-1195-2018, https://doi.org/10.5194/tc-12-1195-2018, 2018
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Most mountain glaciers have receded throughout the last century in response to global climate change. This recession produces a range of natural hazards including glacial lake outburst floods (GLOFs). We have produced the first global inventory of GLOFs associated with the failure of moraine dams and show, counterintuitively, that these have reduced in frequency over recent decades. In this paper we explore the reasons for this pattern.
Kira Sadighi, Evan Coffey, Andrea Polidori, Brandon Feenstra, Qin Lv, Daven K. Henze, and Michael Hannigan
Atmos. Meas. Tech., 11, 1777–1792, https://doi.org/10.5194/amt-11-1777-2018, https://doi.org/10.5194/amt-11-1777-2018, 2018
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Ground-level ozone has negative human health impacts. In the summer of 2015, 13 low-cost sensor monitors were deployed to several neighborhoods around Riverside, California. There were significant spatial differences between monitors. This is important because it means that ozone in certain places may be higher than what EPA monitors report for an area, which is pertinent for residents of those communities. This research helps inform the limitations and advantages of low-cost sensor networks.
Marta Camino-Serrano, Bertrand Guenet, Sebastiaan Luyssaert, Philippe Ciais, Vladislav Bastrikov, Bruno De Vos, Bert Gielen, Gerd Gleixner, Albert Jornet-Puig, Klaus Kaiser, Dolly Kothawala, Ronny Lauerwald, Josep Peñuelas, Marion Schrumpf, Sara Vicca, Nicolas Vuichard, David Walmsley, and Ivan A. Janssens
Geosci. Model Dev., 11, 937–957, https://doi.org/10.5194/gmd-11-937-2018, https://doi.org/10.5194/gmd-11-937-2018, 2018
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Global models generally oversimplify the representation of soil organic carbon (SOC), and thus its response to global warming remains uncertain. We present the new soil module ORCHIDEE-SOM, within the global model ORCHIDEE, that refines the representation of SOC dynamics and includes the dissolved organic carbon (DOC) processes. The model is able to reproduce SOC stocks and DOC concentrations in four different ecosystems, opening an opportunity for improved predictions of SOC in global models.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
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The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Bakr Badawy, Saroja Polavarapu, Dylan B. A. Jones, Feng Deng, Michael Neish, Joe R. Melton, Ray Nassar, and Vivek K. Arora
Geosci. Model Dev., 11, 631–663, https://doi.org/10.5194/gmd-11-631-2018, https://doi.org/10.5194/gmd-11-631-2018, 2018
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We assess the impact of using the meteorological fields from GEM-MACH-GHG to drive CLASS-CTEM. This coupling is considered an important step toward understanding how meteorological uncertainties affect both CO2 flux estimates and modeled atmospheric transport. Ultimately, such an approach will provide more direct feedback to the CLASS-CTEM developers and thus help to improve the performance of CLASS-CTEM by identifying the model limitations based on atmospheric constraints.
Emily Ane Dionizio, Marcos Heil Costa, Andrea D. de Almeida Castanho, Gabrielle Ferreira Pires, Beatriz Schwantes Marimon, Ben Hur Marimon-Junior, Eddie Lenza, Fernando Martins Pimenta, Xiaojuan Yang, and Atul K. Jain
Biogeosciences, 15, 919–936, https://doi.org/10.5194/bg-15-919-2018, https://doi.org/10.5194/bg-15-919-2018, 2018
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Using a dynamic vegetation model, we demonstrate that fire occurrence is the main determinant factor of vegetation changes along the Amazon–Cerrado border, followed by nutrient limitation and interannual climate variability. Although we simulated more than 80 % of the variability of biomass in the transition zone, in many places the simulated biomass clearly does not match observations. The accurate representation of the transition is important for understanding the savannization of the Amazon.
Mahdi Nakhavali, Pierre Friedlingstein, Ronny Lauerwald, Jing Tang, Sarah Chadburn, Marta Camino-Serrano, Bertrand Guenet, Anna Harper, David Walmsley, Matthias Peichl, and Bert Gielen
Geosci. Model Dev., 11, 593–609, https://doi.org/10.5194/gmd-11-593-2018, https://doi.org/10.5194/gmd-11-593-2018, 2018
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In order to provide a better understanding of the Earth's carbon cycle, we need a model that represents the whole continuum from atmosphere to land and into the ocean. In this study we include in JULES a representation of dissolved organic carbon (DOC) processes. Our results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating the terrestrial and aquatic ecosystem.
Kelley C. Wells, Dylan B. Millet, Nicolas Bousserez, Daven K. Henze, Timothy J. Griffis, Sreelekha Chaliyakunnel, Edward J. Dlugokencky, Eri Saikawa, Gao Xiang, Ronald G. Prinn, Simon O'Doherty, Dickon Young, Ray F. Weiss, Geoff S. Dutton, James W. Elkins, Paul B. Krummel, Ray Langenfelds, and L. Paul Steele
Atmos. Chem. Phys., 18, 735–756, https://doi.org/10.5194/acp-18-735-2018, https://doi.org/10.5194/acp-18-735-2018, 2018
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This paper uses three different frameworks to derive nitrous oxide (N2O) emissions based on global surface observations. One of these frameworks employs a new approach that allows for fast computation and explores a larger solution space than other methods. Our results point to a few conclusions about the global N2O budget, including a larger contribution from tropical sources, an overestimate of natural soil emissions, and an underestimate of agricultural sources particularly in springtime.
Matthieu Guimberteau, Dan Zhu, Fabienne Maignan, Ye Huang, Chao Yue, Sarah Dantec-Nédélec, Catherine Ottlé, Albert Jornet-Puig, Ana Bastos, Pierre Laurent, Daniel Goll, Simon Bowring, Jinfeng Chang, Bertrand Guenet, Marwa Tifafi, Shushi Peng, Gerhard Krinner, Agnès Ducharne, Fuxing Wang, Tao Wang, Xuhui Wang, Yilong Wang, Zun Yin, Ronny Lauerwald, Emilie Joetzjer, Chunjing Qiu, Hyungjun Kim, and Philippe Ciais
Geosci. Model Dev., 11, 121–163, https://doi.org/10.5194/gmd-11-121-2018, https://doi.org/10.5194/gmd-11-121-2018, 2018
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Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module.
Lin Zhang, Youfan Chen, Yuanhong Zhao, Daven K. Henze, Liye Zhu, Yu Song, Fabien Paulot, Xuejun Liu, Yuepeng Pan, Yi Lin, and Binxiang Huang
Atmos. Chem. Phys., 18, 339–355, https://doi.org/10.5194/acp-18-339-2018, https://doi.org/10.5194/acp-18-339-2018, 2018
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Substantial differences exist in current estimates of agricultural ammonia emissions in China, hindering understanding of their environmental consequences. This study applies both bottom-up and top-down methods to better quantify agricultural ammonia sources in China using observations from satellite and surface networks interpreted by a chemical transport model. Our estimate of annual Chinese anthropogenic ammonia emission is 11.7 tg (teragram) for 2008 with a strong seasonality peak in summer.
Fei Lun, Junguo Liu, Philippe Ciais, Thomas Nesme, Jinfeng Chang, Rong Wang, Daniel Goll, Jordi Sardans, Josep Peñuelas, and Michael Obersteiner
Earth Syst. Sci. Data, 10, 1–18, https://doi.org/10.5194/essd-10-1-2018, https://doi.org/10.5194/essd-10-1-2018, 2018
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We quantified in detail the P budgets in agricultural systems and PUE on global, regional, and national scales from 2002 to 2010. Globally, half of the total P inputs into agricultural systems accumulated in agricultural soils, with the rest lost to bodies of water. There are great differences in P budgets and PUE in agricultural systems on global, regional, and national scales. International trade played a significant role in P redistribution and P in fertilizer and food among countries.
Arsène Druel, Philippe Peylin, Gerhard Krinner, Philippe Ciais, Nicolas Viovy, Anna Peregon, Vladislav Bastrikov, Natalya Kosykh, and Nina Mironycheva-Tokareva
Geosci. Model Dev., 10, 4693–4722, https://doi.org/10.5194/gmd-10-4693-2017, https://doi.org/10.5194/gmd-10-4693-2017, 2017
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To improve the simulation of vegetation–climate feedbacks at high latitudes, three new circumpolar vegetation types were added in the ORCHIDEE land surface model: bryophytes (mosses) and lichens, Arctic shrubs, and Arctic grasses. This article is an introduction to the modification of vegetation distribution and physical behaviour, implying for example lower productivity, roughness, and higher winter albedo or freshwater discharge in the Arctic Ocean.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
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This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
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We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Rudra K. Shrestha, Vivek K. Arora, Joe R. Melton, and Laxmi Sushama
Biogeosciences, 14, 4733–4753, https://doi.org/10.5194/bg-14-4733-2017, https://doi.org/10.5194/bg-14-4733-2017, 2017
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Computer models of vegetation provide a tool to assess how future changes in climate may the affect geographical distribution of vegetation. However, such models must first be assessed for their ability to reproduce the present-day geographical distribution of vegetation. Here, we assess the ability of one such dynamic vegetation model. We find that while the model is broadly successful in reproducing the geographical distribution of trees and grasses in North America some limitations remain.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gabriel Abramowitz, Martin G. De Kauwe, Bradley Evans, Vanessa Haverd, Longhui Li, Caitlin Moore, Youngryel Ryu, Simon Scheiter, Stanislaus J. Schymanski, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, https://doi.org/10.5194/bg-14-4711-2017, 2017
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This paper attempts to review some of the current challenges faced by the modelling community in simulating the behaviour of savanna ecosystems. We provide a particular focus on three dynamic processes (phenology, root-water access, and fire) that are characteristic of savannas, which we believe are not adequately represented in current-generation terrestrial biosphere models. We highlight reasons for these misrepresentations, possible solutions and a future direction for research in this area.
Daniel S. Goll, Nicolas Vuichard, Fabienne Maignan, Albert Jornet-Puig, Jordi Sardans, Aurelie Violette, Shushi Peng, Yan Sun, Marko Kvakic, Matthieu Guimberteau, Bertrand Guenet, Soenke Zaehle, Josep Penuelas, Ivan Janssens, and Philippe Ciais
Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, https://doi.org/10.5194/gmd-10-3745-2017, 2017
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We describe a representation of the terrestrial phosphorus cycle for the ORCHIDEE land surface model. The model is able to reproduce the observed shift from nitrogen to phosphorus limited net primary productivity along a soil formation chronosequence in Hawaii, as well as the contrasting responses of net primary productivity to nutrient addition. However, the simulated nutrient use efficiencies are lower, as observed primarily due to biases in the nutrient content and turnover of woody biomass.
Nils Hase, Scot M. Miller, Peter Maaß, Justus Notholt, Mathias Palm, and Thorsten Warneke
Geosci. Model Dev., 10, 3695–3713, https://doi.org/10.5194/gmd-10-3695-2017, https://doi.org/10.5194/gmd-10-3695-2017, 2017
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Inverse modeling uses atmospheric measurements to estimate emissions of greenhouse gases, which are key to understand the climate system. However, the measurement information alone is typically insufficient to provide reasonable emission estimates. Additional information is required. This article applies modern mathematical inversion techniques to formulate such additional knowledge. It is a prime example of how such tools can improve the quality of estimates compared to commonly used methods.
Jun-Wei Xu, Randall V. Martin, Andrew Morrow, Sangeeta Sharma, Lin Huang, W. Richard Leaitch, Julia Burkart, Hannes Schulz, Marco Zanatta, Megan D. Willis, Daven K. Henze, Colin J. Lee, Andreas B. Herber, and Jonathan P. D. Abbatt
Atmos. Chem. Phys., 17, 11971–11989, https://doi.org/10.5194/acp-17-11971-2017, https://doi.org/10.5194/acp-17-11971-2017, 2017
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We interpret a series of recent airborne and ground-based measurements with the GEOS-Chem model and its adjoint to attribute the sources of Arctic BC. Anthropogenic emissions in eastern and southern Asia make the largest contribution to Arctic BC. Gas flaring emissions from oilfields in western Siberia and from the Tarim oilfield in western China could have striking impacts on Arctic BC loadings.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
Bowen Zhang, Hanqin Tian, Chaoqun Lu, Shree R. S. Dangal, Jia Yang, and Shufen Pan
Earth Syst. Sci. Data, 9, 667–678, https://doi.org/10.5194/essd-9-667-2017, https://doi.org/10.5194/essd-9-667-2017, 2017
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This work addressed how manure nitrogen (N) production and application to cropland have changed over time and space. The 5 arcmin gridded global dataset of manure nitrogen production generated from this study could be used as an input for global or regional land surface and ecosystem models to evaluate the impacts of manure nitrogen on key biogeochemical processes and water quality.
Ling Qi, Qinbin Li, Daven K. Henze, Hsien-Liang Tseng, and Cenlin He
Atmos. Chem. Phys., 17, 9697–9716, https://doi.org/10.5194/acp-17-9697-2017, https://doi.org/10.5194/acp-17-9697-2017, 2017
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We find that Asian anthropogenic sources are the largest contributors (~ 40 %) to surface BC in spring in the Arctic, inconsistent with previous studies which repeatedly identified sources of surface BC as anthropogenic emissions from Europe and Russia. It takes 12–17 days for Asian anthropogenic emissions to be transported to the Arctic surface. Additionally, a large fraction (40–65 %) of Asian contribution is in the form of chronic pollution on 1- to 2-month timescales.
Jakob Zscheischler, Miguel D. Mahecha, Valerio Avitabile, Leonardo Calle, Nuno Carvalhais, Philippe Ciais, Fabian Gans, Nicolas Gruber, Jens Hartmann, Martin Herold, Kazuhito Ichii, Martin Jung, Peter Landschützer, Goulven G. Laruelle, Ronny Lauerwald, Dario Papale, Philippe Peylin, Benjamin Poulter, Deepak Ray, Pierre Regnier, Christian Rödenbeck, Rosa M. Roman-Cuesta, Christopher Schwalm, Gianluca Tramontana, Alexandra Tyukavina, Riccardo Valentini, Guido van der Werf, Tristram O. West, Julie E. Wolf, and Markus Reichstein
Biogeosciences, 14, 3685–3703, https://doi.org/10.5194/bg-14-3685-2017, https://doi.org/10.5194/bg-14-3685-2017, 2017
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Here we synthesize a wide range of global spatiotemporal observational data on carbon exchanges between the Earth surface and the atmosphere. A key challenge was to consistently combining observational products of terrestrial and aquatic surfaces. Our primary goal is to identify today’s key uncertainties and observational shortcomings that would need to be addressed in future measurement campaigns or expansions of in situ observatories.
Guangsheng Chen, Shufen Pan, Daniel J. Hayes, and Hanqin Tian
Earth Syst. Sci. Data, 9, 545–556, https://doi.org/10.5194/essd-9-545-2017, https://doi.org/10.5194/essd-9-545-2017, 2017
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Through synthesizing multiple inventory data sources, this study developed methods to spatialize the time series plantation forest and tree species distribution data for the conterminous US during 1928–2012. These time series and gridded data set can be readily applied in regional Earth system modeling frameworks for assessing the impacts of plantation management practices on forest productivity, carbon and nitrogen stocks, and greenhouse gas and water fluxes on regional or national scales.
