Articles | Volume 17, issue 11
Atmos. Chem. Phys., 17, 7213–7228, 2017
https://doi.org/10.5194/acp-17-7213-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 17, 7213–7228, 2017
https://doi.org/10.5194/acp-17-7213-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 16 Jun 2017
Research article | 16 Jun 2017
A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions
Richard J. Millar et al.
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Christopher J. Smith, Piers M. Forster, Myles Allen, Nicholas Leach, Richard J. Millar, Giovanni A. Passerello, and Leighton A. Regayre
Geosci. Model Dev., 11, 2273–2297, https://doi.org/10.5194/gmd-11-2273-2018, https://doi.org/10.5194/gmd-11-2273-2018, 2018
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FAIR v1.3 is a simple Python-based climate model emulator. It takes emissions of greenhouse gases and aerosol and ozone precursors to calculate radiative forcing and temperature change. It includes a simple representation of carbon cycle feedbacks due to temperature and accumulated carbon uptake. Large ensembles can be run with minimal computational expense for any user-specified emissions pathway. We produce such an ensemble using the RCP emissions datasets.
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 Discuss., https://doi.org/10.5194/bg-2021-37, https://doi.org/10.5194/bg-2021-37, 2021
Preprint under review for BG
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Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters are emerging, especially in the last two 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.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Bettina K. Gier, Michael Buchwitz, Maximilian Reuter, Peter M. Cox, Pierre Friedlingstein, and Veronika Eyring
Biogeosciences, 17, 6115–6144, https://doi.org/10.5194/bg-17-6115-2020, https://doi.org/10.5194/bg-17-6115-2020, 2020
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Models from Coupled Model Intercomparison Project (CMIP) phases 5 and 6 are compared to a satellite data product of column-averaged CO2 mole fractions (XCO2). The previously believed discrepancy of the negative trend in seasonal cycle amplitude in the satellite product, which is not seen in in situ data nor in the models, is attributed to a sampling characteristic. Furthermore, CMIP6 models are shown to have made progress in reproducing the observed XCO2 time series compared to CMIP5.
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. Discuss., https://doi.org/10.5194/hess-2020-528, https://doi.org/10.5194/hess-2020-528, 2020
Revised manuscript under review for HESS
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While few studies have investigated the impacts of drought on vegetation, their findings are limited by the choice of vegetation proxy and model. Here, we used the LAI as proxy, and DGVMs to simulate drought impacts because the models use observationally-derived climate. We found that the semi-desert biome respond strongly to drought in the summer season, while the tropical forest biome shows weak response. This study could help target areas to improve drought monitoring and simulation.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-390, https://doi.org/10.5194/gmd-2020-390, 2020
Preprint under review for GMD
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This paper presents an update of the FaIR simple climate model, used for estimating the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used not only in academic or corporate research, but also in education.
Robin D. Lamboll, Zebedee R. J. Nicholls, Jarmo S. Kikstra, Malte Meinshausen, and Joeri Rogelj
Geosci. Model Dev., 13, 5259–5275, https://doi.org/10.5194/gmd-13-5259-2020, https://doi.org/10.5194/gmd-13-5259-2020, 2020
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Many models project how human activity can lead to more or less climate change, but most of these models do not project all climate-relevant emissions, potentially biasing climate projections. This paper outlines a Python package called Silicone, which can add missing emissions in a flexible yet high-throughput manner. It does this
infillingbased on more complete literature projections. It facilitates a more complete understanding of the climate impact of alternative emission pathways.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
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Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
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
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, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Jean-Christophe Golaz, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Nan Rosenbloom, Martin Schupfner, Roland Seferian, Zhenya Song, Christian Steger, Alistair Sellar, Neil Swart, Kaoru Tachiiri, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Rong Xinyao, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-68, https://doi.org/10.5194/esd-2020-68, 2020
Revised manuscript accepted for ESD
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We present a broad overview of CMIP6 ScenarioMIP outcomes from a multi-model ensemble 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. We also document results from large ensembles.
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris D. Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Olivier Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Emilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, Rachel M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry F. Tjiputra, Andy Wiltshire, Tongwen Wu, and Tilo Ziehn
Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, https://doi.org/10.5194/bg-17-4173-2020, 2020
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Since the preindustrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans. Comparison of different earth system models with the carbon cycle allows us to assess how carbon uptake by land and ocean differs among models. This yields an estimate of uncertainty in our understanding of how land and ocean respond to increasing atmospheric CO2. This paper summarizes results from two such model intercomparison projects that use an idealized scenario.
