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
Related authors
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
Short summary
Short summary
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.
Elizabeth Quaye, Ben T. Johnson, James M. Haywood, Guido R. van der Werf, Roland Vernooij, Stephen A. Sitch, and Tom Eames
EGUsphere, https://doi.org/10.5194/egusphere-2025-3936, https://doi.org/10.5194/egusphere-2025-3936, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We find aerosol optical depths in a global climate model are overestimated during extreme wildfire events if emissions are scaled up by a factor of two, typically applied to improve simulated aerosol on seasonal–annual timescales. We propose a technique where a variable scaling factor is determined by fuel consumption, improving correlation in five fire-affected areas. We explore the impact of this change on aerosol radiative effects, during extreme events and on broader space and time scales.
Hui Li, Philippe Ciais, Pramod Kumar, Didier A. Hauglustaine, Frédéric Chevallier, Grégoire Broquet, Dylan B. Millet, Kelley C. Wells, Jinghui Lian, and Bo Zheng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-424, https://doi.org/10.5194/essd-2025-424, 2025
Preprint under review for ESSD
Short summary
Short summary
We present the first global, multi-year maps of monthly isoprene emissions (2013–2020) derived from satellite isoprene observations, averaging 456 TgC yr-1. The dataset reveals two emission peaks linked to 2015–2016 El Niño and 2019–2020 extreme heat events, driven mainly by tropical regions such as the Amazon. It highlights the region-specific sensitivity of biogenic isoprene emissions to temperature anomalies, providing new insights into their roles in air quality and climate feedbacks.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
Geosci. Model Dev., 18, 4915–4933, https://doi.org/10.5194/gmd-18-4915-2025, https://doi.org/10.5194/gmd-18-4915-2025, 2025
Short summary
Short summary
This study enhances the accuracy of modeling the carbon dynamics of the Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to use in refining global carbon cycle models.
Dieu Anh Tran, Jordi Vilà-Guerau de Arellano, Ingrid T. Luijkx, Christoph Gerbig, Michał Gałkowski, Santiago Botía, Kim Faassen, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2025-2351, https://doi.org/10.5194/egusphere-2025-2351, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Analysis of CH4 data (2010–2021) from ZOTTO in Central Siberia shows an increase in the summer diurnal amplitude, driven by nighttime emissions. These trends correlate with rising soil temperature and moisture, especially in late summer. Peaks in 2012, 2016, and 2019 emission link to wildfires and wetland activity. Findings suggest wetlands as key CH4 sources and underscore the need for ongoing high-resolution monitoring in this region.
Jade Skye, Joe R. Melton, Colin Goldblatt, Louis Saumier, Angela Gallego-Sala, Michelle Garneau, R. Scott Winton, Erick B. Bahati, Juan C. Benavides, Lee Fedorchuk, Gérard Imani, Carol Kagaba, Frank Kansiime, Mariusz Lamentowicz, Michel Mbasi, Daria Wochal, Sambor Czerwiński, Jacek Landowski, Joanna Landowska, Vincent Maire, Minna M. Väliranta, Matthew Warren, Lydia E. S. Cole, Marissa A. Davies, Erik A. Lilleskov, Jingjing Sun, and Yuwan Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-432, https://doi.org/10.5194/essd-2025-432, 2025
Preprint under review for ESSD
Short summary
Short summary
Peatlands are large stores of carbon but are vulnerable to human activities and climate change. Comprehensive peatland data are vital to understand these ecosystems, but existing datasets are fragmented and contain errors. To address this, we created Peat-DBase — a standardized global database of peat depth measurements with > 200,000 measurements worldwide, showing average depths of 144 cm. Peat-DBase avoids overlapping data compilation efforts while identifying critical observational gaps.
Rubaya Pervin, Scott Robeson, Mallory Barnes, Stephen Sitch, Anthony Walker, Ben Poulter, Fabienne Maignan, Qing Sun, Thomas Colligan, Sönke Zaehle, Kashif Mahmud, Peter Anthoni, Almut Arneth, Vivek Arora, Vladislav Bastrikov, Liam Bogucki, Bertrand Decharme, Christine Delire, Stefanie Falk, Akihiko Ito, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Michael O’Sullivan, Wenping Yuan, and Natasha MacBean
EGUsphere, https://doi.org/10.5194/egusphere-2025-2841, https://doi.org/10.5194/egusphere-2025-2841, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Drylands contribute more than a third of the global vegetation productivity. Yet, these regions are not well represented in global vegetation models. Here, we tested how well 15 global models capture annual changes in dryland vegetation productivity. Models that didn’t have vegetation change over time or fire have lower variability in vegetation productivity. Models need better representation of grass cover types and their coverage. Our work highlights where and how these models need to improve.
Zhixuan Guo, Wei Li, Philippe Ciais, Stephen Sitch, Guido R. van der Werf, Simon P. K. Bowring, Ana Bastos, Florent Mouillot, Jiaying He, Minxuan Sun, Lei Zhu, Xiaomeng Du, Nan Wang, and Xiaomeng Huang
Earth Syst. Sci. Data, 17, 3599–3618, https://doi.org/10.5194/essd-17-3599-2025, https://doi.org/10.5194/essd-17-3599-2025, 2025
Short summary
Short summary
To address the limitations of short time spans in satellite data and spatiotemporal discontinuity in site records, we reconstructed global monthly burned area maps at a 0.5° resolution for 1901–2020 using machine learning models. The global burned area is predicted at 3.46 × 106–4.58 × 106 km² per year, showing a decline from 1901 to 1978, an increase from 1978 to 2008 and a sharper decrease from 2008 to 2020. This dataset provides a benchmark for studies on fire ecology and the carbon cycle.
Ida Bagus Mandhara Brasika, Pierre Friedlingstein, Stephen Sitch, Michael O'Sullivan, Maria Carolina Duran-Rojas, Thais Michele Rosan, Kees Klein Goldewijk, Julia Pongratz, Clemens Schwingshackl, Louise P. Chini, and George C. Hurtt
Biogeosciences, 22, 3547–3561, https://doi.org/10.5194/bg-22-3547-2025, https://doi.org/10.5194/bg-22-3547-2025, 2025
Short summary
Short summary
Indonesia is the world's third-highest carbon emitter from land use change. However, there are uncertainties in the carbon emissions of Indonesia. Our best estimate of carbon emissions from land use change in Indonesia is 0.12 ± 0.02 PgC/yr with a steady trend. Despite many uncertainties created by drivers, models, and products, we also found robust agreements between these models and products. All agree that Indonesian carbon emissions from LULCC (land use and land cover change) have had no decreasing trend for the last 2 decades.
Gabriel Destouet, Nikola Besic, Emilie Joetzjer, and Matthias Cuntz
Atmos. Meas. Tech., 18, 3193–3215, https://doi.org/10.5194/amt-18-3193-2025, https://doi.org/10.5194/amt-18-3193-2025, 2025
Short summary
Short summary
Over the past two decades, global flux tower networks have provided valuable insights into ecosystem functioning. However, the standard eddy-covariance method used for processing flux data has limitations, leading to data loss and limited resolution due to fixed time steps. This paper introduces a new method using wavelet analysis to increase temporal resolution and improve data retention. Applied at the Hesse forest flux tower in France, this approach provides high-resolution flux estimates, enhancing the accuracy of flux measurements.
Tuuli Miinalainen, Amanda Ojasalo, Holly Croft, Mika Aurela, Mikko Peltoniemi, Silvia Caldararu, Sönke Zaehle, and Tea Thum
EGUsphere, https://doi.org/10.5194/egusphere-2025-2987, https://doi.org/10.5194/egusphere-2025-2987, 2025
Short summary
Short summary
Estimating the future carbon budget requires an accurate understanding of the interlinkages between the land carbon and nitrogen cycles. We use a remote sensing leaf chlorophyll product to evaluate a terrestrial biosphere model, QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system). Our study showcases how the latest advancements in remote sensing-based vegetation monitoring can be harnessed for improving and evaluating process-based vegetation models.