Rongting Xu, Hanqin Tian, Chaoqun Lu, Shufen Pan, Jian Chen, Jia Yang, and Bowen Zhang
Clim. Past, 13, 977–990, https://doi.org/10.5194/cp-13-977-2017, https://doi.org/10.5194/cp-13-977-2017, 2017
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As N2O emissions were present in preindustrial times, only the difference between current and preindustrial emissions represents net human-induced climate change. Large uncertainty exists in previous estimates of preindustrial N2O emissions from the land biosphere. Our estimate using process-based model was the first study that provided the preindustrial N2O emission at the biome, sector or country, and global level, which could be a useful reference for future climate mitigation.
Joe R. Melton, Reinel Sospedra-Alfonso, and Kelly E. McCusker
Geosci. Model Dev., 10, 2761–2783, https://doi.org/10.5194/gmd-10-2761-2017, https://doi.org/10.5194/gmd-10-2761-2017, 2017
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Climate models have large grid cells due to the computational cost of running these complex models. Within grid cells like these, the land surface can vary dramatically impacting the exchange of water, carbon, and energy between the atmosphere and land. We use a technique to determine natural clusters of high-resolution soil texture within large grid cells and use them as inputs to our model. We find relatively low sensitivity to soil texture changes except in very dry regions and peatlands.
Yuanqiao Wu, Ed Chan, Joe R. Melton, and Diana L. Verseghy
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-152, https://doi.org/10.5194/gmd-2017-152, 2017
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Peatlands are an important component of the carbon cycle that is expected to change under climate change, but accurate information on the global distribution of peatlands is presently unavailable. We use a machine-learning method to create a map of global peatland extent suitable for use in an Earth system model. For areas where data exists we find excellent agreement with observations and our method has greater skill than solely using soil datasets to estimate peatland coverage.
Jonathan J. Guerrette and Daven K. Henze
Atmos. Chem. Phys., 17, 7605–7633, https://doi.org/10.5194/acp-17-7605-2017, https://doi.org/10.5194/acp-17-7605-2017, 2017
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This work describes the implementation and application of a new advanced tool, WRFDA-Chem, for top-down constraints of regional atmospheric chemical emissions. Aircraft and surface observations of black carbon are traced to anthropogenic and biomass burning sources in California during ARCTAS-CARB. The information content of the observations is quantified through variance reduction and degrees of freedom of signal, which can be used to assess observing strategies and emission inventories.
Eleanor J. Burke, Altug Ekici, Ye Huang, Sarah E. Chadburn, Chris Huntingford, Philippe Ciais, Pierre Friedlingstein, Shushi Peng, and Gerhard Krinner
Biogeosciences, 14, 3051–3066, https://doi.org/10.5194/bg-14-3051-2017, https://doi.org/10.5194/bg-14-3051-2017, 2017
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There are large reserves of carbon within the permafrost which might be released to the atmosphere under global warming. Our models suggest this release may cause an additional global temperature increase of 0.005 to 0.2°C by the year 2100 and 0.01 to 0.34°C by the year 2300. Under climate mitigation scenarios this is between 1.5 and 9 % (by 2100) and between 6 and 16 % (by 2300) of the global mean temperature change. There is a large uncertainty associated with these results.
Richard J. Millar, Zebedee R. Nicholls, Pierre Friedlingstein, and Myles R. Allen
Atmos. Chem. Phys., 17, 7213–7228, https://doi.org/10.5194/acp-17-7213-2017, https://doi.org/10.5194/acp-17-7213-2017, 2017
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Simple representations of the global coupled climate–carbon-cycle system are required for climate policy analysis. Existing models have often failed to capture important physical dependencies of the climate response to carbon dioxide emissions. In this paper we propose a simple but novel modification to impulse-response climate–carbon-cycle models to capture these physical dependencies. This simple model creates an important tool for both climate policy and climate science analysis.
Zhe Jiang, Helen Worden, John R. Worden, Daven K. Henze, Dylan B. A. Jones, Avelino F. Arellano, Emily V. Fischer, Liye Zhu, Kazuyuki Miyazaki, K. Folkert Boersma, and Vivienne H. Payne
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-382, https://doi.org/10.5194/acp-2017-382, 2017
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We investigated the variation of US tropospheric NO2 in the past decade. We demonstrated significant divergence between the time variation in tropospheric NO2 columns from OMI retrievals and surface measurements. Our analysis suggests limited contributions from local effects such as fossil fuel emissions, lightning, or instrument artifacts, and indicates possible important contributions from long-range transport of Asian emissions that are modulated by ENSO.
Kathrin M. Keller, Sebastian Lienert, Anil Bozbiyik, Thomas F. Stocker, Olga V. Churakova (Sidorova), David C. Frank, Stefan Klesse, Charles D. Koven, Markus Leuenberger, William J. Riley, Matthias Saurer, Rolf Siegwolf, Rosemarie B. Weigt, and Fortunat Joos
Biogeosciences, 14, 2641–2673, https://doi.org/10.5194/bg-14-2641-2017, https://doi.org/10.5194/bg-14-2641-2017, 2017
Reinhard Prestele, Almut Arneth, Alberte Bondeau, Nathalie de Noblet-Ducoudré, Thomas A. M. Pugh, Stephen Sitch, Elke Stehfest, and Peter H. Verburg
Earth Syst. Dynam., 8, 369–386, https://doi.org/10.5194/esd-8-369-2017, https://doi.org/10.5194/esd-8-369-2017, 2017
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Land-use change is still overly simplistically implemented in global ecosystem and climate models. We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models. We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use–climate interactions and feedback.
Daniel S. Goll, Alexander J. Winkler, Thomas Raddatz, Ning Dong, Ian Colin Prentice, Philippe Ciais, and Victor Brovkin
Geosci. Model Dev., 10, 2009–2030, https://doi.org/10.5194/gmd-10-2009-2017, https://doi.org/10.5194/gmd-10-2009-2017, 2017
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The response of soil organic carbon decomposition to warming and the interactions between nitrogen and carbon cycling affect the feedbacks between the land carbon cycle and the climate. In the model JSBACH carbon–nitrogen interactions have only a small effect on the feedbacks, whereas modifications of soil organic carbon decomposition have a large effect. The carbon cycle in the improved model is more resilient to climatic changes than in previous version of the model.
Min Huang, Gregory R. Carmichael, R. Bradley Pierce, Duseong S. Jo, Rokjin J. Park, Johannes Flemming, Louisa K. Emmons, Kevin W. Bowman, Daven K. Henze, Yanko Davila, Kengo Sudo, Jan Eiof Jonson, Marianne Tronstad Lund, Greet Janssens-Maenhout, Frank J. Dentener, Terry J. Keating, Hilke Oetjen, and Vivienne H. Payne
Atmos. Chem. Phys., 17, 5721–5750, https://doi.org/10.5194/acp-17-5721-2017, https://doi.org/10.5194/acp-17-5721-2017, 2017
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In support of the HTAP phase 2 experiment, we conducted a number of regional-scale Sulfur Transport and dEposition Model base and sensitivity simulations over North America during May–June 2010. The STEM chemical boundary conditions were downscaled from three (GEOS-Chem, RAQMS, and ECMWF C-IFS) global chemical transport models' simulations. Analyses were performed on large spatial–temporal scales relative to HTAP1 and also on subcontinental and event scales including the use of satellite data.
Tea Thum, Sönke Zaehle, Philipp Köhler, Tuula Aalto, Mika Aurela, Luis Guanter, Pasi Kolari, Tuomas Laurila, Annalea Lohila, Federico Magnani, Christiaan Van Der Tol, and Tiina Markkanen
Biogeosciences, 14, 1969–1987, https://doi.org/10.5194/bg-14-1969-2017, https://doi.org/10.5194/bg-14-1969-2017, 2017
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Modelling seasonal cycle at the coniferous forests poses a challenge. We implemented a model for sun-induced chlorophyll fluorescence (SIF) to a land surface model JSBACH. It was used to study the seasonality of the carbon cycle in the Fenno-Scandinavian region. Comparison was made to direct CO2 flux measurements and satellite observations of SIF. SIF proved to be a better proxy for photosynthesis than the fraction of absorbed photosynthetically active radiation.
Zhe Jiang, John R. Worden, Helen Worden, Merritt Deeter, Dylan B. A. Jones, Avelino F. Arellano, and Daven K. Henze
Atmos. Chem. Phys., 17, 4565–4583, https://doi.org/10.5194/acp-17-4565-2017, https://doi.org/10.5194/acp-17-4565-2017, 2017
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We constrain the long-term variation in global CO emissions for 2001–2015. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, unchanged anthropogenic CO emissions from Europe since 2008, and likely a positive trend from India and southeast Asia.
Karina Williams, Jemma Gornall, Anna Harper, Andy Wiltshire, Debbie Hemming, Tristan Quaife, Tim Arkebauer, and David Scoby
Geosci. Model Dev., 10, 1291–1320, https://doi.org/10.5194/gmd-10-1291-2017, https://doi.org/10.5194/gmd-10-1291-2017, 2017
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This study looks in detail at how well the crop model within the Joint UK Land Environment Simulator (JULES), a community land-surface model, is able to simulate irrigated maize in Nebraska. We use the results to point to future priorities for model development and describe how our methodology can be adapted to set up model runs for other sites and crop varieties.
Scot M. Miller and Anna M. Michalak
Atmos. Chem. Phys., 17, 3963–3985, https://doi.org/10.5194/acp-17-3963-2017, https://doi.org/10.5194/acp-17-3963-2017, 2017
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We reviewed recent efforts to estimate state- and national-scale carbon dioxide and methane emissions from individual anthropogenic source sectors in the United States. State and federal greenhouse gas regulations almost always target reductions from specific source sectors, and reliable emission estimates are important to support and evaluate these policies. We also describe a number of forward-looking opportunities that would improve sector-specific estimates.
Sam S. Rabin, Joe R. Melton, Gitta Lasslop, Dominique Bachelet, Matthew Forrest, Stijn Hantson, Jed O. Kaplan, Fang Li, Stéphane Mangeon, Daniel S. Ward, Chao Yue, Vivek K. Arora, Thomas Hickler, Silvia Kloster, Wolfgang Knorr, Lars Nieradzik, Allan Spessa, Gerd A. Folberth, Tim Sheehan, Apostolos Voulgarakis, Douglas I. Kelley, I. Colin Prentice, Stephen Sitch, Sandy Harrison, and Almut Arneth
Geosci. Model Dev., 10, 1175–1197, https://doi.org/10.5194/gmd-10-1175-2017, https://doi.org/10.5194/gmd-10-1175-2017, 2017
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Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include. A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance. It also includes equations for all models.
Chaoqun Lu and Hanqin Tian
Earth Syst. Sci. Data, 9, 181–192, https://doi.org/10.5194/essd-9-181-2017, https://doi.org/10.5194/essd-9-181-2017, 2017
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This work has addressed how agricultural nitrogen and phosphorous fertilizer use has changed over time and space. The final product covers global agricultural land, spanning from 1961 to 2013 at a spatial resolution of 0.5° × 0.5° latitude by longitude. It can serve as an important input driver for regional and global assessment and Earth system modeling of agricultural productivity, crop yield, greenhouse gas balance, global nutrient budget, and ecosystem feedback to climate.
Mehliyar Sadiq, Amos P. K. Tai, Danica Lombardozzi, and Maria Val Martin
Atmos. Chem. Phys., 17, 3055–3066, https://doi.org/10.5194/acp-17-3055-2017, https://doi.org/10.5194/acp-17-3055-2017, 2017
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Surface ozone harms vegetation, which can influence not only climate but also ozone air quality itself. We implement a scheme for ozone damage on vegetation into an Earth system model, so that for the first time simulated vegetation and ozone can coevolve in a fully coupled simulation. With ozone–vegetation coupling, simulated ozone is found to be significantly higher by up to 6 ppbv. Reduced dry deposition and enhanced isoprene emission contribute to most of these increases.
Chantelle R. Lonsdale, Jennifer D. Hegarty, Karen E. Cady-Pereira, Matthew J. Alvarado, Daven K. Henze, Matthew D. Turner, Shannon L. Capps, John B. Nowak, J. Andy Neuman, Ann M. Middlebrook, Roya Bahreini, Jennifer G. Murphy, Milos Z. Markovic, Trevor C. VandenBoer, Lynn M. Russell, and Amy Jo Scarino
Atmos. Chem. Phys., 17, 2721–2739, https://doi.org/10.5194/acp-17-2721-2017, https://doi.org/10.5194/acp-17-2721-2017, 2017
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This study takes advantage of the high-resolution observations of NH3(g) made by the TES satellite instrument over Bakersfield during the CalNex campaign, along with campaign measurements, to compare CMAQ model results in the San Joaquin Valley, California. Additionally we evaluate the CMAQ bi-directional ammonia flux results using the CARB emissions inventory against these satellite and campaign measurements, not previously explored in combination.
Jovan M. Tadić, Xuemei Qiu, Scot Miller, and Anna M. Michalak
Geosci. Model Dev., 10, 709–720, https://doi.org/10.5194/gmd-10-709-2017, https://doi.org/10.5194/gmd-10-709-2017, 2017
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We developed a new method to create contiguous maps from sparse and/or noisy satellite observations. This approach could be used to produce retroactive or real-time estimates of environmental data observed by satellites which exhibit spatio-temporal autocorrelations. The method could be applied in a standalone mode or as part of a broader satellite data processing package. Maps produced in this way could then be incorporated into physical and biogeochemical models of the Earth system.
Danica L. Lombardozzi, Melanie J. B. Zeppel, Rosie A. Fisher, and Ahmed Tawfik
Geosci. Model Dev., 10, 321–331, https://doi.org/10.5194/gmd-10-321-2017, https://doi.org/10.5194/gmd-10-321-2017, 2017
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Earth's terrestrial surface influences climate by exchanging carbon and water with the atmosphere through stomatal pores. However, most land-surface models, used to predict global carbon and water fluxes, estimate that water lost through stomata is less than what observations show. In this study, we integrate plant water loss data from 204 species into a global land surface model, finding that global estimates of plant water loss increase, soil moisture decreases, and carbon gain also decreases.
Martina Franz, David Simpson, Almut Arneth, and Sönke Zaehle
Biogeosciences, 14, 45–71, https://doi.org/10.5194/bg-14-45-2017, https://doi.org/10.5194/bg-14-45-2017, 2017
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Ozone is a toxic air pollutant that can damage plant leaves and impact their carbon uptake from the atmosphere. We extend a terrestrial biosphere model to account for ozone damage of plants and investigate the impact on the terrestrial carbon cycle. Our approach accounts for ozone transport from the free troposphere to leaf level. We find that this substantially affects simulated ozone uptake into the plants. Simulations indicate that ozone damages plants less than expected from previous studies
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Cathy M. Trudinger, Vanessa Haverd, Peter R. Briggs, and Josep G. Canadell
Biogeosciences, 13, 6363–6383, https://doi.org/10.5194/bg-13-6363-2016, https://doi.org/10.5194/bg-13-6363-2016, 2016
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Semi-arid ecosystems in Australia are responsible for a significant part of the variability in global atmospheric carbon dioxide. Here we use Australian observations to estimate parameters in a land surface model of carbon and water cycles. We quantify the variability in Australian carbon fluxes between 1982 and 2013, including the large uptake in 2011 associated with exceptionally wet conditions following a prolonged drought. We estimate the effect of parameter uncertainty on these estimates.