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 A. Sitch, and Sonke Zaehle
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-205, https://doi.org/10.5194/gmd-2020-205, 2020
Preprint under review for GMD
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Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle which is included within the UK Earth System model to improve projections of cliamte change and impacts on ecosystems.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, https://doi.org/10.5194/hess-24-1485-2020, 2020
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Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Nicholas James Leach, Zebedee Nicholls, Stuart Jenkins, Christopher J. Smith, John Lynch, Michelle Cain, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-379, https://doi.org/10.5194/gmd-2019-379, 2020
Revised manuscript not accepted
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GIR is a simple climate model designed to make exploration of the impact of greenhouse gas and aerosol emissions on the climate easy and understandable for its users. It uses an intuitive input and output structure, and the model is itself a set of only six equations. This lends the model to applications such as teaching, or as a lowest common denominator model between groups in large-scale climate assessments. It could also be used to investigate more complex models through emulation.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
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Earth system models for producing climate projections under given forcings include additional processes and feedbacks that traditional physical climate models do not consider. We present an overview of climate feedbacks for key Earth system components and discuss the evaluation of these feedbacks. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-400, https://doi.org/10.5194/hess-2018-400, 2018
Revised manuscript has not been submitted
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Extreme rainfall events are major concerns in Bangladesh because such events can cause flash floods and damage nearly harvestable crops in pre-monsoon season; whereas, in monsoon season, the impacts can range from widespread agricultural loss, huge property damage to loss of lives and livelihoods. This paper reveals the role of anthropogenic climate change drivers in changing the risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional scale within Bangladesh.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
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Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Sonya L. Fiddes, Matthew T. Woodhouse, Zebedee Nicholls, Todd P. Lane, and Robyn Schofield
Atmos. Chem. Phys., 18, 10177–10198, https://doi.org/10.5194/acp-18-10177-2018, https://doi.org/10.5194/acp-18-10177-2018, 2018
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The role of natural aerosol in the climate system is uncertain. A key contributor to marine aerosol is dimethyl sulfide (DMS), released by phytoplankton in the oceans. We study the effect of DMS on clouds and rain using a climate model with a detailed aerosol scheme. We show that DMS acts to reduce rainfall in cloud deck regions, leading to longer lived clouds and a large impact on solar energy reaching the surface. Further study of these areas will improve future climate projections.
Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, and Carolina Duran-Rojas
Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, https://doi.org/10.5194/gmd-11-2857-2018, 2018
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Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES is a DGVM that represents the land surface in the UK Earth System Model. We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets. JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements.
Christopher J. Smith, Piers M. Forster, Myles Allen, Nicholas Leach, Richard J. Millar, Giovanni A. Passerello, and Leighton A. Regayre
Geosci. Model Dev., 11, 2273–2297, https://doi.org/10.5194/gmd-11-2273-2018, https://doi.org/10.5194/gmd-11-2273-2018, 2018
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FAIR v1.3 is a simple Python-based climate model emulator. It takes emissions of greenhouse gases and aerosol and ozone precursors to calculate radiative forcing and temperature change. It includes a simple representation of carbon cycle feedbacks due to temperature and accumulated carbon uptake. Large ensembles can be run with minimal computational expense for any user-specified emissions pathway. We produce such an ensemble using the RCP emissions datasets.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
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The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Mahdi Nakhavali, Pierre Friedlingstein, Ronny Lauerwald, Jing Tang, Sarah Chadburn, Marta Camino-Serrano, Bertrand Guenet, Anna Harper, David Walmsley, Matthias Peichl, and Bert Gielen
Geosci. Model Dev., 11, 593–609, https://doi.org/10.5194/gmd-11-593-2018, https://doi.org/10.5194/gmd-11-593-2018, 2018
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In order to provide a better understanding of the Earth's carbon cycle, we need a model that represents the whole continuum from atmosphere to land and into the ocean. In this study we include in JULES a representation of dissolved organic carbon (DOC) processes. Our results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating the terrestrial and aquatic ecosystem.