Ke Yu, Yang Su, Ronny Lauerwald, Philippe Ciais, Yi Xi, Haoran Xu, Xianglin Zhang, Nicolas Viovy, Amie Pickering, Marie Collard, and Daniel S. Goll
EGUsphere, https://doi.org/10.5194/egusphere-2025-1861, https://doi.org/10.5194/egusphere-2025-1861, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Coupling crop and land surface models helps quantify the climate effects of agriculture, but lacks crop-specific management processes. We enhanced a land surface model with time-varying albedo from foliar yellowing and residue cover, improving the simulation of energy and water fluxes. Results show cooler surfaces and slightly wetter soils during residue cover, highlighting how managements improve climate mitigation and adaptation, advancing the development of climate-smart agriculture.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
Short summary
Short summary
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, Philippe Ciais, and Daniel S. Goll
EGUsphere, https://doi.org/10.5194/egusphere-2025-2545, https://doi.org/10.5194/egusphere-2025-2545, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Accurate estimates of global soil organic carbon (SOC) content and its spatial pattern are critical for future climate change mitigation. However, the most advanced mechanistic SOC models struggle to do this task. Here we apply multiple explainable machine learning methods to identify missing variables and misrepresented relationships between environmental factors and SOC in these models, offering new insights to guide model development for more reliable SOC predictions.
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, 17, 2713–2733, https://doi.org/10.5194/essd-17-2713-2025, https://doi.org/10.5194/essd-17-2713-2025, 2025
Short summary
Short summary
We have developed new maps that reveal 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 2500 gauges and a wealth of climate and environmental information. The maps are a critical step in understanding and predicting how carbon moves through our environment, hence making them a useful tool for tackling climate challenges.
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, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, 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, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025, https://doi.org/10.5194/essd-17-2507-2025, 2025
Short summary
Short summary
We present daily methane (CH4) fluxes of northern wetlands at 10 km resolution during 2016–2022 (WetCH4) derived from a novel machine learning framework. We estimated an average annual CH4 emission of 22.8 ± 2.4 Tg CH4 yr−1 (15.7–51.6 Tg CH4 yr−1). Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variation coming from Western Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Philippe Bousquet, Josep G. Canadell, Nick Davidson, Meng Ding, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Liangyun Liu, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, Xiao Zhang, and Michele Thieme
Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, https://doi.org/10.5194/essd-17-2277-2025, 2025
Short summary
Short summary
The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies – that is, the maximum extent – covers 18.2 × 106 km2, equivalent to 13.4 % of total global land area.
Hanyu Liu, Felix R. Vogel, Misa Ishizawa, Zhen Zhang, Benjamin Poulter, Doug E. J. Worthy, Leyang Feng, Anna L. Gagné-Landmann, Ao Chen, Ziting Huang, Dylan C. Gaeta, Joe R. Melton, Douglas Chan, Vineet Yadav, Deborah Huntzinger, and Scot M. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2025-2150, https://doi.org/10.5194/egusphere-2025-2150, 2025
Short summary
Short summary
We find that the state-of-the-art process-based methane flux models have both lower flux magnitude and reduced inter-model uncertainty compared to a previous model inter-comparison from over a decade ago. Despite these improvements, methane flux estimates from process-based models are still likely too high compared to atmospheric observations. We also find that models with simpler parameterizations often result in better agreement with atmospheric observations in high-latitude North America.
Min Feng, Joseph O. Sexton, Panshi Wang, Paul M. Montesano, Leonardo Calle, Nuno Carvalhais, Benjamin Poulter, Matthew J. Macander, Michael A. Wulder, Margaret Wooten, William Wagner, Akiko Elders, Saurabh Channan, and Christopher S. R. Neigh
EGUsphere, https://doi.org/10.5194/egusphere-2025-2268, https://doi.org/10.5194/egusphere-2025-2268, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
The boreal forest, warming fastest among forested biomes, shows a northward shift in tree cover. Using the longest, highest-resolution satellite maps, we found an 0.844 million km² increase in tree cover and a 0.45° northward shift from 1985–2020, especially in northern latitudes. Stable disturbance rates suggest climate-driven growth. Young forests' biomass may help reduce global CO2, despite uncertainties in carbon balance, disturbance, and respiration.
Konstantin Gregor, Benjamin F. Meyer, Tillmann Gaida, Victor Justo Vasquez, Karina Bett-Williams, Matthew Forrest, João P. Darela-Filho, Sam Rabin, Marcos Longo, Joe R. Melton, Johan Nord, Peter Anthoni, Vladislav Bastrikov, Thomas Colligan, Christine Delire, Michael C. Dietze, George Hurtt, Akihiko Ito, Lasse T. Keetz, Jürgen Knauer, Johannes Köster, Tzu-Shun Lin, Lei Ma, Marie Minvielle, Stefan Olin, Sebastian Ostberg, Hao Shi, Reiner Schnur, Urs Schönenberger, Qing Sun, Peter E. Thornton, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2025-1733, https://doi.org/10.5194/egusphere-2025-1733, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Geoscientific models are crucial for understanding Earth’s processes. However, they sometimes do not adhere to highest software quality standards, and scientific results are often hard to reproduce due to the complexity of the workflows. Here we gather the expertise of 20 modeling groups and software engineers to define best practices for making geoscientific models maintainable, usable, and reproducible. We conclude with an open-source example serving as a reference for modeling communities.
Martin Richard Willett, Melissa Brooks, Andrew Bushell, Paul Earnshaw, Samantha Smith, Lorenzo Tomassini, Martin Best, Ian Boutle, Jennifer Brooke, John M. Edwards, Kalli Furtado, Catherine Hardacre, Andrew J. Hartley, Alan Hewitt, Ben Johnson, Adrian Lock, Andy Malcolm, Jane Mulcahy, Eike Müller, Heather Rumbold, Gabriel G. Rooney, Alistair Sellar, Masashi Ujiie, Annelize van Niekerk, Andy Wiltshire, and Michael Whitall
EGUsphere, https://doi.org/10.5194/egusphere-2025-1829, https://doi.org/10.5194/egusphere-2025-1829, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application. We describe a recent iteration of these configurations, GA8GL9, which includes improvements to the represenation of convection and other physical processes. GA8GL9 is used for operational weather prediction in the UK and forms the basis for the next GA and GL configuration.
Tanguy Postic, François de Coligny, Isabelle Chuine, Louis Devresse, Daniel Berveiller, Hervé Cochard, Matthias Cuntz, Nicolas Delpierre, Émilie Joetzjer, Jean-Marc Limousin, Jean-Marc Ourcival, François Pimont, Julien Ruffault, Guillaume Simioni, Nicolas K. Martin-StPaul, and Xavier Morin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2110, https://doi.org/10.5194/egusphere-2025-2110, 2025
Short summary
Short summary
PHOREAU is a forest dynamic model that links plant traits with water use, growth, and climate responses to explore how species diversity affects productivity and resilience. Validated across European forests, PHOREAU simulates how tree communities function under drought and warming. Our findings support the use of trait-based modeling to guide forest adaptation strategies under future climate scenarios.
Benjamin C. Sapper, Sean Youn, Daven K. Henze, Manjula Canagaratna, Harald Stark, and Jose L. Jimenez
Geosci. Model Dev., 18, 2891–2919, https://doi.org/10.5194/gmd-18-2891-2025, https://doi.org/10.5194/gmd-18-2891-2025, 2025
Short summary
Short summary
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 error-weighted PMF that drastically reduces the computational costs of previously developed algorithms. We use this technique to deliver interpretable factors and solution diagnostics from an atmospheric chemistry dataset.