Doug McNeall, Jonny Williams, Ben Booth, Richard Betts, Peter Challenor, Andy Wiltshire, and David Sexton
Earth Syst. Dynam., 7, 917–935, https://doi.org/10.5194/esd-7-917-2016, https://doi.org/10.5194/esd-7-917-2016, 2016
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We compare simulated with observed forests to constrain uncertain input parameters of the land surface component of a climate model.
We find that the model is unlikely to be able to simulate the Amazon and other major forests simultaneously at any one parameter set, suggesting a bias in the model's representation of the Amazon.
We find we cannot constrain parameters individually, but we can rule out large areas of joint parameter space.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Eva van Gorsel, Sebastian Wolf, James Cleverly, Peter Isaac, Vanessa Haverd, Cäcilia Ewenz, Stefan Arndt, Jason Beringer, Víctor Resco de Dios, Bradley J. Evans, Anne Griebel, Lindsay B. Hutley, Trevor Keenan, Natascha Kljun, Craig Macfarlane, Wayne S. Meyer, Ian McHugh, Elise Pendall, Suzanne M. Prober, and Richard Silberstein
Biogeosciences, 13, 5947–5964, https://doi.org/10.5194/bg-13-5947-2016, https://doi.org/10.5194/bg-13-5947-2016, 2016
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Temperature extremes are expected to become more prevalent in the future and understanding ecosystem response is crucial. We synthesised measurements and model results to investigate the effect of a summer heat wave on carbon and water exchange across three biogeographic regions in southern Australia. Forests proved relatively resilient to short-term heat extremes but the response of woodlands indicates that the carbon sinks of large areas of Australia may not be sustainable in a future climate.
Camilla Weum Stjern, Bjørn Hallvard Samset, Gunnar Myhre, Huisheng Bian, Mian Chin, Yanko Davila, Frank Dentener, Louisa Emmons, Johannes Flemming, Amund Søvde Haslerud, Daven Henze, Jan Eiof Jonson, Tom Kucsera, Marianne Tronstad Lund, Michael Schulz, Kengo Sudo, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 16, 13579–13599, https://doi.org/10.5194/acp-16-13579-2016, https://doi.org/10.5194/acp-16-13579-2016, 2016
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Air pollution can reach distant regions through intercontinental transport. Here we first present results from the Hemispheric Transport of Air Pollution Phase 2 exercise, where many models performed the same set of coordinated emission-reduction experiments. We find that mitigations have considerable extra-regional effects, and show that this is particularly true for black carbon emissions, as long-range transport elevates aerosols to higher levels where their radiative influence is stronger.
Jason Beringer, Lindsay B. Hutley, Ian McHugh, Stefan K. Arndt, David Campbell, Helen A. Cleugh, James Cleverly, Víctor Resco de Dios, Derek Eamus, Bradley Evans, Cacilia Ewenz, Peter Grace, Anne Griebel, Vanessa Haverd, Nina Hinko-Najera, Alfredo Huete, Peter Isaac, Kasturi Kanniah, Ray Leuning, Michael J. Liddell, Craig Macfarlane, Wayne Meyer, Caitlin Moore, Elise Pendall, Alison Phillips, Rebecca L. Phillips, Suzanne M. Prober, Natalia Restrepo-Coupe, Susanna Rutledge, Ivan Schroder, Richard Silberstein, Patricia Southall, Mei Sun Yee, Nigel J. Tapper, Eva van Gorsel, Camilla Vote, Jeff Walker, and Tim Wardlaw
Biogeosciences, 13, 5895–5916, https://doi.org/10.5194/bg-13-5895-2016, https://doi.org/10.5194/bg-13-5895-2016, 2016
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OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. We describe the evolution, design, and status as well as an overview of data processing. We suggest that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing Australian ecosystems.
Sylvia S. Nyawira, Julia E. M. S. Nabel, Axel Don, Victor Brovkin, and Julia Pongratz
Biogeosciences, 13, 5661–5675, https://doi.org/10.5194/bg-13-5661-2016, https://doi.org/10.5194/bg-13-5661-2016, 2016
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We introduce an approach applicable to dynamic global vegetation models for evaluating simulated soil carbon changes from land-use changes against meta-analyses. The approach makes use of the large spatial coverage of the observations, and accounts for different ages of the sampled land-use transitions. The evaluation offers an opportunity for identifying causes of model–data discrepancies. Applied to the model JSBACH, we find that introducing crop harvest substantially improves the results.
Zeli Tan, Qianlai Zhuang, Daven K. Henze, Christian Frankenberg, Ed Dlugokencky, Colm Sweeney, Alexander J. Turner, Motoki Sasakawa, and Toshinobu Machida
Atmos. Chem. Phys., 16, 12649–12666, https://doi.org/10.5194/acp-16-12649-2016, https://doi.org/10.5194/acp-16-12649-2016, 2016
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Methane emissions from the pan-Arctic could be important in understanding the global carbon cycle but are still poorly constrained to date. This study demonstrated that satellite retrievals can be used to reduce the uncertainty of the estimates of these emissions. We also provided additional evidence for the existence of large methane emissions from pan-Arctic lakes in the Siberian yedoma permafrost region. We found that biogeochemical models should be improved for better estimates.
Brian C. O'Neill, Claudia Tebaldi, Detlef P. van Vuuren, Veronika Eyring, Pierre Friedlingstein, George Hurtt, Reto Knutti, Elmar Kriegler, Jean-Francois Lamarque, Jason Lowe, Gerald A. Meehl, Richard Moss, Keywan Riahi, and Benjamin M. Sanderson
Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, https://doi.org/10.5194/gmd-9-3461-2016, 2016
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The Scenario Model Intercomparison Project (ScenarioMIP) will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. The design consists of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions. Climate model projections will facilitate integrated studies of climate change as well as address targeted scientific questions.
Fang Zhao, Ning Zeng, Ghassem Asrar, Pierre Friedlingstein, Akihiko Ito, Atul Jain, Eugenia Kalnay, Etsushi Kato, Charles D. Koven, Ben Poulter, Rashid Rafique, Stephen Sitch, Shijie Shu, Beni Stocker, Nicolas Viovy, Andy Wiltshire, and Sonke Zaehle
Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, https://doi.org/10.5194/bg-13-5121-2016, 2016
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The increasing seasonality of atmospheric CO2 is strongly linked with enhanced land vegetation activities in the last 5 decades, for which the importance of increasing CO2, climate and land use/cover change was evaluated in single model studies (Zeng et al., 2014; Forkel et al., 2016). Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.
Xiyan Xu, William J. Riley, Charles D. Koven, Dave P. Billesbach, Rachel Y.-W. Chang, Róisín Commane, Eugénie S. Euskirchen, Sean Hartery, Yoshinobu Harazono, Hiroki Iwata, Kyle C. McDonald, Charles E. Miller, Walter C. Oechel, Benjamin Poulter, Naama Raz-Yaseef, Colm Sweeney, Margaret Torn, Steven C. Wofsy, Zhen Zhang, and Donatella Zona
Biogeosciences, 13, 5043–5056, https://doi.org/10.5194/bg-13-5043-2016, https://doi.org/10.5194/bg-13-5043-2016, 2016
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Wetlands are the largest global natural methane source. Peat-rich bogs and fens lying between 50°N and 70°N contribute 10–30% to this source. The predictive capability of the seasonal methane cycle can directly affect the estimation of global methane budget. We present multiscale methane seasonal emission by observations and modeling and find that the uncertainties in predicting the seasonal methane emissions are from the wetland extent, cold-season CH4 production and CH4 transport processes.
Vanessa Haverd, Matthias Cuntz, Lars P. Nieradzik, and Ian N. Harman
Geosci. Model Dev., 9, 3111–3122, https://doi.org/10.5194/gmd-9-3111-2016, https://doi.org/10.5194/gmd-9-3111-2016, 2016
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CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. We improve CABLE’s simulation of evaporation using a new scheme for drought response and a physically accurate representation of coupled energy and water fluxes in the soil. Marked improvements in predictions of evaporation are demonstrated globally. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.
Gregor J. Schürmann, Thomas Kaminski, Christoph Köstler, Nuno Carvalhais, Michael Voßbeck, Jens Kattge, Ralf Giering, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, https://doi.org/10.5194/gmd-9-2999-2016, 2016
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We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
Yiying Chen, James Ryder, Vladislav Bastrikov, Matthew J. McGrath, Kim Naudts, Juliane Otto, Catherine Ottlé, Philippe Peylin, Jan Polcher, Aude Valade, Andrew Black, Jan A. Elbers, Eddy Moors, Thomas Foken, Eva van Gorsel, Vanessa Haverd, Bernard Heinesch, Frank Tiedemann, Alexander Knohl, Samuli Launiainen, Denis Loustau, Jérôme Ogée, Timo Vessala, and Sebastiaan Luyssaert
Geosci. Model Dev., 9, 2951–2972, https://doi.org/10.5194/gmd-9-2951-2016, https://doi.org/10.5194/gmd-9-2951-2016, 2016
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In this study, we compiled a set of within-canopy and above-canopy measurements of energy and water fluxes, and used these data to parametrize and validate the new multi-layer energy budget scheme for a range of forest types. An adequate parametrization approach has been presented for the global-scale land surface model (ORCHIDEE-CAN). Furthermore, model performance of the new multi-layer parametrization was compared against the existing single-layer scheme.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
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How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Stéphane Mangeon, Apostolos Voulgarakis, Richard Gilham, Anna Harper, Stephen Sitch, and Gerd Folberth
Geosci. Model Dev., 9, 2685–2700, https://doi.org/10.5194/gmd-9-2685-2016, https://doi.org/10.5194/gmd-9-2685-2016, 2016
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To understand the role of fires in the Earth system, global fire models are required. In this paper we describe the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO). It follows a reduced complexity approach using mainly temperature, humidity and precipitation. INFERNO was found to perform well on a global scale and to maintain regional patterns over the 1997–2011 period of study, despite regional biases particularly linked to fuel consumption.
Yuanqiao Wu, Diana L. Verseghy, and Joe R. Melton
Geosci. Model Dev., 9, 2639–2663, https://doi.org/10.5194/gmd-9-2639-2016, https://doi.org/10.5194/gmd-9-2639-2016, 2016
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About 20 % of the carbon stored in global soils occurs in peatlands. Warmer and drier conditions will both tend to stimulate the decomposition of peat and increase CO2 and methane emissions, thus potentially enhancing the warming trend. It is important that this feedback mechanism be captured in climate models. This work integrated peatlands into the Canadian Earth system model (CanESM) for global climate predictions and represent a valuable enhancement to the family of Earth system models.
Zuo Xue, Ruoying He, Katja Fennel, Wei-Jun Cai, Steven Lohrenz, Wei-Jen Huang, Hanqin Tian, Wei Ren, and Zhengchen Zang
Biogeosciences, 13, 4359–4377, https://doi.org/10.5194/bg-13-4359-2016, https://doi.org/10.5194/bg-13-4359-2016, 2016
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In this study we used a state-of-the-science coupled physical–biogeochemical model to simulate and examine temporal and spatial variability of sea surface CO2 concentration in the Gulf of Mexico. Our model revealed the Gulf was a net CO2 sink with a flux of 1.11 ± 0.84 × 1012 mol C yr−1. We also found that biological uptake was the primary driver making the Gulf an overall CO2 sink and that the carbon flux in the northern Gulf was very susceptible to changes in river inputs.
Joshua B. Fisher, Munish Sikka, Deborah N. Huntzinger, Christopher Schwalm, and Junjie Liu
Biogeosciences, 13, 4271–4277, https://doi.org/10.5194/bg-13-4271-2016, https://doi.org/10.5194/bg-13-4271-2016, 2016
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Atmospheric models of CO2 require estimates of land CO2 fluxes at relatively high temporal resolutions because of the high rate of atmospheric mixing and wind heterogeneity. However, land CO2 fluxes are often provided at monthly time steps. Here, we describe a new dataset created from 15 global land models and 4 combined products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), which we have converted from monthly to 3-hourly output.
Rosa Maria Roman-Cuesta, Mariana C. Rufino, Martin Herold, Klaus Butterbach-Bahl, Todd S. Rosenstock, Mario Herrero, Stephen Ogle, Changsheng Li, Benjamin Poulter, Louis Verchot, Christopher Martius, John Stuiver, and Sytze de Bruin
Biogeosciences, 13, 4253–4269, https://doi.org/10.5194/bg-13-4253-2016, https://doi.org/10.5194/bg-13-4253-2016, 2016
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This research provides spatial data on gross emissions from the land use sector for the tropical region for the period 2000–2005. This sector contributes up to 24 % of the global emissions, but there is little understanding of where the hotspots of emissions are, how uncertain they are, and what the human activities behind these emissions are. Data provided here should assist countries to identify priority areas for mitigation action and contrast the effectiveness of their current measures.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
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Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Xiaofeng Xu, Fengming Yuan, Paul J. Hanson, Stan D. Wullschleger, Peter E. Thornton, William J. Riley, Xia Song, David E. Graham, Changchun Song, and Hanqin Tian
Biogeosciences, 13, 3735–3755, https://doi.org/10.5194/bg-13-3735-2016, https://doi.org/10.5194/bg-13-3735-2016, 2016
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Accurately projecting future climate change requires a good methane modeling. However, how good the current models are and what are the key improvements needed remain unclear. This paper reviews the 40 published methane models to characterize the strengths and weakness of current methane models and further lay out the roadmap for future model improvements.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
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Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes. A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project – FireMIP.
Rhys Whitley, Jason Beringer, Lindsay B. Hutley, Gab Abramowitz, Martin G. De Kauwe, Remko Duursma, Bradley Evans, Vanessa Haverd, Longhui Li, Youngryel Ryu, Benjamin Smith, Ying-Ping Wang, Mathew Williams, and Qiang Yu
Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, https://doi.org/10.5194/bg-13-3245-2016, 2016
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In this study we assess how well terrestrial biosphere models perform at predicting water and carbon cycling for savanna ecosystems. We apply our models to five savanna sites in Northern Australia and highlight key causes for model failure. Our assessment of model performance uses a novel benchmarking system that scores a model’s predictive ability based on how well it is utilizing its driving information. On average, we found the models as a group display only moderate levels of performance.
Zhe Jiang, Kazuyuki Miyazaki, John R. Worden, Jane J. Liu, Dylan B. A. Jones, and Daven K. Henze
Atmos. Chem. Phys., 16, 6537–6546, https://doi.org/10.5194/acp-16-6537-2016, https://doi.org/10.5194/acp-16-6537-2016, 2016
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We quantify the impacts of anthropogenic and natural sources on free tropospheric ozone over the Middle East, using the adjoint of the GEOS-Chem model with updated NOx emissions estimates from an ensemble Kalman filter. We show that the global total contribution of lightning NOx on free tropospheric O3 over the Middle East is about 2 times larger than that from global anthropogenic sources. The summertime free tropospheric O3 enhancement is primarily due to Asian NOx emissions.
Nicolas Bousserez, Daven K. Henze, Brigitte Rooney, Andre Perkins, Kevin J. Wecht, Alexander J. Turner, Vijay Natraj, and John R. Worden
Atmos. Chem. Phys., 16, 6175–6190, https://doi.org/10.5194/acp-16-6175-2016, https://doi.org/10.5194/acp-16-6175-2016, 2016
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This work provides new insight into the observational constraints provided by current low-Earth orbit (LEO) and future potential geostationary (GEO) satellite missions on methane emissions in North America. Using efficient numerical tools, the information content (error reductions, spatial resolution of the constraints) of methane inversions using different instrument configurations (TIR, SWIR and multi-spectral) was estimated at model grid-scale resolution (0.5° × 0.7°).