Cheng Gong, Yan Wang, Hanqin Tian, Sian Kou-Giesbrecht, Nicolas Vuichard, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2025-1416, https://doi.org/10.5194/egusphere-2025-1416, 2025
Short summary
Short summary
Our results showed substantially varied fertilizer-induced soil NOx emissions in 2019 from 0.84 to 2.2 Tg N yr-1 globally. Such variations further lead to 0.3 to 3.3 ppbv summertime ozone enhancement in agricultural hotspot regions and 7.1 ppbv to 16.6 ppbv reductions in global methane concentrations
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep 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, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. 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, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
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 synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress 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.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
Short summary
Short summary
The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-188, https://doi.org/10.5194/essd-2025-188, 2025
Preprint under review for ESSD
Short summary
Short summary
This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
Tea Thum, Tuuli Miinalainen, Outi Seppälä, Holly Croft, Cheryl Rogers, Ralf Staebler, Silvia Caldararu, and Sönke Zaehle
Biogeosciences, 22, 1781–1807, https://doi.org/10.5194/bg-22-1781-2025, https://doi.org/10.5194/bg-22-1781-2025, 2025
Short summary
Short summary
Climate change has the potential to influence the carbon sequestration potential of terrestrial ecosystems, and here the nitrogen cycle is also important. We used the terrestrial biosphere model QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) in a mixed deciduous forest in Canada. We investigated the usefulness of using the leaf area index and leaf chlorophyll content to improve the parameterization of the model. This work paves the way for using spaceborne observations in model parameterizations, also including information on the nitrogen cycle.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
Short summary
Short summary
We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Carlos A. Sierra, Ingrid Chanca, Meinrat Andreae, Alessandro Carioca de Araújo, Hella van Asperen, Lars Borchardt, Santiago Botía, Luiz Antonio Candido, Caio S. C. Correa, Cléo Quaresma Dias-Junior, Markus Eritt, Annica Fröhlich, Luciana V. Gatti, Marcus Guderle, Samuel Hammer, Martin Heimann, Viviana Horna, Armin Jordan, Steffen Knabe, Richard Kneißl, Jost Valentin Lavric, Ingeborg Levin, Kita Macario, Juliana Menger, Heiko Moossen, Carlos Alberto Quesada, Michael Rothe, Christian Rödenbeck, Yago Santos, Axel Steinhof, Bruno Takeshi, Susan Trumbore, and Sönke Zaehle
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-151, https://doi.org/10.5194/essd-2025-151, 2025
Preprint under review for ESSD
Short summary
Short summary
We present here a unique dataset of atmospheric observations of greenhouse gases and isotopes that provide key information on land-atmosphere interactions for the Amazon forests of central Brazil. The data show a relatively large level of variability, but also important trends in greenhouse gases, and signals from fires as well as seasonal biological activity.
Inês Vieira, Félicien Meunier, Maria Carolina Duran Rojas, Stephen Sitch, Flossie Brown, Giacomo Gerosa, Silvano Fares, Pascal Boeckx, Marijn Bauters, and Hans Verbeeck
EGUsphere, https://doi.org/10.5194/egusphere-2025-1375, https://doi.org/10.5194/egusphere-2025-1375, 2025
Short summary
Short summary
We used a computer model to study how ozone pollution reduces plant growth in six European forests, from Finland to Italy. Combining field data and simulations, we found that ozone can lower carbon uptake by up to 6 % each year, especially in Mediterranean areas. Our study shows that local climate and forest type influence ozone damage and highlights the need to include ozone effects in forest and climate models.
Libo Wang, Lawrence Mudryk, Joe R. Melton, Colleen Mortimer, Jason Cole, Gesa Meyer, Paul Bartlett, and Mickaël Lalande
EGUsphere, https://doi.org/10.5194/egusphere-2025-1264, https://doi.org/10.5194/egusphere-2025-1264, 2025
Short summary
Short summary
This study shows that an alternate snow cover fraction (SCF) parameterization significantly improves SCF simulated in the CLASSIC model in mountainous areas for all three choices of meteorological datasets. Annual mean bias, unbiased root mean squared area, and correlation improve by 75 %, 32 %, and 7 % when evaluated with MODIS SCF observations over the Northern Hemisphere. We also link relative biases in the meteorological forcing data to differences in simulated snow water equivalent and SCF.
Mathew Williams, David T. Milodowski, T. Luke Smallman, Kyle G. Dexter, Gabi C. Hegerl, Iain M. McNicol, Michael O'Sullivan, Carla M. Roesch, Casey M. Ryan, Stephen Sitch, and Aude Valade
Biogeosciences, 22, 1597–1614, https://doi.org/10.5194/bg-22-1597-2025, https://doi.org/10.5194/bg-22-1597-2025, 2025
Short summary
Short summary
Southern African woodlands are important in both regional and global carbon cycles. A new carbon analysis created by combining satellite data with ecosystem modelling shows that the region has a neutral C balance overall but with important spatial variations. Patterns of biomass and C balance across the region are the outcome of climate controls on production and vegetation–fire interactions, which determine the mortality of vegetation and spatial variations in vegetation function.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
Short summary
Short summary
This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Tomohiro Hajima, Michio Kawamiya, Akihiko Ito, Kaoru Tachiiri, Chris D. Jones, Vivek Arora, Victor Brovkin, Roland Séférian, Spencer Liddicoat, Pierre Friedlingstein, and Elena Shevliakova
Biogeosciences, 22, 1447–1473, https://doi.org/10.5194/bg-22-1447-2025, https://doi.org/10.5194/bg-22-1447-2025, 2025
Short summary
Short summary
This study analyzes atmospheric CO2 concentrations and global carbon budgets simulated by multiple Earth system models, using several types of simulations (CO2 concentration- and emission-driven experiments). We successfully identified problems with regard to the global carbon budget in each model. We also found urgent issues with regard to land use change CO2 emissions that should be solved in the latest generation of models.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
Short summary
Short summary
We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, 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, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets 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 (1750–2024). 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.
Beata Opacka, Trissevgeni Stavrakou, Jean-François Müller, Isabelle De Smedt, Jos van Geffen, Eloise A. Marais, Rebekah P. Horner, Dylan B. Millet, Kelly C. Wells, and Alex B. Guenther
Atmos. Chem. Phys., 25, 2863–2894, https://doi.org/10.5194/acp-25-2863-2025, https://doi.org/10.5194/acp-25-2863-2025, 2025
Short summary
Short summary
Vegetation releases biogenic volatile organic compounds, while soils and lightning contribute to the natural emissions of nitrogen oxides into the atmosphere. These gases interact in complex ways. Using satellite data and models, we developed a new method to simultaneously optimize these natural emissions over Africa in 2019. Our approach resulted in an increase in natural emissions, supported by independent data indicating that current estimates are underestimated.
Hemraj Bhattarai, Maria Val Martin, Stephen Sitch, David H. Y. Yung, and Amos P. K. Tai
EGUsphere, https://doi.org/10.5194/egusphere-2025-804, https://doi.org/10.5194/egusphere-2025-804, 2025
Short summary
Short summary
Wildfires are becoming more frequent and severe due to climate change, posing various risks. We explore how future climate conditions will influence global wildfire activity and carbon emissions by 2100. Using advanced computer modeling, we found that while some regions remain stable, boreal forests will see a major rise in burned area and emissions. These changes are driven by drier conditions and increased vegetation growth, highlighting the urgent need for better fire management strategies.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
Short summary
Short summary
The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Kelley C. Wells, Dylan B. Millet, Jared F. Brewer, Vivienne H. Payne, Karen E. 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
Atmos. Meas. Tech., 18, 695–716, https://doi.org/10.5194/amt-18-695-2025, https://doi.org/10.5194/amt-18-695-2025, 2025
Short summary
Short summary
Atmospheric volatile organic compounds (VOCs) affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new decadal (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.
Jeongmin Yun, Junjie Liu, Brendan Byrne, Brad Weir, Lesley E. Ott, Kathryn McKain, Bianca C. Baier, Luciana V. Gatti, and Sebastien C. Biraud
Atmos. Chem. Phys., 25, 1725–1748, https://doi.org/10.5194/acp-25-1725-2025, https://doi.org/10.5194/acp-25-1725-2025, 2025
Short summary
Short summary
This study quantifies errors in regional net surface–atmosphere CO2 flux estimates from an inverse model ensemble using airborne CO2 measurements. Our results show that flux error estimates based on observations significantly exceed those computed from the ensemble spread of flux estimates in regions with high fossil fuel emissions. This finding suggests the presence of systematic biases in the inversion estimates, associated with errors in the fossil fuel emissions common to all models.
Detlef van Vuuren, Brian O'Neill, Claudia Tebaldi, Louise Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Benjamin Sanderson, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh Fall, Katja Frieler, Matthew Gidden, Laila Gohar, Andrew Jones, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camila Mathison, Shahbaz Mehmood, Luciana Prado, Qiang Zhang, Steven Rose, Alexander Ruane, Carl-Friederich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha Vishwanathan, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3765, https://doi.org/10.5194/egusphere-2024-3765, 2025
Short summary
Short summary
We propose a set of six plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Daniele Peano, Deborah Hemming, Christine Delire, Yuanchao Fan, Hanna Lee, Stefano Materia, Julia E. M .S. Nabel, Taejin Park, David Wårlind, Andy Wiltshire, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2024-4114, https://doi.org/10.5194/egusphere-2024-4114, 2025
Short summary
Short summary
Earth System Models are the principal tools for scientists to study past, present, and future climate changes. This work investigates the ability of a set of them to represent the observed changes in vegetation, which are vital to estimating the impact of future climate mitigation and adaptation strategies. This study highlights the main limitations in correctly representing vegetation variability. These tools still need further development to improve our understanding of future changes.
Binyuan Xu, Hanqin Tian, Shufen Pan, Xiaoyong Li, Ran Meng, Óscar Melo, Anne McDonald, María de los Ángeles Picone, Xiao-Peng Song, Edson Severnini, Katharine G. Young, and Feng Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-527, https://doi.org/10.5194/essd-2024-527, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
This study focuses on land use change in South America, reconstructing the historical dynamics of four major crops (soybean, maize, wheat, and rice) from 1950 to 2020 by integrating multiple data sources. The results reveal a significant expansion in cropland, particularly for soybean, leading to a substantial reduction in natural vegetation such as forests and grasslands. The datasets can be used to assess the impacts of cropland expansion on carbon and nitrogen cycles in South America.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Müller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul A. Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
Biogeosciences, 22, 323–340, https://doi.org/10.5194/bg-22-323-2025, https://doi.org/10.5194/bg-22-323-2025, 2025
Short summary
Short summary
Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in northern Europe using ecosystem models, atmospheric inversions, and upscaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions, and upscaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
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 H. 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, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
Short summary
Short summary
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 yr-1 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.
Fortunat Joos, Sebastian Lienert, and Sönke Zaehle
Biogeosciences, 22, 19–39, https://doi.org/10.5194/bg-22-19-2025, https://doi.org/10.5194/bg-22-19-2025, 2025
Short summary
Short summary
How plants regulate their exchange of CO2 and water with the atmosphere under global warming is critical for their carbon uptake and their cooling influence. We analyze the isotope ratio of atmospheric CO2 and detect no significant decadal trends in the seasonal cycle amplitude. The data are consistent with the regulation towards leaf CO2 and intrinsic water use efficiency growing proportionally to atmospheric CO2, in contrast to recent suggestions of downregulation of CO2 and water fluxes.
Yona Silvy, Thomas L. Frölicher, Jens Terhaar, Fortunat Joos, Friedrich A. Burger, Fabrice Lacroix, Myles Allen, Raffaele Bernardello, 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
Earth Syst. Dynam., 15, 1591–1628, https://doi.org/10.5194/esd-15-1591-2024, https://doi.org/10.5194/esd-15-1591-2024, 2024
Short summary
Short summary
The adaptive emission reduction approach is applied with Earth system models to generate temperature stabilization simulations. These simulations provide compatible emission pathways and budgets for a given warming level, uncovering uncertainty ranges previously missing in the Coupled Model Intercomparison Project scenarios. These target-based emission-driven simulations offer a more coherent assessment across models for studying both the carbon cycle and its impacts under climate stabilization.
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 17, 8853–8872, https://doi.org/10.5194/gmd-17-8853-2024, https://doi.org/10.5194/gmd-17-8853-2024, 2024
Short summary
Short summary
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.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024, https://doi.org/10.5194/bg-21-5321-2024, 2024
Short summary
Short summary
This study investigates present-day carbon cycle variables in CMIP5 and CMIP6 simulations. Overall, CMIP6 models perform better but also show many remaining biases. A significant improvement in the simulation of photosynthesis in models with a nitrogen cycle is found, with only small differences between emission- and concentration-based simulations. Thus, we recommend using emission-driven simulations in CMIP7 by default and including the nitrogen cycle in all future carbon cycle models.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Deepangsu Chatterjee, Randall V. Martin, Chi Li, Dandan Zhang, Haihui Zhu, Daven K. Henze, James H. Crawford, Ronald C. Cohen, Lok N. Lamsal, and Alexander M. Cede
Atmos. Chem. Phys., 24, 12687–12706, https://doi.org/10.5194/acp-24-12687-2024, https://doi.org/10.5194/acp-24-12687-2024, 2024
Short summary
Short summary
We investigate the hourly variation of NO2 columns and surface concentrations by applying the GEOS-Chem model to interpret aircraft and ground-based measurements over the US and Pandora sun photometer measurements over the US, Europe, and Asia. Corrections to the Pandora columns and finer model resolution improve the modeled representation of the summertime hourly variation of total NO2 columns to explain the weaker hourly variation in NO2 columns than at the surface.
Flossie Brown, Gerd Folberth, Stephen Sitch, Paulo Artaxo, Marijn Bauters, Pascal Boeckx, Alexander W. Cheesman, Matteo Detto, Ninong Komala, Luciana Rizzo, Nestor Rojas, Ines dos Santos Vieira, Steven Turnock, Hans Verbeeck, and Alfonso Zambrano
Atmos. Chem. Phys., 24, 12537–12555, https://doi.org/10.5194/acp-24-12537-2024, https://doi.org/10.5194/acp-24-12537-2024, 2024
Short summary
Short summary
Ozone is a pollutant that is detrimental to human and plant health. Ozone monitoring sites in the tropics are limited, so models are often used to understand ozone exposure. We use measurements from the tropics to evaluate ozone from the UK Earth system model, UKESM1. UKESM1 is able to capture the pattern of ozone in the tropics, except in southeast Asia, although it systematically overestimates it at all sites. This work highlights that UKESM1 can capture seasonal and hourly variability.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
Short summary
Short summary
This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Gabriela Sophia, Silvia Caldararu, Benjamin David Stocker, and Sönke Zaehle
Biogeosciences, 21, 4169–4193, https://doi.org/10.5194/bg-21-4169-2024, https://doi.org/10.5194/bg-21-4169-2024, 2024
Short summary
Short summary
Through an extensive global dataset of leaf nutrient resorption and a multifactorial analysis, we show that the majority of spatial variation in nutrient resorption may be driven by leaf habit and type, with thicker, longer-lived leaves having lower resorption efficiencies. Climate, soil fertility and soil-related factors emerge as strong drivers with an additional effect on its role. These results are essential for comprehending plant nutrient status, plant productivity and nutrient cycling.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
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
Short summary
Short summary
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.
Michael Stanley, Mikael Kuusela, Brendan Byrne, and Junjie Liu
Atmos. Chem. Phys., 24, 9419–9433, https://doi.org/10.5194/acp-24-9419-2024, https://doi.org/10.5194/acp-24-9419-2024, 2024
Short summary
Short summary
To serve the uncertainty quantification (UQ) needs of 4D-Var data assimilation (DA) practitioners, we describe and justify a UQ algorithm from carbon flux inversion and incorporate its sampling uncertainty into the final reported UQ. The algorithm is mathematically proved, and its performance is shown for a carbon flux observing system simulation experiment. These results legitimize and generalize this algorithm's current use and make available this effective algorithm to new DA domains.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
Short summary
Short summary
Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Dieu Anh Tran, Christoph Gerbig, Christian Rödenbeck, and Sönke Zaehle
Atmos. Chem. Phys., 24, 8413–8440, https://doi.org/10.5194/acp-24-8413-2024, https://doi.org/10.5194/acp-24-8413-2024, 2024
Short summary
Short summary
The analysis of the atmospheric CO2 record from the Zotino Tall Tower Observatory (ZOTTO) in central Siberia shows significant increases in the length and amplitude of the CO2 uptake and release in the 2010–2021 period. The trend shows a stronger increase in carbon release amplitude compared to the uptake, suggesting that, despite enhanced growing season uptake, during this period climate warming did not elevate the annual net CO2 uptake as cold-season respirations also responded to the warming.