Veronika Eyring, Mattia Righi, Axel Lauer, Martin Evaldsson, Sabrina Wenzel, Colin Jones, Alessandro Anav, Oliver Andrews, Irene Cionni, Edouard L. Davin, Clara Deser, Carsten Ehbrecht, Pierre Friedlingstein, Peter Gleckler, Klaus-Dirk Gottschaldt, Stefan Hagemann, Martin Juckes, Stephan Kindermann, John Krasting, Dominik Kunert, Richard Levine, Alexander Loew, Jarmo Mäkelä, Gill Martin, Erik Mason, Adam S. Phillips, Simon Read, Catherine Rio, Romain Roehrig, Daniel Senftleben, Andreas Sterl, Lambertus H. van Ulft, Jeremy Walton, Shiyu Wang, and Keith D. Williams
Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, https://doi.org/10.5194/gmd-9-1747-2016, 2016
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A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) in CMIP has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations.
Johannes Meyerholt, Sönke Zaehle, and Matthew J. Smith
Biogeosciences, 13, 1491–1518, https://doi.org/10.5194/bg-13-1491-2016, https://doi.org/10.5194/bg-13-1491-2016, 2016
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We investigated how today's state-of-the-art terrestrial biosphere models represent biological nitrogen fixation and what the consequences of varying representation are for model predictions under ambient conditions and under scenarios of elevated atmospheric carbon dioxide concentrations. We found that varying global nitrogen fixation rates are simulated under ambient conditions and that the responses of the simulated carbon and nitrogen cycles are significantly affected under perturbation.
Natalie Mahowald, Fiona Lo, Yun Zheng, Laura Harrison, Chris Funk, Danica Lombardozzi, and Christine Goodale
Earth Syst. Dynam., 7, 211–229, https://doi.org/10.5194/esd-7-211-2016, https://doi.org/10.5194/esd-7-211-2016, 2016
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This paper evaluates the model predictions of leaf area index in the current climate, compared against satellite observations. It also summarizes the predicted changes in leaf area index in the future, and identifies whether some of the uncertainty in future predictions can be decreased.
Zhen Zhang, Niklaus E. Zimmermann, Jed O. Kaplan, and Benjamin Poulter
Biogeosciences, 13, 1387–1408, https://doi.org/10.5194/bg-13-1387-2016, https://doi.org/10.5194/bg-13-1387-2016, 2016
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This study investigates improvements and uncertainties associated with estimating global inundated area and wetland CH4 emissions using TOPMODEL. Different topographic information and catchment aggregation schemes are evaluated against seasonal and permanently inundated wetland observations. Reducing uncertainty in prognostic wetland dynamics modeling must take into account forcing data as well as topographic scaling schemes.
Scot M. Miller, Roisin Commane, Joe R. Melton, Arlyn E. Andrews, Joshua Benmergui, Edward J. Dlugokencky, Greet Janssens-Maenhout, Anna M. Michalak, Colm Sweeney, and Doug E. J. Worthy
Biogeosciences, 13, 1329–1339, https://doi.org/10.5194/bg-13-1329-2016, https://doi.org/10.5194/bg-13-1329-2016, 2016
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We use atmospheric data from the US and Canada to examine seven wetland methane flux estimates. Relative to existing estimates, we find a methane source that is smaller in magnitude with a broader seasonal cycle. Furthermore, we estimate the largest fluxes over the Hudson Bay Lowlands, a spatial distribution that differs from commonly used remote sensing estimates of wetland location.
V. Haverd, B. Smith, M. Raupach, P. Briggs, L. Nieradzik, J. Beringer, L. Hutley, C. M. Trudinger, and J. Cleverly
Biogeosciences, 13, 761–779, https://doi.org/10.5194/bg-13-761-2016, https://doi.org/10.5194/bg-13-761-2016, 2016
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We present a new approach for modelling coupled phenology and carbon allocation in savannas, and test it using data from the OzFlux network. Model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, in response to resource availability, and not from imposed hypotheses about the controls on tree-grass co-existence. Results indicate that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.
J. R. Melton and V. K. Arora
Geosci. Model Dev., 9, 323–361, https://doi.org/10.5194/gmd-9-323-2016, https://doi.org/10.5194/gmd-9-323-2016, 2016
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We use a modified form of the Lotka–Volterra (L–V) equations to simulate competition between plant functional types (PFTs) on a global scale with the Canadian Terrestrial Ecosystem Model (CTEM) version 2.0. Our modified L–V simulations compare well against observation-based records of PFT distributions, while simulations with unmodified L–V equations show significant biases. We include an appendix detailing all aspects of CTEM v. 2.0.
J. Ryder, J. Polcher, P. Peylin, C. Ottlé, Y. Chen, E. van Gorsel, V. Haverd, M. J. McGrath, K. Naudts, J. Otto, A. Valade, and S. Luyssaert
Geosci. Model Dev., 9, 223–245, https://doi.org/10.5194/gmd-9-223-2016, https://doi.org/10.5194/gmd-9-223-2016, 2016
H.-M. Lee, F. Paulot, D. K. Henze, K. Travis, D. J. Jacob, L. H. Pardo, and B. A. Schichtel
Atmos. Chem. Phys., 16, 525–540, https://doi.org/10.5194/acp-16-525-2016, https://doi.org/10.5194/acp-16-525-2016, 2016
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Sources of nitrogen deposition (Ndep) in Federal Class I areas in the US are investigated, identifying unique features in contributions from different species, sectors and locations. Ndep in many parks is impacted by emissions several hundred km away; the role of oxidized vs reduced sources varies regionally. Emissions reductions in the western US most effectively reduce the extent of areas in critical load exceedance, while reductions in the east most effectively reduce exceedance magnitudes.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
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We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
D. Fowler, C. E. Steadman, D. Stevenson, M. Coyle, R. M. Rees, U. M. Skiba, M. A. Sutton, J. N. Cape, A. J. Dore, M. Vieno, D. Simpson, S. Zaehle, B. D. Stocker, M. Rinaldi, M. C. Facchini, C. R. Flechard, E. Nemitz, M. Twigg, J. W. Erisman, K. Butterbach-Bahl, and J. N. Galloway
Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, https://doi.org/10.5194/acp-15-13849-2015, 2015
M. W. Shephard, C. A. McLinden, K. E. Cady-Pereira, M. Luo, S. G. Moussa, A. Leithead, J. Liggio, R. M. Staebler, A. Akingunola, P. Makar, P. Lehr, J. Zhang, D. K. Henze, D. B. Millet, J. O. Bash, L. Zhu, K. C. Wells, S. L. Capps, S. Chaliyakunnel, M. Gordon, K. Hayden, J. R. Brook, M. Wolde, and S.-M. Li
Atmos. Meas. Tech., 8, 5189–5211, https://doi.org/10.5194/amt-8-5189-2015, https://doi.org/10.5194/amt-8-5189-2015, 2015
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This study provides direct validations of Tropospheric Emission Spectrometer (TES) satellite retrieved profiles against coincident aircraft profiles of carbon monoxide, ammonia, methanol, and formic acid, all of which are of interest for air quality. The comparisons are performed over the Canadian oil sands region during an intensive field campaign in support of the Joint Canada-Alberta Implementation Plan for the Oil Sands Monitoring (JOSM). Initial model evaluations are also provided.
C. Mathison, A. J. Wiltshire, P. Falloon, and A. J. Challinor
Hydrol. Earth Syst. Sci., 19, 4783–4810, https://doi.org/10.5194/hess-19-4783-2015, https://doi.org/10.5194/hess-19-4783-2015, 2015
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South Asia is a highly variable region where there is concern over water and food security. The simulations presented suggest an increasing trend in water resources, in some cases almost doubling by the end of the century although this is masked by the large annual variability of river flows for this region. Future peak river flows still occur during the monsoon period, with a tendency for reduced frequency of lowest flows and increased magnitude of highest flows across the selected locations.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
S. Olin, M. Lindeskog, T. A. M. Pugh, G. Schurgers, D. Wårlind, M. Mishurov, S. Zaehle, B. D. Stocker, B. Smith, and A. Arneth
Earth Syst. Dynam., 6, 745–768, https://doi.org/10.5194/esd-6-745-2015, https://doi.org/10.5194/esd-6-745-2015, 2015
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Croplands are vital ecosystems for human well-being. Properly managed they can supply food, store carbon and even sequester carbon from the atmosphere. Conversely, if poorly managed, croplands can be a source of nitrogen to inland and coastal waters, causing algal blooms, and a source of carbon dioxide to the atmosphere, accentuating climate change. Here we studied cropland management types for their potential to store carbon and minimize nitrogen losses while maintaining crop yields.
L. Zhu, D. Henze, J. Bash, G.-R. Jeong, K. Cady-Pereira, M. Shephard, M. Luo, F. Paulot, and S. Capps
Atmos. Chem. Phys., 15, 12823–12843, https://doi.org/10.5194/acp-15-12823-2015, https://doi.org/10.5194/acp-15-12823-2015, 2015
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We implement new diurnal variation scheme for ammonia livestock emissions and bidirectional exchange scheme and its adjoint in the GEOS-Chem global chemical transport model. Updated diurnal variability improves modeled-to-hourly in situ measurements comparison. The ammonium soil pool in the bidirectional exchange model largely extends the ammonia lifetime in the atmosphere. Large model biases remain as livestock emissions are still underestimated.
J. E. M. S. Nabel
Geosci. Model Dev., 8, 3563–3577, https://doi.org/10.5194/gmd-8-3563-2015, https://doi.org/10.5194/gmd-8-3563-2015, 2015
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Dynamic vegetation models (DVMs) often have high computational expenses, which the presented dynamic two-layer classification concept (D2C) aims to reduce. When implementing D2C into a DVM, a new layer for the dynamic grouping of grid-cells with similar climate and species compositions is introduced. The grouping of cells reduces the number of required calculations. With TreeMig-2L, I present how D2C can be implemented in a DVM and demonstrate that D2C can strongly reduce computational expenses.
F. Deng, D. B. A. Jones, T. W. Walker, M. Keller, K. W. Bowman, D. K. Henze, R. Nassar, E. A. Kort, S. C. Wofsy, K. A. Walker, A. E. Bourassa, and D. A. Degenstein
Atmos. Chem. Phys., 15, 11773–11788, https://doi.org/10.5194/acp-15-11773-2015, https://doi.org/10.5194/acp-15-11773-2015, 2015
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The upper troposphere and lower stratosphere (UTLS) is characterized by strong gradients in the distribution of long-lived tracers, which are sensitive to discrepancies in transport in models. We found that our model overestimates CO2 in the polar UTLS through comparison of modeled CO2 with aircraft observations. We then corrected the modeled CO2 and quantified the impact of the correction on the flux estimates using an atmospheric model together with atmospheric CO2 measured from a satellite.
K. C. Wells, D. B. Millet, N. Bousserez, D. K. Henze, S. Chaliyakunnel, T. J. Griffis, Y. Luan, E. J. Dlugokencky, R. G. Prinn, S. O'Doherty, R. F. Weiss, G. S. Dutton, J. W. Elkins, P. B. Krummel, R. Langenfelds, L. P. Steele, E. A. Kort, S. C. Wofsy, and T. Umezawa
Geosci. Model Dev., 8, 3179–3198, https://doi.org/10.5194/gmd-8-3179-2015, https://doi.org/10.5194/gmd-8-3179-2015, 2015
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This paper introduces a new inversion framework for N2O using GEOS-Chem and its adjoint, which we employed in a series of observing system simulation experiments to evaluate the source and sink constraints provided by surface and aircraft-based N2O measurements. We also applied a new approach for estimating a posteriori uncertainty for high-dimensional inversions, and used it to quantify the spatial and temporal resolution of N2O emission constraints achieved with the current observing network.
Y. Zhao, L. Zhang, Y. Pan, Y. Wang, F. Paulot, and D. K. Henze
Atmos. Chem. Phys., 15, 10905–10924, https://doi.org/10.5194/acp-15-10905-2015, https://doi.org/10.5194/acp-15-10905-2015, 2015
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Rapid Asian industrialization has led to increased atmospheric nitrogen deposition downwind. This work analyzes the sources and processes controlling atmospheric nitrogen deposition to the northwestern Pacific. Both nitrogen emissions and meteorology, largely controlled by the East Asian Monsoon, determine the seasonality of nitrogen deposition. Ascribing deposition over the marginal seas to nitrogen sources from different regions and sectors shows important contribution from fertilizer use.
P. D. Hamer, K. W. Bowman, D. K. Henze, J.-L. Attié, and V. Marécal
Atmos. Chem. Phys., 15, 10645–10667, https://doi.org/10.5194/acp-15-10645-2015, https://doi.org/10.5194/acp-15-10645-2015, 2015
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Using a simplified air quality forecasting model, we explore how characteristics of air quality observations affect our ability to understand and predict ozone air pollution. We show that the photochemical conditions can strongly influence the observing priorities for ozone prediction, such as which species are observed and how well, when, and how frequently. High-freqency observations of ozone, NOx and HCHO in combination during the morning and afternoon are particularly advantageous.
L. Zhang, D. K. Henze, G. A. Grell, G. R. Carmichael, N. Bousserez, Q. Zhang, O. Torres, C. Ahn, Z. Lu, J. Cao, and Y. Mao
Atmos. Chem. Phys., 15, 10281–10308, https://doi.org/10.5194/acp-15-10281-2015, https://doi.org/10.5194/acp-15-10281-2015, 2015
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We attempt to reduce uncertainties in BC emissions and improve BC model simulations by developing top-down, spatially resolved, estimates of BC emissions through assimilation of OMI observations of aerosol absorption optical depth (AAOD) with the GEOS-Chem model and its adjoint for April and October of 2006. Despite the limitations and uncertainties, using OMI AAOD to constrain BC sources we are able to improve model representation of BC distributions, particularly over China.
C. D. Koven, J. Q. Chambers, K. Georgiou, R. Knox, R. Negron-Juarez, W. J. Riley, V. K. Arora, V. Brovkin, P. Friedlingstein, and C. D. Jones
Biogeosciences, 12, 5211–5228, https://doi.org/10.5194/bg-12-5211-2015, https://doi.org/10.5194/bg-12-5211-2015, 2015
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Terrestrial carbon feedbacks are a large uncertainty in climate change. We separate modeled feedback responses into those governed by changed carbon inputs (productivity) and changed outputs (turnover). The disaggregated responses show that both are important in controlling inter-model uncertainty. Interactions between productivity and turnover are also important, and research must focus on these interactions for more accurate projections of carbon cycle feedbacks.
J. R. Worden, A. J. Turner, A. Bloom, S. S. Kulawik, J. Liu, M. Lee, R. Weidner, K. Bowman, C. Frankenberg, R. Parker, and V. H. Payne
Atmos. Meas. Tech., 8, 3433–3445, https://doi.org/10.5194/amt-8-3433-2015, https://doi.org/10.5194/amt-8-3433-2015, 2015
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Here we demonstrate the potential for estimating lower tropospheric CH4 concentrations through the combination of free-tropospheric methane measurements from the Aura Tropospheric Emission Spectrometer (TES) and XCH4 (dry-mole air fraction of methane) from the Greenhouse Gases Observing Satellite - Thermal And Near-infrared for carbon Observation (GOSAT TANSO).