Zhendong Lu, Jun Wang, Yi Wang, Daven K. Henze, Xi Chen, Tong Sha, and Kang Sun
Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
Short summary
Short summary
In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Preprint archived
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Preprint archived
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Ahlström, A., Raupach, M. R., Schurgers, G., Smith, B., Arneth, A., Jung, M., Reichstein, M., Canadell, J. G., Friedlingstein, P., Jain, A. K., and Kato, E.:
The dominant role of semi-arid ecosystems in the trend and variability of the
land CO2 sink, Science, 348, 895–899, https://doi.org/10.1126/science.aaa1668, 2015. a
Baker, D.: 10 second averaged OCO-2 XCO2 retrievals, version nine [data set], available at: ftp://ftp.cira.colostate.edu/ftp/BAKER (last access: 29 October 2020), 2019. a
Baker, I. T., Prihodko, L., Denning, A. S., Goulden, M., Miller, S., and Da
Rocha, H. R.: Seasonal drought stress in the amazon: Reconciling models and
observations, J. Geophys. Res.-Biogeosci., 114, 1–10,
https://doi.org/10.1029/2007JG000644, 2008. a
Baldocchi, D.: “Breathing” of the Terrestrial Biosphere: Lessons Learned
from a Global Network of Carbon Dioxide Flux Measurement Systems, Aust. J.
Bot., 56, 1–26, 2008. a
Baldocchi, D., Chu, H., and Reichstein, M.: Inter-annual variability of net
and gross ecosystem carbon fluxes: A review, Agric. For. Meteorol., 249,
520–533, https://doi.org/10.1016/j.agrformet.2017.05.015, 2017. a, b, c, d
Bastos, A., Friedlingstein, P., Sitch, S., Chen, C., Mialon, A., Wigneron, J. P., Arora, V. K., Briggs, P. R., Canadell, J. G., Ciais, P., and Chevallier, F.:
Impact of the 2015/2016 El Niño on the terrestrial carbon cycle
constrained by bottom-up and top-down approaches, Philos. T. Roy. Soc. B, 373, 20170304,
https://doi.org/10.1098/rstb.2017.0304, 2018. a
Byrne, B., Liu, J., Lee, M., Baker, I., Bowman, K. W., Deutscher, N. M., Feist,
D. G., Griffith, D. W., Iraci, L. T., Kiel, M., Kimball, J. S., Miller,
C. E., Morino, I., Parazoo, N. C., Petri, C., Roehl, C. M., Sha, M. K.,
Strong, K., Velazco, V. A., Wennberg, P. O., and Wunch, D.: Improved
Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining
Surface-Based and Space-Based Atmospheric CO2 Measurements, J. Geophys.
Res. Atmos., 125, https://doi.org/10.1029/2019JD032029, 2020a. a
Byrne, B., Liu, J., Bloom, A. A., Bowman, K. W., Butterfield, Z., Joiner, J.,
Keenan, T. F., Keppel‐Aleks, G., Parazoo, N. C., and Yin, Y.: Contrasting
regional carbon cycle responses to seasonal climate anomalies across the
east‐west divide of temperate North America, Global Biogeochem. Cy., 34, 1–26, https://doi.org/10.1029/2020gb006598, 2020b. a, b
Carroll, D., Menemenlis, D., Adkins, J. F., Bowman, K. W., Brix, H.,
Dutkiewicz, S., Fenty, I., Gierach, M. M., Hill, C., Jahn, O.,
Landschützer, P., Lauderdale, J. M., Liu, J., Manizza, M., Naviaux,
J. D., Rödenbeck, C., Schimel, D. S., Van der Stocken, T., and Zhang,
H.: The ECCO‐Darwin Data‐Assimilative Global Ocean Biogeochemistry
Model: Estimates of Seasonal to Multidecadal Surface Ocean p CO2 and
Air‐Sea CO2 Flux , J. Adv. Model. Earth Syst., 12, 1–28,
https://doi.org/10.1029/2019ms001888, 2020. a
Chen, N., Zhu, J., Zhang, Y., Liu, Y., Li, J., Zu, J., and Huang, K.:
Nonlinear response of ecosystem respiration to multiple levels of
temperature increases, Ecol. Evol., 9, 925–937, https://doi.org/10.1002/ece3.4658,
2019. a
Chevallier, F., Bréon, F.-M., and Rayner, P. J.: Contribution of the
Orbiting Carbon Observatory to the estimation of CO2 sources and sinks:
Theoretical study in a variational data assimilation framework, J. Geophys. Res.-Atmos., 112, https://doi.org/10.1029/2006JD007375, 2007. a, b
Chevallier, F., Palmer, P. I., Feng, L., Boesch, H., O'Dell, C. W., and
Philippe, B.: Toward robust and consistent regional CO2 flux estimates
from in situ and spaceborne measurements of atmospheric CO2, Geophys.
Res. Lett., 31, 1–8, https://doi.org/10.1002/2013GL058772.Received, 2014. a, b
Cooperative Global Atmospheric Data Integration Project: Multi-laboratory compilation of atmospheric carbon dioxide data for the period 1957–2018; obspack_co2_1_GLOBALVIEWplus_v5.0_2019_08_12; NOAA Earth System Research Laboratory, Global Monitoring Division [data set], available at: http://dx.doi.org/10.25925/20190812 (last access: 20 September 2020), 2019. a
Crisp, D.: Measuring atmospheric carbon dioxide from space: The GOSAT and
OCO-2 missions, Opt. InfoBase Conf. Pap., 2, https://doi.org/10.1364/e2.2011.ewc6,
2015. a
Crowell, S., Baker, D., Schuh, A., Basu, S., Jacobson, A. R., Chevallier, F., Liu, J., Deng, F., Feng, L., McKain, K., Chatterjee, A., Miller, J. B., Stephens, B. B., Eldering, A., Crisp, D., Schimel, D., Nassar, R., O'Dell, C. W., Oda, T., Sweeney, C., Palmer, P. I., and Jones, D. B. A.: The 2015–2016 carbon cycle as seen from OCO-2 and the global in situ network, Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, 2019. a, b, c
Dargaville, R. J., Heimann, M., McGuire, A. D., Prentice, I. C., Kicklighter,
D. W., Joos, F., Clein, J. S., Esser, G., Foley, J., Kaplan, J., Meier,
R. A., Melillo, J. M., Moore, B., Ramankutty, N., Reichenau, T., Schloss, A.,
Sitch, S., Tian, H., Williams, L. J., and Wittenberg, U.: Evaluation of
terrestrial carbon cycle models with atmospheric CO2 measurements: Results
from transient simulations considering increasing CO2, climate, and
land-use effects, Global Biogeochem. Cy., 16, 39-1, https://doi.org/10.1029/2001gb001426,
2002. a
Dayalu, A., Munger, J. W., Wofsy, S. C., Wang, Y., Nehrkorn, T., Zhao, Y., McElroy, M. B., Nielsen, C. P., and Luus, K.: Assessing biotic contributions to CO2 fluxes in northern China using the Vegetation, Photosynthesis and Respiration Model (VPRM-CHINA) and observations from 2005 to 2009, Biogeosciences, 15, 6713–6729, https://doi.org/10.5194/bg-15-6713-2018, 2018. a
Doughty, C. E. and Goulden, M. L.: Seasonal patterns of tropical forest leaf
area index and CO2 exchange, J. Geophys. Res.-Biogeo., 113, https://doi.org/10.1029/2007JG000590, 2008. a
Eldering, A., O'Dell, C. W., Wennberg, P. O., Crisp, D., Gunson, M. R., Viatte, C., Avis, C., Braverman, A., Castano, R., Chang, A., Chapsky, L., Cheng, C., Connor, B., Dang, L., Doran, G., Fisher, B., Frankenberg, C., Fu, D., Granat, R., Hobbs, J., Lee, R. A. M., Mandrake, L., McDuffie, J., Miller, C. E., Myers, V., Natraj, V., O'Brien, D., Osterman, G. B., Oyafuso, F., Payne, V. H., Pollock, H. R., Polonsky, I., Roehl, C. M., Rosenberg, R., Schwandner, F., Smyth, M., Tang, V., Taylor, T. E., To, C., Wunch, D., and Yoshimizu, J.: The Orbiting Carbon Observatory-2: first 18 months of science data products, Atmos. Meas. Tech., 10, 549–563, https://doi.org/10.5194/amt-10-549-2017, 2017. a, b