T. Launois, P. Peylin, S. Belviso, and B. Poulter
Atmos. Chem. Phys., 15, 9285–9312, https://doi.org/10.5194/acp-15-9285-2015, https://doi.org/10.5194/acp-15-9285-2015, 2015
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
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In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
B. Poulter, N. MacBean, A. Hartley, I. Khlystova, O. Arino, R. Betts, S. Bontemps, M. Boettcher, C. Brockmann, P. Defourny, S. Hagemann, M. Herold, G. Kirches, C. Lamarche, D. Lederer, C. Ottlé, M. Peters, and P. Peylin
Geosci. Model Dev., 8, 2315–2328, https://doi.org/10.5194/gmd-8-2315-2015, https://doi.org/10.5194/gmd-8-2315-2015, 2015
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Land cover is an essential variable in earth system models and determines conditions driving biogeochemical, energy and water exchange between ecosystems and the atmosphere. A methodology is presented for mapping plant functional types used in global vegetation models from a updated land cover classification system and open-source conversion tool, resulting from a consultative process among map producers and modelers engaged in the European Space Agency’s Land Cover Climate Change Initiative.
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Geosci. Model Dev., 8, 2263–2283, https://doi.org/10.5194/gmd-8-2263-2015, https://doi.org/10.5194/gmd-8-2263-2015, 2015
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This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.
Y. H. Mao, Q. B. Li, D. K. Henze, Z. Jiang, D. B. A. Jones, M. Kopacz, C. He, L. Qi, M. Gao, W.-M. Hao, and K.-N. Liou
Atmos. Chem. Phys., 15, 7685–7702, https://doi.org/10.5194/acp-15-7685-2015, https://doi.org/10.5194/acp-15-7685-2015, 2015
K. Nishina, A. Ito, P. Falloon, A. D. Friend, D. J. Beerling, P. Ciais, D. B. Clark, R. Kahana, E. Kato, W. Lucht, M. Lomas, R. Pavlick, S. Schaphoff, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 6, 435–445, https://doi.org/10.5194/esd-6-435-2015, https://doi.org/10.5194/esd-6-435-2015, 2015
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Our study focused on uncertainties in terrestrial C cycling under newly developed scenarios with CMIP5. This study presents first results for examining relative uncertainties of projected terrestrial C cycling in multiple projection components. Only using our new model inter-comparison project data sets enables us to evaluate various uncertainty sources in projection periods. The information on relative uncertainties is useful for climate science and climate change impact evaluation.
K. Naudts, J. Ryder, M. J. McGrath, J. Otto, Y. Chen, A. Valade, V. Bellasen, G. Berhongaray, G. Bönisch, M. Campioli, J. Ghattas, T. De Groote, V. Haverd, J. Kattge, N. MacBean, F. Maignan, P. Merilä, J. Penuelas, P. Peylin, B. Pinty, H. Pretzsch, E. D. Schulze, D. Solyga, N. Vuichard, Y. Yan, and S. Luyssaert
Geosci. Model Dev., 8, 2035–2065, https://doi.org/10.5194/gmd-8-2035-2015, https://doi.org/10.5194/gmd-8-2035-2015, 2015
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Despite the potential of forest management to mitigate climate change, none of today's predictions of future climate accounts for the impact of forest management. To address this gap in modelling capability, we developed and parametrised a land-surface model to simulate biogeochemical and biophysical effects of forest management. Comparison of model output against data showed an increased model performance in reproducing large-scale spatial patterns and inter-annual variability over Europe.
J. J. Guerrette and D. K. Henze
Geosci. Model Dev., 8, 1857–1876, https://doi.org/10.5194/gmd-8-1857-2015, https://doi.org/10.5194/gmd-8-1857-2015, 2015
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WRFPLUS-Chem is a coupled meteorology-chemistry adjoint and tangent linear model, with applications in sensitivity analysis and four-dimensional variational data assimilation. The linearized models are verified against finite difference approximations from the nonlinear forward model, WRF-Chem. A new checkpointing scheme enables data assimilation beyond 6h. New capabilities are demonstrated in an emission sensitivity study.
Z. Jiang, D. B. A. Jones, J. Worden, H. M. Worden, D. K. Henze, and Y. X. Wang
Atmos. Chem. Phys., 15, 6801–6814, https://doi.org/10.5194/acp-15-6801-2015, https://doi.org/10.5194/acp-15-6801-2015, 2015
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We present a high-resolution (0.5 x 0.667) regional CO inversion over North America in the period of June 2004–May 2005, using a combination of GEOS-Chem model and MOPITT CO observations. With optimized lateral boundary conditions, we show that regional inversion analyses can reduce the sensitivity of the CO source estimates to errors in long-range transport and in the distributions of the hydroxyl radical (OH), and consequently, provide better quantification on regional CO source estimates.
T. J. Bohn, J. R. Melton, A. Ito, T. Kleinen, R. Spahni, B. D. Stocker, B. Zhang, X. Zhu, R. Schroeder, M. V. Glagolev, S. Maksyutov, V. Brovkin, G. Chen, S. N. Denisov, A. V. Eliseev, A. Gallego-Sala, K. C. McDonald, M.A. Rawlins, W. J. Riley, Z. M. Subin, H. Tian, Q. Zhuang, and J. O. Kaplan
Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, https://doi.org/10.5194/bg-12-3321-2015, 2015
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We evaluated 21 forward models and 5 inversions over western Siberia in terms of CH4 emissions and simulated wetland areas and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite inundation products. In addition to assembling a definitive collection of methane emissions estimates for the region, we were able to identify the types of wetland maps and model features necessary for accurate simulations of high-latitude wetlands.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
Short summary
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Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
Short summary
Short summary
Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
T. Osborne, J. Gornall, J. Hooker, K. Williams, A. Wiltshire, R. Betts, and T. Wheeler
Geosci. Model Dev., 8, 1139–1155, https://doi.org/10.5194/gmd-8-1139-2015, https://doi.org/10.5194/gmd-8-1139-2015, 2015
S. M. Miller, M. N. Hayek, A. E. Andrews, I. Fung, and J. Liu
Atmos. Chem. Phys., 15, 2903–2914, https://doi.org/10.5194/acp-15-2903-2015, https://doi.org/10.5194/acp-15-2903-2015, 2015
F. Pacifico, G. A. Folberth, S. Sitch, J. M. Haywood, L. V. Rizzo, F. F. Malavelle, and P. Artaxo
Atmos. Chem. Phys., 15, 2791–2804, https://doi.org/10.5194/acp-15-2791-2015, https://doi.org/10.5194/acp-15-2791-2015, 2015
R. A. Betts, N. Golding, P. Gonzalez, J. Gornall, R. Kahana, G. Kay, L. Mitchell, and A. Wiltshire
Biogeosciences, 12, 1317–1338, https://doi.org/10.5194/bg-12-1317-2015, https://doi.org/10.5194/bg-12-1317-2015, 2015
J. R. Melton, R. K. Shrestha, and V. K. Arora
Biogeosciences, 12, 1151–1168, https://doi.org/10.5194/bg-12-1151-2015, https://doi.org/10.5194/bg-12-1151-2015, 2015
Short summary
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Net ecosystem productivity (NEP) in seasonally dry Amazon forests varies
greatly between sites with similar precipitation patterns. We ran CLASS-CTEM at two LBA Amazon sites (Tapajós 83km & Jarú Reserve) that exhibit opposite seasonal NEP cycles despite reasonably similar meteorological conditions. We find the influence of soil texture and depth, through soil moisture, on seasonal patterns of GPP and, especially, heterotrophic respiration is important for correctly simulating NEP seasonality.
Z. Jiang, D. B. A. Jones, H. M. Worden, and D. K. Henze
Atmos. Chem. Phys., 15, 1521–1537, https://doi.org/10.5194/acp-15-1521-2015, https://doi.org/10.5194/acp-15-1521-2015, 2015
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Using MOPITT (version 5) tropospheric profile and surface layer retrievals, we constrain global CO emissions in the period of June 2004 – May 2005. The inversions suggest a reduction in CO emission in the tropics and an increase in emissions at middle and high latitudes. The results demonstrate that the use of the surface layer retrievals from MOPITT can significantly mitigate the potential impacts of model bias in OH and long-range transport on CO emission estimates.
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
A. W. King, R. J. Andres, K. J. Davis, M. Hafer, D. J. Hayes, D. N. Huntzinger, B. de Jong, W. A. Kurz, A. D. McGuire, R. Vargas, Y. Wei, T. O. West, and C. W. Woodall
Biogeosciences, 12, 399–414, https://doi.org/10.5194/bg-12-399-2015, https://doi.org/10.5194/bg-12-399-2015, 2015
Z. Jiang, J. R. Worden, D. B. A. Jones, J.-T. Lin, W. W. Verstraeten, and D. K. Henze
Atmos. Chem. Phys., 15, 99–112, https://doi.org/10.5194/acp-15-99-2015, https://doi.org/10.5194/acp-15-99-2015, 2015
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We use satellite measurements of O3, CO and NO2 from TES, MOPITT and OMI to quantify O3 precursor emissions for 2006 and their impact on free tropospheric O3 over northeastern Asia. Using the adjoint of GEOS-Chem, we found that Chinese emissions have the largest influence on the free tropospheric O3. The contributions from lightning NOx in summer and India and southeastern Asia emissions in winter are sizable, comparable with Chinese emissions.
Y. Wei, S. Liu, D. N. Huntzinger, A. M. Michalak, N. Viovy, W. M. Post, C. R. Schwalm, K. Schaefer, A. R. Jacobson, C. Lu, H. Tian, D. M. Ricciuto, R. B. Cook, J. Mao, and X. Shi
Geosci. Model Dev., 7, 2875–2893, https://doi.org/10.5194/gmd-7-2875-2014, https://doi.org/10.5194/gmd-7-2875-2014, 2014
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
Short summary
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ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
L. R. Boysen, V. Brovkin, V. K. Arora, P. Cadule, N. de Noblet-Ducoudré, E. Kato, J. Pongratz, and V. Gayler
Earth Syst. Dynam., 5, 309–319, https://doi.org/10.5194/esd-5-309-2014, https://doi.org/10.5194/esd-5-309-2014, 2014
Q. Zhu, Q. Zhuang, D. Henze, K. Bowman, M. Chen, Y. Liu, Y. He, H. Matsueda, T. Machida, Y. Sawa, and W. Oechel
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-22587-2014, https://doi.org/10.5194/acpd-14-22587-2014, 2014
Revised manuscript not accepted
J. B. Fisher, M. Sikka, W. C. Oechel, D. N. Huntzinger, J. R. Melton, C. D. Koven, A. Ahlström, M. A. Arain, I. Baker, J. M. Chen, P. Ciais, C. Davidson, M. Dietze, B. El-Masri, D. Hayes, C. Huntingford, A. K. Jain, P. E. Levy, M. R. Lomas, B. Poulter, D. Price, A. K. Sahoo, K. Schaefer, H. Tian, E. Tomelleri, H. Verbeeck, N. Viovy, R. Wania, N. Zeng, and C. E. Miller
Biogeosciences, 11, 4271–4288, https://doi.org/10.5194/bg-11-4271-2014, https://doi.org/10.5194/bg-11-4271-2014, 2014
V. Haverd, B. Smith, L. P. Nieradzik, and P. R. Briggs
Biogeosciences, 11, 4039–4055, https://doi.org/10.5194/bg-11-4039-2014, https://doi.org/10.5194/bg-11-4039-2014, 2014
K. E. Cady-Pereira, S. Chaliyakunnel, M. W. Shephard, D. B. Millet, M. Luo, and K. C. Wells
Atmos. Meas. Tech., 7, 2297–2311, https://doi.org/10.5194/amt-7-2297-2014, https://doi.org/10.5194/amt-7-2297-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
N. M. Fyllas, E. Gloor, L. M. Mercado, S. Sitch, C. A. Quesada, T. F. Domingues, D. R. Galbraith, A. Torre-Lezama, E. Vilanova, H. Ramírez-Angulo, N. Higuchi, D. A. Neill, M. Silveira, L. Ferreira, G. A. Aymard C., Y. Malhi, O. L. Phillips, and J. Lloyd
Geosci. Model Dev., 7, 1251–1269, https://doi.org/10.5194/gmd-7-1251-2014, https://doi.org/10.5194/gmd-7-1251-2014, 2014
Z. Shen, J. Liu, L. W. Horowitz, D. K. Henze, S. Fan, Levy II H., D. L. Mauzerall, J.-T. Lin, and S. Tao
Atmos. Chem. Phys., 14, 6315–6327, https://doi.org/10.5194/acp-14-6315-2014, https://doi.org/10.5194/acp-14-6315-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
K. Gribanov, J. Jouzel, V. Bastrikov, J.-L. Bonne, F.-M. Breon, M. Butzin, O. Cattani, V. Masson-Delmotte, N. Rokotyan, M. Werner, and V. Zakharov
Atmos. Chem. Phys., 14, 5943–5957, https://doi.org/10.5194/acp-14-5943-2014, https://doi.org/10.5194/acp-14-5943-2014, 2014
A. J. Wiltshire
The Cryosphere, 8, 941–958, https://doi.org/10.5194/tc-8-941-2014, https://doi.org/10.5194/tc-8-941-2014, 2014
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
F. Deng, D. B. A. Jones, D. K. Henze, N. Bousserez, K. W. Bowman, J. B. Fisher, R. Nassar, C. O'Dell, D. Wunch, P. O. Wennberg, E. A. Kort, S. C. Wofsy, T. Blumenstock, N. M. Deutscher, D. W. T. Griffith, F. Hase, P. Heikkinen, V. Sherlock, K. Strong, R. Sussmann, and T. Warneke
Atmos. Chem. Phys., 14, 3703–3727, https://doi.org/10.5194/acp-14-3703-2014, https://doi.org/10.5194/acp-14-3703-2014, 2014
B. Smith, D. Wårlind, A. Arneth, T. Hickler, P. Leadley, J. Siltberg, and S. Zaehle
Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, https://doi.org/10.5194/bg-11-2027-2014, 2014
K. Nishina, A. Ito, D. J. Beerling, P. Cadule, P. Ciais, D. B. Clark, P. Falloon, A. D. Friend, R. Kahana, E. Kato, R. Keribin, W. Lucht, M. Lomas, T. T. Rademacher, R. Pavlick, S. Schaphoff, N. Vuichard, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 5, 197–209, https://doi.org/10.5194/esd-5-197-2014, https://doi.org/10.5194/esd-5-197-2014, 2014
I. N. Fletcher, L. E. O. C. Aragão, A. Lima, Y. Shimabukuro, and P. Friedlingstein
Biogeosciences, 11, 1449–1459, https://doi.org/10.5194/bg-11-1449-2014, https://doi.org/10.5194/bg-11-1449-2014, 2014
K. C. Wells, D. B. Millet, K. E. Cady-Pereira, M. W. Shephard, D. K. Henze, N. Bousserez, E. C. Apel, J. de Gouw, C. Warneke, and H. B. Singh
Atmos. Chem. Phys., 14, 2555–2570, https://doi.org/10.5194/acp-14-2555-2014, https://doi.org/10.5194/acp-14-2555-2014, 2014
J. R. Melton and V. K. Arora
Biogeosciences, 11, 1021–1036, https://doi.org/10.5194/bg-11-1021-2014, https://doi.org/10.5194/bg-11-1021-2014, 2014
S. M. Miller, A. M. Michalak, and P. J. Levi
Geosci. Model Dev., 7, 303–315, https://doi.org/10.5194/gmd-7-303-2014, https://doi.org/10.5194/gmd-7-303-2014, 2014
D. Dalmonech, A. M. Foley, A. Anav, P. Friedlingstein, A. D. Friend, M. Kidston, M. Willeit, and S. Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-2083-2014, https://doi.org/10.5194/bgd-11-2083-2014, 2014
Revised manuscript has not been submitted
C. R. Schwalm, D. N. Huntinzger, R. B. Cook, Y. Wei, I. T. Baker, R. P. Neilson, B. Poulter, P. Caldwell, G. Sun, H. Q. Tian, and N. Zeng
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-1801-2014, https://doi.org/10.5194/bgd-11-1801-2014, 2014
Revised manuscript not accepted
B. Guenet, F. E. Moyano, N. Vuichard, G. J. D. Kirk, P. H. Bellamy, S. Zaehle, and P. Ciais
Geosci. Model Dev., 6, 2153–2163, https://doi.org/10.5194/gmd-6-2153-2013, https://doi.org/10.5194/gmd-6-2153-2013, 2013
D. N. Huntzinger, C. Schwalm, A. M. Michalak, K. Schaefer, A. W. King, Y. Wei, A. Jacobson, S. Liu, R. B. Cook, W. M. Post, G. Berthier, D. Hayes, M. Huang, A. Ito, H. Lei, C. Lu, J. Mao, C. H. Peng, S. Peng, B. Poulter, D. Riccuito, X. Shi, H. Tian, W. Wang, N. Zeng, F. Zhao, and Q. Zhu
Geosci. Model Dev., 6, 2121–2133, https://doi.org/10.5194/gmd-6-2121-2013, https://doi.org/10.5194/gmd-6-2121-2013, 2013
H. Tian, G. Chen, C. Lu, X. Xu, W. Ren, K. Banger, B. Zhang, B. Tao, S. Pan, M. Liu, and C. Zhang
Biogeosciences Discuss., https://doi.org/10.5194/bgd-10-19811-2013, https://doi.org/10.5194/bgd-10-19811-2013, 2013
Revised manuscript has not been submitted
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
C. Yue, P. Ciais, S. Luyssaert, P. Cadule, J. Harden, J. Randerson, V. Bellassen, T. Wang, S. L. Piao, B. Poulter, and N. Viovy
Biogeosciences, 10, 8233–8252, https://doi.org/10.5194/bg-10-8233-2013, https://doi.org/10.5194/bg-10-8233-2013, 2013
B. S. Meland, X. Xu, D. K. Henze, and J. Wang
Atmos. Meas. Tech., 6, 3441–3457, https://doi.org/10.5194/amt-6-3441-2013, https://doi.org/10.5194/amt-6-3441-2013, 2013
Y. Song, A. K. Jain, and G. F. McIsaac
Biogeosciences, 10, 8039–8066, https://doi.org/10.5194/bg-10-8039-2013, https://doi.org/10.5194/bg-10-8039-2013, 2013
C. Ottlé, J. Lescure, F. Maignan, B. Poulter, T. Wang, and N. Delbart
Earth Syst. Sci. Data, 5, 331–348, https://doi.org/10.5194/essd-5-331-2013, https://doi.org/10.5194/essd-5-331-2013, 2013
P. C. Stoy, M. C. Dietze, A. D. Richardson, R. Vargas, A. G. Barr, R. S. Anderson, M. A. Arain, I. T. Baker, T. A. Black, J. M. Chen, R. B. Cook, C. M. Gough, R. F. Grant, D. Y. Hollinger, R. C. Izaurralde, C. J. Kucharik, P. Lafleur, B. E. Law, S. Liu, E. Lokupitiya, Y. Luo, J. W. Munger, C. Peng, B. Poulter, D. T. Price, D. M. Ricciuto, W. J. Riley, A. K. Sahoo, K. Schaefer, C. R. Schwalm, H. Tian, H. Verbeeck, and E. Weng
Biogeosciences, 10, 6893–6909, https://doi.org/10.5194/bg-10-6893-2013, https://doi.org/10.5194/bg-10-6893-2013, 2013
D. Lombardozzi, J. P. Sparks, and G. Bonan
Biogeosciences, 10, 6815–6831, https://doi.org/10.5194/bg-10-6815-2013, https://doi.org/10.5194/bg-10-6815-2013, 2013
D. Dalmonech and S. Zaehle
Biogeosciences, 10, 4189–4210, https://doi.org/10.5194/bg-10-4189-2013, https://doi.org/10.5194/bg-10-4189-2013, 2013
R. Wania, J. R. Melton, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, G. Chen, A. V. Eliseev, P. O. Hopcroft, W. J. Riley, Z. M. Subin, H. Tian, P. M. van Bodegom, T. Kleinen, Z. C. Yu, J. S. Singarayer, S. Zürcher, D. P. Lettenmaier, D. J. Beerling, S. N. Denisov, C. Prigent, F. Papa, and J. O. Kaplan
Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, https://doi.org/10.5194/gmd-6-617-2013, 2013
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
S. Hagemann, C. Chen, D. B. Clark, S. Folwell, S. N. Gosling, I. Haddeland, N. Hanasaki, J. Heinke, F. Ludwig, F. Voss, and A. J. Wiltshire
Earth Syst. Dynam., 4, 129–144, https://doi.org/10.5194/esd-4-129-2013, https://doi.org/10.5194/esd-4-129-2013, 2013
X. Yang, W. M. Post, P. E. Thornton, and A. Jain
Biogeosciences, 10, 2525–2537, https://doi.org/10.5194/bg-10-2525-2013, https://doi.org/10.5194/bg-10-2525-2013, 2013
B. B. B. Booth, D. Bernie, D. McNeall, E. Hawkins, J. Caesar, C. Boulton, P. Friedlingstein, and D. M. H. Sexton
Earth Syst. Dynam., 4, 95–108, https://doi.org/10.5194/esd-4-95-2013, https://doi.org/10.5194/esd-4-95-2013, 2013
V. Haverd, M. R. Raupach, P. R. Briggs, J. G. Canadell, P. Isaac, C. Pickett-Heaps, S. H. Roxburgh, E. van Gorsel, R. A. Viscarra Rossel, and Z. Wang
Biogeosciences, 10, 2011–2040, https://doi.org/10.5194/bg-10-2011-2013, https://doi.org/10.5194/bg-10-2011-2013, 2013
L. Hu, D. B. Millet, S. Y. Kim, K. C. Wells, T. J. Griffis, E. V. Fischer, D. Helmig, J. Hueber, and A. J. Curtis
Atmos. Chem. Phys., 13, 3379–3392, https://doi.org/10.5194/acp-13-3379-2013, https://doi.org/10.5194/acp-13-3379-2013, 2013
V. Haverd, M. R. Raupach, P. R. Briggs, J. G. Canadell., S. J. Davis, R. M. Law, C. P. Meyer, G. P. Peters, C. Pickett-Heaps, and B. Sherman
Biogeosciences, 10, 851–869, https://doi.org/10.5194/bg-10-851-2013, https://doi.org/10.5194/bg-10-851-2013, 2013
J. R. Melton, R. Wania, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, D. J. Beerling, G. Chen, A. V. Eliseev, S. N. Denisov, P. O. Hopcroft, D. P. Lettenmaier, W. J. Riley, J. S. Singarayer, Z. M. Subin, H. Tian, S. Zürcher, V. Brovkin, P. M. van Bodegom, T. Kleinen, Z. C. Yu, and J. O. Kaplan
Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, https://doi.org/10.5194/bg-10-753-2013, 2013
Related subject area
Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Tracing the origins of stratospheric ozone intrusions: direct vs. indirect pathways and their impacts on Central and Eastern China in spring–summer 2019
Flow-dependent observation errors for greenhouse gas inversions in an ensemble Kalman smoother
Observational and model evidence for a prominent stratospheric influence on variability in tropospheric nitrous oxide
Estimation of Canada's methane emissions: inverse modelling analysis using the Environment and Climate Change Canada (ECCC) measurement network
Spatiotemporal source apportionment of ozone pollution over the Greater Bay Area
Potential of 14C-based vs. ΔCO-based ΔffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions
On the uncertainty of anthropogenic aromatic volatile organic compound emissions: model evaluation and sensitivity analysis
A mechanism of stratospheric O3 intrusion into the atmospheric environment: a case study of the North China Plain
Influence of atmospheric circulation on the interannual variability of transport from global and regional emissions into the Arctic
The role of OCO-3 XCO2 retrievals in estimating global terrestrial net ecosystem exchanges
Surface networks in the Arctic may miss a future methane bomb
Potential of using CO2 observations over India in a regional carbon budget estimation by improving the modelling system
A bottom-up emission estimate for the 2022 Nord Stream gas leak: derivation, simulations, and evaluation
An improved Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST): update, validation and applications
European CH4 inversions with ICON-ART coupled to the CarbonTracker Data Assimilation Shell
Extreme weather exacerbates ozone pollution in the Pearl River Delta, China: role of natural processes
Multidecadal ozone trends in China and implications for human health and crop yields: a hybrid approach combining a chemical transport model and machine learning
On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO2 in WRF-Chem – comparisons to in situ, satellite, and MAX-DOAS observations
Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling
The sensitivity of Southern Ocean atmospheric dimethyl sulfide (DMS) to modeled oceanic DMS concentrations and emissions
Impacts of maritime shipping on air pollution along the US East Coast
Understanding greenhouse gas (GHG) column concentrations in Munich using the Weather Research and Forecasting (WRF) model
Impact of transport model resolution and a priori assumptions on inverse modeling of Swiss F-gas emissions
Estimation of power plant SO2 emissions using the HYSPLIT dispersion model and airborne observations with plume rise ensemble runs
Can we use atmospheric CO2 measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris
A new steady-state gas–particle partitioning model of polycyclic aromatic hydrocarbons: implication for the influence of the particulate proportion in emissions
An analysis of CMAQ gas-phase dry deposition over North America through grid-scale and land-use-specific diagnostics in the context of AQMEII4
Rethinking the role of transport and photochemistry in regional ozone pollution: insights from ozone concentration and mass budgets
Decreasing seasonal cycle amplitude of methane in the northern high latitudes being driven by lower-latitude changes in emissions and transport
The effect of anthropogenic emission, meteorological factors, and carbon dioxide on the surface ozone increase in China from 2008 to 2018 during the East Asia summer monsoon season
Development of a CMAQ–PMF-based composite index for prescribing an effective ozone abatement strategy: a case study of sensitivity of surface ozone to precursor volatile organic compound species in southern Taiwan
Comment on “Climate consequences of hydrogen emissions” by Ocko and Hamburg (2022)
Constraining emissions of volatile organic compounds from western US wildfires with WE-CAN and FIREX-AQ airborne observations
Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action
Coupled mesoscale–microscale modeling of air quality in a polluted city using WRF-LES-Chem
Impact of aerosol optics on vertical distribution of ozone in autumn over Yangtze River Delta
A view of the European carbon flux landscape through the lens of the ICOS atmospheric observation network
Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020
Evaluation of simulated CO2 power plant plumes from six high-resolution atmospheric transport models
Impacts of urbanization on air quality and the related health risks in a city with complex terrain
Optimizing 4 years of CO2 biospheric fluxes from OCO-2 and in situ data in TM5: fire emissions from GFED and inferred from MOPITT CO data
Development and application of a multi-scale modeling framework for urban high-resolution NO2 pollution mapping
Towards monitoring the CO2 source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO2 mole fraction
Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations
Estimated regional CO2 flux and uncertainty based on an ensemble of atmospheric CO2 inversions
Assessing the representativity of NH3 measurements influenced by boundary-layer dynamics and the turbulent dispersion of a nearby emission source
Analysis of CO2, CH4, and CO surface and column concentrations observed at Réunion Island by assessing WRF-Chem simulations
Technical note: Interpretation of field observations of point-source methane plume using observation-driven large-eddy simulations
Quantifying fossil fuel methane emissions using observations of atmospheric ethane and an uncertain emission ratio
The impact of peripheral circulation characteristics of typhoon on sustained ozone episodes over the Pearl River Delta region, China
Kai Meng, Tianliang Zhao, Yongqing Bai, Ming Wu, Le Cao, Xuewei Hou, Yuehan Luo, and Yongcheng Jiang
Atmos. Chem. Phys., 24, 12623–12642, https://doi.org/10.5194/acp-24-12623-2024, https://doi.org/10.5194/acp-24-12623-2024, 2024
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We studied the impact of stratospheric intrusions (SIs) on tropospheric and near-surface ozone in Central and Eastern China from a stratospheric source tracing perspective. SIs contribute the most in the eastern plains, with a contribution exceeding 15 %, and have a small contribution to the west and south. Western Siberia and Mongolia are the most critical source areas for indirect and direct SIs, with the Rossby wave and northeast cold vortex being important driving circulation systems.
Michael Steiner, Luca Cantarello, Stephan Henne, and Dominik Brunner
Atmos. Chem. Phys., 24, 12447–12463, https://doi.org/10.5194/acp-24-12447-2024, https://doi.org/10.5194/acp-24-12447-2024, 2024
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Atmospheric greenhouse gas inversions have great potential to independently check reported bottom-up emissions; however they are subject to large uncertainties. It is paramount to address and reduce the largest source of uncertainty, which stems from the representation of atmospheric transport in the models. In this study, we show that the use of a temporally varying flow-dependent atmospheric transport uncertainty can enhance the accuracy of emission estimation in an idealized experiment.
Cynthia D. Nevison, Qing Liang, Paul A. Newman, Britton B. Stephens, Geoff Dutton, Xin Lan, Roisin Commane, Yenny Gonzalez, and Eric Kort
Atmos. Chem. Phys., 24, 10513–10529, https://doi.org/10.5194/acp-24-10513-2024, https://doi.org/10.5194/acp-24-10513-2024, 2024
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This study examines the drivers of interannual variability in tropospheric N2O. New insights are obtained from aircraft data and a chemistry–climate model that explicitly simulates stratospheric N2O. The stratosphere is found to be the dominant driver of N2O variability in the Northern Hemisphere, while both the stratosphere and El Niño cycles are important in the Southern Hemisphere. These results are consistent with known atmospheric dynamics and differences between the hemispheres.
Misa Ishizawa, Douglas Chan, Doug Worthy, Elton Chan, Felix Vogel, Joe R. Melton, and Vivek K. Arora
Atmos. Chem. Phys., 24, 10013–10038, https://doi.org/10.5194/acp-24-10013-2024, https://doi.org/10.5194/acp-24-10013-2024, 2024
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Methane (CH4) emissions in Canada for 2007–2017 were estimated using Canada’s surface greenhouse gas measurements. The estimated emissions show no significant trend, but emission uncertainty was reduced as more measurement sites became available. Notably for climate change, we find the wetland CH4 emissions show a positive correlation with surface air temperature in summer. Canada’s measurement network could monitor future CH4 emission changes and compliance with climate change mitigation goals.
Yiang Chen, Xingcheng Lu, and Jimmy C. H. Fung
Atmos. Chem. Phys., 24, 8847–8864, https://doi.org/10.5194/acp-24-8847-2024, https://doi.org/10.5194/acp-24-8847-2024, 2024
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This study investigates the contribution of pollutants from different emitting periods to ozone episodes over the Greater Bay Area. The analysis reveals the variation in major spatiotemporal contributors to the O3 pollution under the influence of typhoons and subtropical high pressure. Through temporal contribution analysis, our work offers a new perspective on the evolution of O3 pollution and can aid in developing effective and timely control policies under unfavorable weather conditions.