Eldering, A., Taylor, T. E., O'Dell, C. W., and Pavlick, R.: The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data, Atmos. Meas. Tech., 12, 2341–2370, https://doi.org/10.5194/amt-12-2341-2019, 2019. a
Fang, Y., Michalak, A. M., Shiga, Y. P., and Yadav, V.: Using atmospheric observations to evaluate the spatiotemporal variability of CO2 fluxes simulated by terrestrial biospheric models, Biogeosciences, 11, 6985–6997, https://doi.org/10.5194/bg-11-6985-2014, 2014. a
Feng, L., Palmer, P. I., Parker, R. J., Deutscher, N. M., Feist, D. G., Kivi, R., Morino, I., and Sussmann, R.: Estimates of European uptake of CO2 inferred from GOSAT XCO2 retrievals: sensitivity to measurement bias inside and outside Europe, Atmos. Chem. Phys., 16, 1289–1302, https://doi.org/10.5194/acp-16-1289-2016, 2016. a
Forkel, M., Carvalhais, N., Rödenbeck, C., Keeling, R., Heimann, M.,
Thonicke, K., Zaehle, S., and Reichstein, M.: Enhanced seasonal CO2
exchange caused by amplified plant productivity in northern ecosystems,
Science, 351, 696–699, https://doi.org/10.1126/science.aac4971, 2016. a
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V., Cadule, P., Doney, S., Eby, M., Fung, I., and Bala, G.: Climate–Carbon Cycle
Feedback Analysis Results from the C4MIP, J. Climate, 19, 3337–3353, https://doi.org/10.1175/JCLI3800.1, 2006. a
Friedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Hauck, J., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., Le Quéré, C., Bakker, D. C. E., Canadell, J. G., Ciais, P., Jackson, R. B., Anthoni, P., Barbero, L., Bastos, A., Bastrikov, V., Becker, M., Bopp, L., Buitenhuis, E., Chandra, N., Chevallier, F., Chini, L. P., Currie, K. I., Feely, R. A., Gehlen, M., Gilfillan, D., Gkritzalis, T., Goll, D. S., Gruber, N., Gutekunst, S., Harris, I., Haverd, V., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Joetzjer, E., Kaplan, J. O., Kato, E., Klein Goldewijk, K., Korsbakken, J. I., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Marland, G., McGuire, P. C., Melton, J. R., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., Neill, C., Omar, A. M., Ono, T., Peregon, A., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Séférian, R., Schwinger, J., Smith, N., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., van der Werf, G. R., Wiltshire, A. J., and Zaehle, S.: Global Carbon Budget 2019, Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, 2019. a
Gatti, L. V., Gloor, M., Miller, J. B., Doughty, C. E., Malhi, Y., Domingues,
L. G., Basso, L. S., Martinewski, A., Correia, C. S., Borges, V. F., Freitas,
S., Braz, R., Anderson, L. O., Rocha, H., Grace, J., Phillips, O. L., and
Lloyd, J.: Drought sensitivity of Amazonian carbon balance revealed by
atmospheric measurements, Nature, 506, 76–80, https://doi.org/10.1038/nature12957,
2014. a
Gelaro, R., McCarty, W., Suárez, M.J., Todling, R., Molod, A., Takacs, L., Randles, C.A., Darmenov, A., Bosilovich, M.G., Reichle, R., and Wargan, K.: The
modern-era retrospective analysis for research and applications, version 2
(MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. a
Gourdji, S. M., Mueller, K. L., Schaefer, K., and Michalak, A. M.: Global
monthly averaged CO2 fluxes recovered using a geostatistical inverse
modeling approach: 2. Results including auxiliary environmental data, J.
Geophys. Res., 113, 1–15, https://doi.org/10.1029/2007jd009733, 2008. a, b, c
Gourdji, S. M., Hirsch, A. I., Mueller, K. L., Yadav, V., Andrews, A. E., and Michalak, A. M.: Regional-scale geostatistical inverse modeling of North American CO2 fluxes: a synthetic data study, Atmos. Chem. Phys., 10, 6151–6167, https://doi.org/10.5194/acp-10-6151-2010, 2010. a
Gourdji, S. M., Mueller, K. L., Yadav, V., Huntzinger, D. N., Andrews, A. E., Trudeau, M., Petron, G., Nehrkorn, T., Eluszkiewicz, J., Henderson, J., Wen, D., Lin, J., Fischer, M., Sweeney, C., and Michalak, A. M.: North American CO2 exchange: inter-comparison of modeled estimates with results from a fine-scale atmospheric inversion, Biogeosciences, 9, 457–475, https://doi.org/10.5194/bg-9-457-2012, 2012. a, b, c, d, e, f
Harris, I. C.: CRU JRA v1. 1: A forcings dataset of gridded land surface blend
of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.
1901-Dec. 2017, University of East Anglia Climatic Research Unit, Centre for
Environmental Data Analysis, https://doi.org/10.5285/13f3635174794bb98cf8ac4b0ee8f4ed,
2019. a
Heskel, M. A., O'Sullivan, O. S., Reich, P. B., Tjoelker, M. G., Weerasinghe,
L. K., Penillard, A., Egerton, J. J., Creek, D., Bloomfield, K. J., Xiang,
J., Sinca, F., Stangl, Z. R., Martinez-De La Torre, A., Griffin, K. L.,
Huntingford, C., Hurry, V., Meir, P., Turnbull, M. H., and Atkin, O. K.:
Convergence in the temperature response of leaf respiration across biomes
and plant functional types, P. Natl. Acad. Sci. USA, 113,
3832–3837, https://doi.org/10.1073/pnas.1520282113, 2016. a
Hu, L., Andrews, A. E., Thoning, K. W., Sweeney, C., Miller, J. B., Michalak,
A. M., Dlugokencky, E., Tans, P. P., Shiga, Y. P., Mountain, M., Nehrkorn,
T., Montzka, S. A., McKain, K., Kofler, J., Trudeau, M., Michel, S. E.,
Biraud, S. C., Fischer, M. L., Worthy, D. E., Vaughn, B. H., White, J. W.,
Yadav, V., Basu, S., and Van Der Velde, I. R.: Enhanced North American
carbon uptake associated with El Niño, Sci. Adv., 5, 1–11,
https://doi.org/10.1126/sciadv.aaw0076, 2019. a
Huntzinger, D. N., Gourdji, S. M., Mueller, K. L., and Michalak, A. M.: The
utility of continuous atmospheric measurements for identifying biospheric
CO2 flux variability, J. Geophys. Res.-Atmos., 116, 1–14,
https://doi.org/10.1029/2010JD015048, 2011. a, b
Huntzinger, D. N., Michalak, A. M., Schwalm, C., Ciais, P., King, A. W., Fang,
Y., Schaefer, K., Wei, Y., Cook, R. B., Fisher, J. B., Hayes, D., Huang, M.,
Ito, A., Jain, A. K., Lei, H., Lu, C., Maignan, F., Mao, J., Parazoo, N.,
Peng, S., Poulter, B., Ricciuto, D., Shi, X., Tian, H., Wang, W., Zeng, N.,
and Zhao, F.: Uncertainty in the response of terrestrial carbon sink to
environmental drivers undermines carbon-climate feedback predictions, Sci.
Rep., 7, 1–8, https://doi.org/10.1038/s41598-017-03818-2, 2017. a
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S.,
Ahlström, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein,
P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B.,
Raduly, B., Rödenbeck, C., Tramontana, G., Viovy, N., Wang, Y. P.,
Weber, U., Zaehle, S., and Zeng, N.: Compensatory water effects link yearly
global land CO2 sink changes to temperature, Nature, 541, 516–520,
https://doi.org/10.1038/nature20780, 2017. a
King, A. W., Andres, R. J., Davis, K. J., Hafer, M., Hayes, D. J., Huntzinger, D. N., de Jong, B., Kurz, W. A., McGuire, A. D., Vargas, R., Wei, Y., West, T. O., and Woodall, C. W.: North America's net terrestrial CO2 exchange with the atmosphere 1990–2009, Biogeosciences, 12, 399–414, https://doi.org/10.5194/bg-12-399-2015, 2015. a, b
Kitanidis, P. K.: Parameter Uncertainty in Estimation of Spatial Functions:
Bayesian Analysis, Water Resour. Res., 22, 499–507,
https://doi.org/10.1029/WR022i004p00499, 1986. a
Kuze, A., Suto, H., Shiomi, K., Nakajima, M., and Hamazaki, T.: On-orbit
performance and level 1 data processing of TANSO-FTS and CAI on GOSAT,
Sensors, Syst. Next-Generation Satell. XIII, 7474, 74740I,
https://doi.org/10.1117/12.830152, 2009. a
Le Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Hauck, J., Pongratz, J., Pickers, P. A., Korsbakken, J. I., Peters, G. P., Canadell, J. G., Arneth, A., Arora, V. K., Barbero, L., Bastos, A., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Doney, S. C., Gkritzalis, T., Goll, D. S., Harris, I., Haverd, V., Hoffman, F. M., Hoppema, M., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Johannessen, T., Jones, C. D., Kato, E., Keeling, R. F., Goldewijk, K. K., Landschützer, P., Lefèvre, N., Lienert, S., Liu, Z., Lombardozzi, D., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S., Neill, C., Olsen, A., Ono, T., Patra, P., Peregon, A., Peters, W., Peylin, P., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rocher, M., Rödenbeck, C., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Steinhoff, T., Sutton, A., Tans, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Wright, R., Zaehle, S., and Zheng, B.: Global Carbon Budget 2018, Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, 2018. a
Liu, J., Bowman, K. W., Schimel, D. S., Parazoo, N. C., Jiang, Z., Lee, M.,
Bloom, A. A., Wunch, D., Frankenberg, C., Sun, Y., O'Dell, C. W., Gurney,
K. R., Menemenlis, D., Gierach, M., Crisp, D., and Eldering, A.: Contrasting
carbon cycle responses of the tropical continents to the 2015–2016 El
Niño, Science, 358, https://doi.org/10.1126/science.aam5690, 2017. a, b, c
Luus, K. A., Commane, R., Parazoo, N. C., Benmergui, J., Euskirchen, E. S.,
Frankenberg, C., Joiner, J., Lindaas, J., Miller, C. E., Oechel, W. C., Zona,
D., Wofsy, S., and Lin, J. C.: Tundra photosynthesis captured by
satellite-observed solar-induced chlorophyll fluorescence, Geophys. Res.
Lett., 44, 1564–1573, https://doi.org/10.1002/2016GL070842, 2017. a
Mahadevan, P., Wofsy, S. C., Matross, D. M., Xiao, X., Dunn, A. L., Lin, J. C.,
Gerbig, C., Munger, J. W., Chow, V. Y., and Gottlieb, E. W.: A
satellite-based biosphere parameterization for net ecosystem CO2 exchange:
Vegetation Photosynthesis and Respiration Model (VPRM), Global Biogeochem. Cy., 22, https://doi.org/10.1029/2006GB002735, 2008. a
Michalak, A. M., Bruhwiler, L., and Tans, P. P.: A geostatistical approach to
surface flux estimation of atmospheric trace gases, J. Geophys. Res.-Atmos., 109, 1–19, https://doi.org/10.1029/2003JD004422, 2004. a
Miller, S. M., Wofsy, S. C., Michalak, A. M., Kort, E. A., Andrews, A. E., Biraud, S. C., Dlugokencky, E. J., Eluszkiewicz, J., Fischer, M. L., Janssens-Maenhout, G., and Miller, B. R.: Anthropogenic emissions of methane in the
United States, P. Natl. Acad. Sci. USA, 110,
20018–20022, https://doi.org/10.1073/pnas.1314392110, 2013. a
Miller, S. M., Saibaba, A. K., Trudeau, M. E., Mountain, M. E., and Andrews, A. E.: Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite, Geosci. Model Dev., 13, 1771–1785, https://doi.org/10.5194/gmd-13-1771-2020, 2020. a, b
Mueller, K. L., Gourdji, S. M., and Michalak, A. M.: Global monthly averaged
CO2 fluxes recovered using a geostatistical inverse modeling approach: 1.
Results using atmospheric measurements, J. Geophys. Res.-Atmos., 113, 1–15,
https://doi.org/10.1029/2007JD009734, 2008. a
Mueller, K. L., Yadav, V., Curtis, P. S., Vogel, C., and Michalak, A. M.:
Attributing the variability of eddy-covariance CO2 flux measurements
across temporal scales using geostatistical regression for a mixed northern
hardwood forest, Global Biogeochem. Cy., 24, https://doi.org/10.1029/2009GB003642,
2010. a
Nakajima, M., Kuze, A., and Suto, H.: The current status of GOSAT and the
concept of GOSAT-2, International Society for Optics and Photonics, 8533,
853306, https://doi.org/10.1117/12.974954, 2012. a
OCO-2 MIP team: OCO-2 v9 inverse model inter-comparison project [data set], available at: https://www.esrl.noaa.gov/gmd/ccgg/OCO2_v9mip, last access: 9 November 2020. a
Oda, T., Maksyutov, S., and Andres, R. J.: The Open-source Data Inventory for Anthropogenic CO2, version 2016 (ODIAC2016): a global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions, Earth Syst. Sci. Data, 10, 87–107, https://doi.org/10.5194/essd-10-87-2018, 2018. a
O'Dell, C. W., Eldering, A., Wennberg, P. O., Crisp, D., Gunson, M. R., Fisher, B., Frankenberg, C., Kiel, M., Lindqvist, H., Mandrake, L., Merrelli, A., Natraj, V., Nelson, R. R., Osterman, G. B., Payne, V. H., Taylor, T. E., Wunch, D., Drouin, B. J., Oyafuso, F., Chang, A., McDuffie, J., Smyth, M., Baker, D. F., Basu, S., Chevallier, F., Crowell, S. M. R., Feng, L., Palmer, P. I., Dubey, M., García, O. E., Griffith, D. W. T., Hase, F., Iraci, L. T., Kivi, R., Morino, I., Notholt, J., Ohyama, H., Petri, C., Roehl, C. M., Sha, M. K., Strong, K., Sussmann, R., Te, Y., Uchino, O., and Velazco, V. A.: Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm, Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, 2018. a, b
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V., Underwood, E. C., D'amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., and Loucks, C. J.: Terrestrial Ecoregions of the World: A New Map of Life on
EarthA new global map of terrestrial ecoregions provides an innovative tool
for conserving biodiversity, BioScience, 51, 933–938,
https://doi.org/10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2, 2001. a
Palmer, P. I., Feng, L., Baker, D., Chevallier, F., Bösch, H., and
Somkuti, P.: Net carbon emissions from African biosphere dominate