Fabian Maier, Christian Rödenbeck, Ingeborg Levin, Christoph Gerbig, Maksym Gachkivskyi, and Samuel Hammer
Atmos. Chem. Phys., 24, 8183–8203, https://doi.org/10.5194/acp-24-8183-2024, https://doi.org/10.5194/acp-24-8183-2024, 2024
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We investigate the usage of discrete radiocarbon (14C)-based fossil fuel carbon dioxide (ffCO2) concentration estimates vs. continuous carbon monoxide (CO)-based ffCO2 estimates to evaluate the seasonal cycle of ffCO2 emissions in an urban region with an inverse modeling framework. We find that the CO-based ffCO2 estimates allow us to reconstruct robust seasonal cycles, which show the distinct COVID-19 drawdown in 2020 and can be used to validate emission inventories.
Kevin Oliveira, Marc Guevara, Oriol Jorba, Hervé Petetin, Dene Bowdalo, Carles Tena, Gilbert Montané Pinto, Franco López, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7137–7177, https://doi.org/10.5194/acp-24-7137-2024, https://doi.org/10.5194/acp-24-7137-2024, 2024
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In this work, we assess and evaluate benzene, toluene, and xylene primary emissions and air quality levels in Spain by combining observations, emission inventories, and air quality modelling techniques. The comparison between modelled and observed levels allows identifying uncertainty sources within the emission input. This contributes to improving air quality models' performance when simulating these compounds, leading to better support for the design of effective pollution control strategies.
Yuehan Luo, Tianliang Zhao, Kai Meng, Jun Hu, Qingjian Yang, Yongqing Bai, Kai Yang, Weikang Fu, Chenghao Tan, Yifan Zhang, Yanzhe Zhang, and Zhikuan Li
Atmos. Chem. Phys., 24, 7013–7026, https://doi.org/10.5194/acp-24-7013-2024, https://doi.org/10.5194/acp-24-7013-2024, 2024
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We reveal a significant mechanism of stratospheric O3 intrusion (SI) into the atmospheric environment induced by an extratropical cyclone system. This system facilitates the downward transport of stratospheric O3 to the near-surface layer by vertical coupling, involving the upper westerly trough, the middle northeast cold vortex, and the lower extratropical cyclone in the troposphere. On average, stratospheric O3 contributed 26.77 % to near-surface O3 levels over the North China Plain.
Cheng Zheng, Yutian Wu, Mingfang Ting, and Clara Orbe
Atmos. Chem. Phys., 24, 6965–6985, https://doi.org/10.5194/acp-24-6965-2024, https://doi.org/10.5194/acp-24-6965-2024, 2024
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Trace gases and aerosols in the Arctic, which typically originate from midlatitude and tropical emission regions, modulate the Arctic climate via their radiative and chemistry impacts. Thus, long-range transport of these substances is important for understanding the current and the future change of Arctic climate. By employing chemistry–climate models, we explore how year-to-year variations in the atmospheric circulation modulate atmospheric long-range transport into the Arctic.
Xingyu Wang, Fei Jiang, Hengmao Wang, Zhengqi Zhang, Mousong Wu, Jun Wang, Wei He, Weimin Ju, and Jingming Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1568, https://doi.org/10.5194/egusphere-2024-1568, 2024
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The role of Orbital Carbon Observatory 3 (OCO-3) satellites in estimating the global terrestrial near-Earth environment is unclear. So we study it by assimilating OCO-3 XCO2 alone and with OCO-2 XCO2 inversion. We found that assimilation OCO-3 XCO2 underestimated land sinks at high latitudes by retrieval alone. Joint assimilation of OCO-2 and OCO-3 XCO2 needs to be retrieved to better estimate global terrestrial NEEs.
Sophie Wittig, Antoine Berchet, Isabelle Pison, Marielle Saunois, and Jean-Daniel Paris
Atmos. Chem. Phys., 24, 6359–6373, https://doi.org/10.5194/acp-24-6359-2024, https://doi.org/10.5194/acp-24-6359-2024, 2024
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The aim of this work is to analyse how accurately a methane bomb event could be detected with the current and a hypothetically extended stationary observation network in the Arctic. For this, we incorporate synthetically modelled possible future CH4 concentrations based on plausible emission scenarios into an inverse modelling framework. We analyse how well the increase is detected in different Arctic regions and evaluate the impact of additional observation sites in this respect.
Vishnu Thilakan, Dhanyalekshmi Pillai, Jithin Sukumaran, Christoph Gerbig, Haseeb Hakkim, Vinayak Sinha, Yukio Terao, Manish Naja, and Monish Vijay Deshpande
Atmos. Chem. Phys., 24, 5315–5335, https://doi.org/10.5194/acp-24-5315-2024, https://doi.org/10.5194/acp-24-5315-2024, 2024
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This study investigates the usability of CO2 mixing ratio observations over India to infer regional carbon sources and sinks. We demonstrate that a high-resolution modelling system can represent the observed CO2 variations reasonably well by improving the transport and flux variations at a fine scale. Future carbon data assimilation systems can thus benefit from these recently available CO2 observations when fine-scale variations are adequately represented in the models.
Rostislav Kouznetsov, Risto Hänninen, Andreas Uppstu, Evgeny Kadantsev, Yalda Fatahi, Marje Prank, Dmitrii Kouznetsov, Steffen Manfred Noe, Heikki Junninen, and Mikhail Sofiev
Atmos. Chem. Phys., 24, 4675–4691, https://doi.org/10.5194/acp-24-4675-2024, https://doi.org/10.5194/acp-24-4675-2024, 2024
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By relying solely on publicly available media reports, we were able to infer the temporal evolution and the injection height for the Nord Stream gas leaks in September 2022. The inventory specifies locations, vertical distributions, and temporal evolution of the methane sources. The inventory can be used to simulate the event with atmospheric transport models. The inventory is supplemented with a set of observational data tailored to evaluate the results of the simulated atmospheric dispersion.
Zhou Zang, Jane Liu, David Tarasick, Omid Moeini, Jianchun Bian, Jinqiang Zhang, Anne M. Thompson, Roeland Van Malderen, Herman G. J. Smit, Ryan M. Stauffer, Bryan J. Johnson, and Debra E. Kollonige
EGUsphere, https://doi.org/10.5194/egusphere-2024-800, https://doi.org/10.5194/egusphere-2024-800, 2024
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The Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST) provides a global-scale, long-term ozone climatology that is horizontally- and vertically-resolved. In this study, we improved, updated, and validated the TOST from 1970 to 2021. Based on this TOST dataset, we characterized global ozone variations spatially in both the troposphere and stratosphere and temporally by season and decade. We also showed a stagnant stratospheric ozone variation since the late 1990s.
Michael Steiner, Wouter Peters, Ingrid Luijkx, Stephan Henne, Huilin Chen, Samuel Hammer, and Dominik Brunner
Atmos. Chem. Phys., 24, 2759–2782, https://doi.org/10.5194/acp-24-2759-2024, https://doi.org/10.5194/acp-24-2759-2024, 2024
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The Paris Agreement increased interest in estimating greenhouse gas (GHG) emissions of individual countries, but top-down emission estimation is not yet considered policy-relevant. It is therefore paramount to reduce large errors and to build systems that are based on the newest atmospheric transport models. In this study, we present the first application of ICON-ART in the inverse modeling of GHG fluxes with an ensemble Kalman filter and present our results for European CH4 emissions.
Nan Wang, Hongyue Wang, Xin Huang, Xi Chen, Yu Zou, Tao Deng, Tingyuan Li, Xiaopu Lyu, and Fumo Yang
Atmos. Chem. Phys., 24, 1559–1570, https://doi.org/10.5194/acp-24-1559-2024, https://doi.org/10.5194/acp-24-1559-2024, 2024
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This study explores the influence of extreme-weather-induced natural processes on ozone pollution, which is often overlooked. By analyzing meteorological factors, natural emissions, chemistry pathways and atmospheric transport, we discovered that these natural processes could substantially exacerbate ozone pollution. The findings contribute to a deeper understanding of ozone pollution and offer valuable insights for controlling ozone pollution in the context of global warming.
Jia Mao, Amos P. K. Tai, David H. Y. Yung, Tiangang Yuan, Kong T. Chau, and Zhaozhong Feng
Atmos. Chem. Phys., 24, 345–366, https://doi.org/10.5194/acp-24-345-2024, https://doi.org/10.5194/acp-24-345-2024, 2024
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Surface ozone (O3) is well-known for posing great threats to both human health and agriculture worldwide. However, a multidecadal assessment of the impacts of O3 on public health and agriculture in China is lacking without sufficient O3 observations. We used a hybrid approach combining a chemical transport model and machine learning to provide a robust dataset of O3 concentrations over the past 4 decades in China, thereby filling the gap in the long-term O3 trend and impact assessment in China.
Leon Kuhn, Steffen Beirle, Vinod Kumar, Sergey Osipov, Andrea Pozzer, Tim Bösch, Rajesh Kumar, and Thomas Wagner
Atmos. Chem. Phys., 24, 185–217, https://doi.org/10.5194/acp-24-185-2024, https://doi.org/10.5194/acp-24-185-2024, 2024
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NO₂ is an important air pollutant. It was observed that the WRF-Chem model shows significant deviations in NO₂ abundance when compared to measurements. We use a 1-month simulation over central Europe to show that these deviations can be mostly resolved by reparameterization of the vertical mixing routine. In order to validate our results, they are compared to in situ, satellite, and MAX-DOAS measurements.
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023, https://doi.org/10.5194/acp-23-15235-2023, 2023
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We show declining trends in NH3 emissions over Europe for 2013–2020 using advanced dispersion and inverse modelling and satellite measurements from CrIS. Emissions decreased by −26% since 2013, showing that the abatement strategies adopted by the European Union have been very efficient. Ammonia emissions are low in winter and peak in summer due to temperature-dependent soil volatilization. The largest decreases were observed in central and western Europe in countries with high emissions.
Yusuf A. Bhatti, Laura E. Revell, Alex J. Schuddeboom, Adrian J. McDonald, Alex T. Archibald, Jonny Williams, Abhijith U. Venugopal, Catherine Hardacre, and Erik Behrens
Atmos. Chem. Phys., 23, 15181–15196, https://doi.org/10.5194/acp-23-15181-2023, https://doi.org/10.5194/acp-23-15181-2023, 2023
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Aerosols are a large source of uncertainty over the Southern Ocean. A dominant source of sulfate aerosol in this region is dimethyl sulfide (DMS), which is poorly simulated by climate models. We show the sensitivity of simulated atmospheric DMS to the choice of oceanic DMS data set and emission scheme. We show that oceanic DMS has twice the influence on atmospheric DMS than the emission scheme. Simulating DMS more accurately in climate models will help to constrain aerosol uncertainty.
Maryam Golbazi and Cristina Archer
Atmos. Chem. Phys., 23, 15057–15075, https://doi.org/10.5194/acp-23-15057-2023, https://doi.org/10.5194/acp-23-15057-2023, 2023
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We use scientific models to study the impact of ship emissions on air quality along the US East Coast. We find an increase in three major pollutants (PM2.5, NO2, and SO2) in coastal regions. However, we detect a reduction in ozone (O3) levels in major coastal cities. This reduction is linked to the significant emissions of nitrogen oxides (NOx) from ships, which scavenged O3, especially in highly polluted urban areas experiencing an NOx-limited regime.
Xinxu Zhao, Jia Chen, Julia Marshall, Michal Gałkowski, Stephan Hachinger, Florian Dietrich, Ankit Shekhar, Johannes Gensheimer, Adrian Wenzel, and Christoph Gerbig
Atmos. Chem. Phys., 23, 14325–14347, https://doi.org/10.5194/acp-23-14325-2023, https://doi.org/10.5194/acp-23-14325-2023, 2023
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We develop a modeling framework using the Weather Research and Forecasting model at a high spatial resolution (up to 400 m) to simulate atmospheric transport of greenhouse gases and interpret column observations. Output is validated against weather stations and column measurements in August 2018. The differential column method is applied, aided by air-mass transport tracing with the Stochastic Time-Inverted Lagrangian Transport (STILT) model, also for an exploratory measurement interpretation.
Ioannis Katharopoulos, Dominique Rust, Martin K. Vollmer, Dominik Brunner, Stefan Reimann, Simon J. O'Doherty, Dickon Young, Kieran M. Stanley, Tanja Schuck, Jgor Arduini, Lukas Emmenegger, and Stephan Henne
Atmos. Chem. Phys., 23, 14159–14186, https://doi.org/10.5194/acp-23-14159-2023, https://doi.org/10.5194/acp-23-14159-2023, 2023
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The effectiveness of climate change mitigation needs to be scrutinized by monitoring greenhouse gas (GHG) emissions. Countries report their emissions to the UN in a bottom-up manner. By combining atmospheric observations and transport models someone can independently validate emission estimates in a top-down fashion. We report Swiss emissions of synthetic GHGs based on kilometer-scale transport and inverse modeling, highlighting the role of appropriate resolution in complex terrain.
Tianfeng Chai, Xinrong Ren, Fong Ngan, Mark Cohen, and Alice Crawford
Atmos. Chem. Phys., 23, 12907–12933, https://doi.org/10.5194/acp-23-12907-2023, https://doi.org/10.5194/acp-23-12907-2023, 2023
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The SO2 emissions of three power plants are estimated using aircraft observations and an ensemble of HYSPLIT dispersion simulations with different plume rise parameters. The emission estimates using the runs with the lowest root mean square errors (RMSEs) and the runs with the best correlation coefficients between the predicted and observed mixing ratios both agree well with the Continuous Emissions Monitoring Systems (CEMS) data. The RMSE-based plume rise appears to be more reasonable.
Jinghui Lian, Thomas Lauvaux, Hervé Utard, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, Olivier Laurent, Ivonne Albarus, Mali Chariot, Simone Kotthaus, Martial Haeffelin, Olivier Sanchez, Olivier Perrussel, Hugo Anne Denier van der Gon, Stijn Nicolaas Camiel Dellaert, and Philippe Ciais
Atmos. Chem. Phys., 23, 8823–8835, https://doi.org/10.5194/acp-23-8823-2023, https://doi.org/10.5194/acp-23-8823-2023, 2023
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This study quantifies urban CO2 emissions via an atmospheric inversion for the Paris metropolitan area over a 6-year period from 2016 to 2021. Results show a long-term decreasing trend of about 2 % ± 0.6 % per year in the annual CO2 emissions over Paris. We conclude that our current capacity can deliver near-real-time CO2 emission estimates at the city scale in under a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.
Fu-Jie Zhu, Peng-Tuan Hu, and Wan-Li Ma
Atmos. Chem. Phys., 23, 8583–8590, https://doi.org/10.5194/acp-23-8583-2023, https://doi.org/10.5194/acp-23-8583-2023, 2023
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A new steady-state gas–particle partitioning model of polycyclic aromatic hydrocarbons was established based on the level-III multimedia fugacity model, which proved that the particulate proportion of PAHs in emissions was a crucial factor for G–P partitioning of PAHs. In addition, gaseous and particulate interference was also derived in the new steady-state model determined by the particulate proportion in emission that could derivate the G–P partitioning quotients from the equilibrium state.