pan-tropical atmospheric CO2 signal, Nat. Commun., 10, 3344,
https://doi.org/10.1038/s41467-019-11097-w, 2019. a
Pan, S., Pan, N., Tian, H., Friedlingstein, P., Sitch, S., Shi, H., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., Lienert, S., Lombardozzi, D., Nabel, J. E. M. S., Ottlé, C., Poulter, B., Zaehle, S., and Running, S. W.: Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling, Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, 2020. a
Peng, S., Ciais, P., Chevallier, F., Peylin, P., Cadule, P., Sitch, S., Piao,
S., Ahlström, A., Huntingford, C., Levy, P., Li, X., Liu, Y., Lomas,
M., Poulter, B., Viovy, N., Wang, T., and Wang, X.: Global Biogeochemical
Cycles simulated by terrestrial ecosystem models, Global Biogeochem. Cy.,
29, 46–64, https://doi.org/10.1002/2014GB004931, 2014. a
Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X.,
Ahlström, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C.,
Jung, M., Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M. R., Lu, M., Luo,
Y., Ma, Y., Myneni, R. B., Poulter, B., Sun, Z., Wang, T., Viovy, N., Zaehle,
S., and Zeng, N.: Evaluation of terrestrial carbon cycle models for their
response to climate variability and to CO2 trends, Glob. Chang. Biol.,
19, 2117–2132, https://doi.org/10.1111/gcb.12187, 2013. a, b
Piao, S., Liu, Z., Wang, T., Peng, S., Ciais, P., Huang, M., Ahlstrom, A.,
Burkhart, J. F., Chevallier, F., Janssens, I. A., Jeong, S. J., Lin, X., Mao,
J., Miller, J., Mohammat, A., Myneni, R. B., Peñuelas, J., Shi, X.,
Stohl, A., Yao, Y., Zhu, Z., and Tans, P. P.: Weakening temperature control
on the interannual variations of spring carbon uptake across northern lands,
Nat. Clim. Change, 7, 359–363, https://doi.org/10.1038/nclimate3277, 2017. a, b
Piao, S., Wang, X., Wang, K., Li, X., Bastos, A., Canadell, J. G., Ciais, P.,
Friedlingstein, P., and Sitch, S.: Interannual variation of terrestrial
carbon cycle: Issues and perspectives, Glob. Chang. Biol., 26, 300–318,
https://doi.org/10.1111/gcb.14884, 2020. a, b
Poulter, B., Heyder, U., and Cramer, W.: Modeling the sensitivity of the
seasonal cycle of GPP to dynamic LAI and soil depths in tropical
rainforests, Ecosystems, 12, 517–533, https://doi.org/10.1007/s10021-009-9238-4,
2009. a, b
Poulter, B., Frank, D., Ciais, P., Myneni, R. B., Andela, N., Bi, J., Broquet,
G., Canadell, J. G., Chevallier, F., Liu, Y. Y., et al.: Contribution of
semi-arid ecosystems to interannual variability of the global carbon cycle,
Nature, 509, 600–603, https://doi.org/10.1038/nature13376, 2014. a
Raich, J. W., Rastetter, E. B., Melillo, J. M., Kicklighter, D. W., Steudler,
P. A., Peterson, J., Grace, A. L., Iii, B. M., and Vörösmarty,
C. J.: Potential Net Primary Productivity in South America : Application of
a Global Model, Ecol. Appl., 1, 399–429, 1991. a
Ramsey, F. and Schafer, D.: The statistical sleuth: a course in methods of
data analysis, Cengage Learning, 784 pp., 2012. a
Randerson, J., Van der Werf, G., Giglio, L., Collatz, G., and Kasibhatla, P.:
Global Fire Emissions Database, Version 4.1 (GFEDv4), ORNL DAAC, Oak Ridge,
Tennessee, USA, https://doi.org/0.3334/ORNLDAAC/1293, 2018. a
Ratner, B.: Statistical and Machine-Learning Data Mining:: Techniques for
Better Predictive Modeling and Analysis of Big Data, CRC Press, 2012. a
Restrepo-Coupe, N., Levine, N. M., Christoffersen, B. O., Albert, L. P., Wu,
J., Costa, M. H., Galbraith, D., Imbuzeiro, H., Martins, G., da Araujo,
A. C., Malhi, Y. S., Zeng, X., Moorcroft, P., and Saleska, S. R.: Do dynamic
global vegetation models capture the seasonality of carbon fluxes in the
Amazon basin? A data-model intercomparison, Glob. Chang. Biol., 23,
191–208, https://doi.org/10.1111/gcb.13442, 2016. a
Rödenbeck, C., Zaehle, S., Keeling, R., and Heimann, M.: How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data, Biogeosciences, 15, 2481–2498, https://doi.org/10.5194/bg-15-2481-2018, 2018. a
Schwarz, G.: Estimating the dimension of a model, The annals of
statistics, 6, 461–464, 1978. a
Shiga, Y. P., Michalak, A. M., Fang, Y., Schaefer, K., Andrews, A. E.,
Huntzinger, D. H., Schwalm, C. R., Thoning, K., and Wei, Y.: Forests
dominate the interannual variability of the North American carbon sink,
Environ. Res. Lett., 13, https://doi.org/10.1088/1748-9326/aad505, 2018. a, b, c
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo, G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C., Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C., Smith, B., Zhu, Z., and Myneni, R.: Recent trends and drivers of regional sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, 2015. a, b
Wang, K., Wang, Y., Wang, X., He, Y., Li, X., Keeling, R. F., Ciais, P.,
Heimann, M., Peng, S., Chevallier, F., Friedlingstein, P., Sitch, S.,
Buermann, W., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., Lienert, S.,
Lombardozzi, D., Nabel, J. E., Poulter, B., Vuichard, N., Wiltshire, A.,
Zeng, N., Zhu, D., and Piao, S.: Causes of slowing-down seasonal CO2
amplitude at Mauna Loa, Glob. Chang. Biol., 26, 4462–4477,
https://doi.org/10.1111/gcb.15162, 2020. a
Wang, X., Piao, S., Ciais, P., Friedlingstein, P., Myneni, R. B., Cox, P.,
Heimann, M., Miller, J., Peng, S., Wang, T., Yang, H., and Chen, A.: A
two-fold increase of carbon cycle sensitivity to tropical temperature
variations, Nature, 506, 212–215, https://doi.org/10.1038/nature12915, 2014. a, b
Wofsy, S. C., Afshar, S., Allen, H. M., Apel, E. C., Asher, E. C., Barletta, B., Bent, J., Bian, H., Biggs, B. C., Blake, D. R., and Blake, N.: ATom: Merged Atmospheric Chemistry,
Trace Gases, and Aerosols, ORNL DAAC, Oak Ridge, Tennessee, USA,
https://doi.org/10.3334/ORNLDAAC/1581, 2018. a
Wunch, D., Toon, G. C., Blavier, J. F. L., Washenfelder, R. A., Notholt, J.,
Connor, B. J., Griffith, D. W., Sherlock, V., and Wennberg, P. O.: The total
carbon column observing network, Philos. T. Roy. Soc. A, 369, 2087–2112, https://doi.org/10.1098/rsta.2010.0240, 2011. a
Yadav, V., Mueller, K. L., Dragoni, D., and Michalak, A. M.: A geostatistical synthesis study of factors affecting gross primary productivity in various ecosystems of North America, Biogeosciences, 7, 2655–2671, https://doi.org/10.5194/bg-7-2655-2010, 2010. a
Yang, D., Liu, Y., Cai, Z., Chen, X., Yao, L., and Lu, D.: First Global Carbon
Dioxide Maps Produced from TanSat Measurements, Adv. Atmos. Sci., 35,
621–623, https://doi.org/10.1007/s00376-018-7312-6, 2018.
a
Zucchini, W.: An introduction to model selection, J. Math. Psychol., 44,
41–61, https://doi.org/10.1006/jmps.1999.1276, 2000. a
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...
Altmetrics
Final-revised paper
Preprint