Christian Hogrefe, Jesse O. Bash, Jonathan E. Pleim, Donna B. Schwede, Robert C. Gilliam, Kristen M. Foley, K. Wyat Appel, and Rohit Mathur
Atmos. Chem. Phys., 23, 8119–8147, https://doi.org/10.5194/acp-23-8119-2023, https://doi.org/10.5194/acp-23-8119-2023, 2023
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Under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in the widely used CMAQ model. The results illustrate how these tools can provide insights into similarities and differences between the two CMAQ dry deposition options that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.
Kun Qu, Xuesong Wang, Xuhui Cai, Yu Yan, Xipeng Jin, Mihalis Vrekoussis, Maria Kanakidou, Guy P. Brasseur, Jin Shen, Teng Xiao, Limin Zeng, and Yuanhang Zhang
Atmos. Chem. Phys., 23, 7653–7671, https://doi.org/10.5194/acp-23-7653-2023, https://doi.org/10.5194/acp-23-7653-2023, 2023
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Basic understandings of ozone processes, especially transport and chemistry, are essential to support ozone pollution control, but studies often have different views on their relative importance. We developed a method to quantify their contributions in the ozone mass and concentration budgets based on the WRF-CMAQ model. Results in a polluted region highlight the differences between two budgets. For future studies, two budgets are both needed to fully understand the effects of ozone processes.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
Atmos. Chem. Phys., 23, 7363–7382, https://doi.org/10.5194/acp-23-7363-2023, https://doi.org/10.5194/acp-23-7363-2023, 2023
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Surface observations of methane show that the seasonal cycle amplitude (SCA) of methane is decreasing in the northern high latitudes (NHLs) but increased globally (1995–2020). The NHL decrease is counterintuitive, as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate changes in SCA in the NHLs. We find well-mixed methane and changes in emissions from Canada, the Middle East, and Europe are the largest contributors to the SCA in NHLs.
Danyang Ma, Tijian Wang, Hao Wu, Yawei Qu, Jian Liu, Jane Liu, Shu Li, Bingliang Zhuang, Mengmeng Li, and Min Xie
Atmos. Chem. Phys., 23, 6525–6544, https://doi.org/10.5194/acp-23-6525-2023, https://doi.org/10.5194/acp-23-6525-2023, 2023
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Increasing surface ozone (O3) concentrations have long been a significant environmental issue in China, despite the Clean Air Action Plan launched in 2013. Most previous research ignores the contributions of CO2 variations. Our study comprehensively analyzed O3 variation across China from various perspectives and highlighted the importance of considering CO2 variations when designing long-term O3 control policies, especially in high-vegetation-coverage areas.
Jackson Hian-Wui Chang, Stephen M. Griffith, Steven Soon-Kai Kong, Ming-Tung Chuang, and Neng-Huei Lin
Atmos. Chem. Phys., 23, 6357–6382, https://doi.org/10.5194/acp-23-6357-2023, https://doi.org/10.5194/acp-23-6357-2023, 2023
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A novel CMAQ–PMF-based composite index is developed to identify the key VOC source species for an effective ozone abatement strategy. The index provides information as to which VOC species are key to ozone formation and where to reduce sources of these VOC species. Using the composite index, we recommended the VOC control measures in southern Taiwan should prioritize solvent usage, vehicle emissions, and the petrochemical industry.
Lei Duan and Ken Caldeira
Atmos. Chem. Phys., 23, 6011–6020, https://doi.org/10.5194/acp-23-6011-2023, https://doi.org/10.5194/acp-23-6011-2023, 2023
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Ocko and Hamburg (2022) emphasize the short-term climate impact of hydrogen, and we present an analysis that places greater focus on long-term outcomes. We have derived equations that describe the time-evolving impact of hydrogen and show that higher methane leakage is primarily responsible for the warming potential of blue hydrogen, while hydrogen leakage plays a less critical role. Fossil fuels show more prominent longer-term climate impacts than clean hydrogen under all emission scenarios.
Lixu Jin, Wade Permar, Vanessa Selimovic, Damien Ketcherside, Robert J. Yokelson, Rebecca S. Hornbrook, Eric C. Apel, I-Ting Ku, Jeffrey L. Collett Jr., Amy P. Sullivan, Daniel A. Jaffe, Jeffrey R. Pierce, Alan Fried, Matthew M. Coggon, Georgios I. Gkatzelis, Carsten Warneke, Emily V. Fischer, and Lu Hu
Atmos. Chem. Phys., 23, 5969–5991, https://doi.org/10.5194/acp-23-5969-2023, https://doi.org/10.5194/acp-23-5969-2023, 2023
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Air quality in the USA has been improving since 1970 due to anthropogenic emission reduction. Those gains have been partly offset by increased wildfire pollution in the western USA in the past 20 years. Still, we do not understand wildfire emissions well due to limited measurements. Here, we used a global transport model to evaluate and constrain current knowledge of wildfire emissions with recent observational constraints, showing the underestimation of wildfire emissions in the western USA.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
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We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Yuting Wang, Yong-Feng Ma, Domingo Muñoz-Esparza, Jianing Dai, Cathy Wing Yi Li, Pablo Lichtig, Roy Chun-Wang Tsang, Chun-Ho Liu, Tao Wang, and Guy Pierre Brasseur
Atmos. Chem. Phys., 23, 5905–5927, https://doi.org/10.5194/acp-23-5905-2023, https://doi.org/10.5194/acp-23-5905-2023, 2023
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Air quality in urban areas is difficult to simulate in coarse-resolution models. This work exploits the WRF (Weather Research and Forecasting) model coupled with a large-eddy simulation (LES) component and online chemistry to perform high-resolution (33.3 m) simulations of air quality in a large city. The evaluation of the simulations with observations shows that increased model resolution improves the representation of the chemical species near the pollution sources.
Shuqi Yan, Bin Zhu, Shuangshuang Shi, Wen Lu, Jinhui Gao, Hanqing Kang, and Duanyang Liu
Atmos. Chem. Phys., 23, 5177–5190, https://doi.org/10.5194/acp-23-5177-2023, https://doi.org/10.5194/acp-23-5177-2023, 2023
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We analyze ozone response to aerosol mixing states in the vertical direction by WRF-Chem simulations. Aerosols generally lead to turbulent suppression, precursor accumulation, low-level photolysis reduction, and upper-level photolysis enhancement under different underlying surface and pollution conditions. Thus, ozone decreases within the entire boundary layer during the daytime, and the decrease is the least in aerosol external mixing states compared to internal and core shell mixing states.
Ida Storm, Ute Karstens, Claudio D'Onofrio, Alex Vermeulen, and Wouter Peters
Atmos. Chem. Phys., 23, 4993–5008, https://doi.org/10.5194/acp-23-4993-2023, https://doi.org/10.5194/acp-23-4993-2023, 2023
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In this study, we evaluate what is in the influence regions of the ICOS atmospheric measurement stations to gain insight into what land cover types and land-cover-associated fluxes the network represents. Subsequently, insights about strengths, weaknesses, and potential gaps can assist in future network expansion decisions. The network is concentrated in central Europe, which leads to a general overrepresentation of coniferous forest and cropland and underrepresentation of grass and shrubland.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Dominik Brunner, Gerrit Kuhlmann, Stephan Henne, Erik Koene, Bastian Kern, Sebastian Wolff, Christiane Voigt, Patrick Jöckel, Christoph Kiemle, Anke Roiger, Alina Fiehn, Sven Krautwurst, Konstantin Gerilowski, Heinrich Bovensmann, Jakob Borchardt, Michal Galkowski, Christoph Gerbig, Julia Marshall, Andrzej Klonecki, Pascal Prunet, Robert Hanfland, Margit Pattantyús-Ábrahám, Andrzej Wyszogrodzki, and Andreas Fix
Atmos. Chem. Phys., 23, 2699–2728, https://doi.org/10.5194/acp-23-2699-2023, https://doi.org/10.5194/acp-23-2699-2023, 2023
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We evaluated six atmospheric transport models for their capability to simulate the CO2 plumes from two of the largest power plants in Europe by comparing the models against aircraft observations collected during the CoMet (Carbon Dioxide and Methane Mission) campaign in 2018. The study analyzed how realistically such plumes can be simulated at different model resolutions and how well the planned European satellite mission CO2M will be able to quantify emissions from power plants.
Chenchao Zhan, Min Xie, Hua Lu, Bojun Liu, Zheng Wu, Tijian Wang, Bingliang Zhuang, Mengmeng Li, and Shu Li
Atmos. Chem. Phys., 23, 771–788, https://doi.org/10.5194/acp-23-771-2023, https://doi.org/10.5194/acp-23-771-2023, 2023
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With the development of urbanization, urban land use and anthropogenic
emissions increase, affecting urban air quality and, in turn, the health risks associated with air pollutants. In this study, we systematically evaluate the impacts of urbanization on air quality and the corresponding health risks in a highly urbanized city with severe air pollution and complex terrain. This work focuses on the health risks caused by urbanization and can provide valuable insight for air pollution strategies.
Hélène Peiro, Sean Crowell, and Berrien Moore III
Atmos. Chem. Phys., 22, 15817–15849, https://doi.org/10.5194/acp-22-15817-2022, https://doi.org/10.5194/acp-22-15817-2022, 2022
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CO data can provide a powerful constraint on fire fluxes, supporting more accurate estimation of biospheric CO2 fluxes. We converted CO fire flux into CO2 fire prior, which is then used to adjust CO2 respiration. We applied this to two other fire flux products. CO2 inversions constrained by satellites or in situ data are then performed. Results show larger variations among the data assimilated than across the priors, but tropical flux from in situ inversions is sensitive to priors.
Zhaofeng Lv, Zhenyu Luo, Fanyuan Deng, Xiaotong Wang, Junchao Zhao, Lucheng Xu, Tingkun He, Yingzhi Zhang, Huan Liu, and Kebin He
Atmos. Chem. Phys., 22, 15685–15702, https://doi.org/10.5194/acp-22-15685-2022, https://doi.org/10.5194/acp-22-15685-2022, 2022
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This study developed a hybrid model, CMAQ-RLINE_URBAN, to predict the urban NO2 concentrations at a high spatial resolution. To estimate the influence of various street canyons on the dispersion of air pollutants, a new parameterization scheme was established based on computational fluid dynamics and machine learning methods. This work created a new method to identify the characteristics of vehicle-related air pollution at both city and street scales simultaneously and accurately.
Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew
Atmos. Chem. Phys., 22, 15287–15312, https://doi.org/10.5194/acp-22-15287-2022, https://doi.org/10.5194/acp-22-15287-2022, 2022
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This paper demonstrates how we can use atmospheric observations to improve the CO2 flux estimates in India. This is achieved by improving the representation of terrain, mesoscale transport, and flux variations. We quantify the impact of the unresolved variations in the current models on optimally estimated fluxes via inverse modelling and quantify the associated flux uncertainty. We illustrate how a parameterization scheme captures this variability in the coarse models.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Naveen Chandra, Prabir K. Patra, Yousuke Niwa, Akihiko Ito, Yosuke Iida, Daisuke Goto, Shinji Morimoto, Masayuki Kondo, Masayuki Takigawa, Tomohiro Hajima, and Michio Watanabe
Atmos. Chem. Phys., 22, 9215–9243, https://doi.org/10.5194/acp-22-9215-2022, https://doi.org/10.5194/acp-22-9215-2022, 2022
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This paper is intended to accomplish two goals: (1) quantify mean and uncertainty in non-fossil-fuel CO2 fluxes estimated by inverse modeling and (2) provide in-depth analyses of regional CO2 fluxes in support of emission mitigation policymaking. CO2 flux variability and trends are discussed concerning natural climate variability and human disturbances using multiple lines of evidence.
Ruben B. Schulte, Margreet C. van Zanten, Bart J. H. van Stratum, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 22, 8241–8257, https://doi.org/10.5194/acp-22-8241-2022, https://doi.org/10.5194/acp-22-8241-2022, 2022
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We present a fine-scale simulation framework, utilizing large-eddy simulations, to assess NH3 measurements influenced by boundary-layer dynamics and turbulent dispersion of a nearby emission source. The minimum required distance from an emission source differs for concentration and flux measurements, from 0.5–3.0 km and 0.75–4.5 km, respectively. The simulation framework presented here proves to be a powerful and versatile tool for future NH3 research at high spatio-temporal resolutions.
Sieglinde Callewaert, Jérôme Brioude, Bavo Langerock, Valentin Duflot, Dominique Fonteyn, Jean-François Müller, Jean-Marc Metzger, Christian Hermans, Nicolas Kumps, Michel Ramonet, Morgan Lopez, Emmanuel Mahieu, and Martine De Mazière
Atmos. Chem. Phys., 22, 7763–7792, https://doi.org/10.5194/acp-22-7763-2022, https://doi.org/10.5194/acp-22-7763-2022, 2022
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A regional atmospheric transport model is used to analyze the factors contributing to CO2, CH4, and CO observations at Réunion Island. We show that the surface observations are dominated by local fluxes and dynamical processes, while the column data are influenced by larger-scale mechanisms such as biomass burning plumes. The model is able to capture the measured time series well; however, the results are highly dependent on accurate boundary conditions and high-resolution emission inventories.
Anja Ražnjević, Chiel van Heerwaarden, Bart van Stratum, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, and Maarten Krol
Atmos. Chem. Phys., 22, 6489–6505, https://doi.org/10.5194/acp-22-6489-2022, https://doi.org/10.5194/acp-22-6489-2022, 2022
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Mobile measurement techniques (e.g., instruments placed in cars) are often employed to identify and quantify individual sources of greenhouse gases. Due to road restrictions, those observations are often sparse (temporally and spatially). We performed high-resolution simulations of plume dispersion, with realistic weather conditions encountered in the field, to reproduce the measurement process of a methane plume emitted from an oil well and provide additional information about the plume.
Alice E. Ramsden, Anita L. Ganesan, Luke M. Western, Matthew Rigby, Alistair J. Manning, Amy Foulds, James L. France, Patrick Barker, Peter Levy, Daniel Say, Adam Wisher, Tim Arnold, Chris Rennick, Kieran M. Stanley, Dickon Young, and Simon O'Doherty
Atmos. Chem. Phys., 22, 3911–3929, https://doi.org/10.5194/acp-22-3911-2022, https://doi.org/10.5194/acp-22-3911-2022, 2022
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Quantifying methane emissions from different sources is a key focus of current research. We present a method for estimating sectoral methane emissions that uses ethane as a tracer for fossil fuel methane. By incorporating variable ethane : methane emission ratios into this model, we produce emissions estimates with improved uncertainty characterisation. This method will be particularly useful for studying methane emissions in areas with complex distributions of sources.
Ying Li, Xiangjun Zhao, Xuejiao Deng, and Jinhui Gao
Atmos. Chem. Phys., 22, 3861–3873, https://doi.org/10.5194/acp-22-3861-2022, https://doi.org/10.5194/acp-22-3861-2022, 2022
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This study finds a new phenomenon of weak wind deepening (WWD) associated with the peripheral circulation of typhoon and gives the influence mechanism of WWD on its contribution to daily variation during sustained ozone episodes. The WWD provides the premise for pollution accumulation in the whole PBL and continued enhancement of ground-level ozone via vertical mixing processes. These findings could benefit the daily daytime ozone forecast in the PRD region and other areas.
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Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use...
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