Benoit P. Guillod, Richard G. Jones, Simon J. Dadson, Gemma Coxon, Gianbattista Bussi, James Freer, Alison L. Kay, Neil R. Massey, Sarah N. Sparrow, David C. H. Wallom, Myles R. Allen, and Jim W. Hall
Hydrol. Earth Syst. Sci., 22, 611–634, https://doi.org/10.5194/hess-22-611-2018, https://doi.org/10.5194/hess-22-611-2018, 2018
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Assessing the potential impacts of extreme events such as drought and flood requires large datasets of such events, especially when looking at the most severe and rare events. Using a state-of-the-art climate modelling infrastructure that is simulating large numbers of weather time series on volunteers' computers, we generate such a large dataset for the United Kingdom. The dataset covers the recent past (1900–2006) as well as two future time periods (2030s and 2080s).
Eleanor J. Burke, Altug Ekici, Ye Huang, Sarah E. Chadburn, Chris Huntingford, Philippe Ciais, Pierre Friedlingstein, Shushi Peng, and Gerhard Krinner
Biogeosciences, 14, 3051–3066, https://doi.org/10.5194/bg-14-3051-2017, https://doi.org/10.5194/bg-14-3051-2017, 2017
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There are large reserves of carbon within the permafrost which might be released to the atmosphere under global warming. Our models suggest this release may cause an additional global temperature increase of 0.005 to 0.2°C by the year 2100 and 0.01 to 0.34°C by the year 2300. Under climate mitigation scenarios this is between 1.5 and 9 % (by 2100) and between 6 and 16 % (by 2300) of the global mean temperature change. There is a large uncertainty associated with these results.
Benoit P. Guillod, Richard G. Jones, Andy Bowery, Karsten Haustein, Neil R. Massey, Daniel M. Mitchell, Friederike E. L. Otto, Sarah N. Sparrow, Peter Uhe, David C. H. Wallom, Simon Wilson, and Myles R. Allen
Geosci. Model Dev., 10, 1849–1872, https://doi.org/10.5194/gmd-10-1849-2017, https://doi.org/10.5194/gmd-10-1849-2017, 2017
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The weather@home climate modelling system uses the computing power of volunteers around the world to generate a very large number of climate model simulations. This is particularly useful when investigating extreme weather events, notably for the attribution of these events to anthropogenic climate change. A new version of weather@home is presented and evaluated, which includes an improved representation of the land surface and increased horizontal resolution over Europe.
Daniel Mitchell, Krishna AchutaRao, Myles Allen, Ingo Bethke, Urs Beyerle, Andrew Ciavarella, Piers M. Forster, Jan Fuglestvedt, Nathan Gillett, Karsten Haustein, William Ingram, Trond Iversen, Viatcheslav Kharin, Nicholas Klingaman, Neil Massey, Erich Fischer, Carl-Friedrich Schleussner, John Scinocca, Øyvind Seland, Hideo Shiogama, Emily Shuckburgh, Sarah Sparrow, Dáithí Stone, Peter Uhe, David Wallom, Michael Wehner, and Rashyd Zaaboul
Geosci. Model Dev., 10, 571–583, https://doi.org/10.5194/gmd-10-571-2017, https://doi.org/10.5194/gmd-10-571-2017, 2017
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This paper provides an experimental design to assess impacts of a world that is 1.5 °C warmer than at pre-industrial levels. The design is a new way to approach impacts from the climate community, and aims to answer questions related to the recent Paris Agreement. In particular the paper provides a method for studying extreme events under relatively high mitigation scenarios.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Brian C. O'Neill, Claudia Tebaldi, Detlef P. van Vuuren, Veronika Eyring, Pierre Friedlingstein, George Hurtt, Reto Knutti, Elmar Kriegler, Jean-Francois Lamarque, Jason Lowe, Gerald A. Meehl, Richard Moss, Keywan Riahi, and Benjamin M. Sanderson
Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, https://doi.org/10.5194/gmd-9-3461-2016, 2016
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The Scenario Model Intercomparison Project (ScenarioMIP) will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. The design consists of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions. Climate model projections will facilitate integrated studies of climate change as well as address targeted scientific questions.
Mitchell T. Black, David J. Karoly, Suzanne M. Rosier, Sam M. Dean, Andrew D. King, Neil R. Massey, Sarah N. Sparrow, Andy Bowery, David Wallom, Richard G. Jones, Friederike E. L. Otto, and Myles R. Allen
Geosci. Model Dev., 9, 3161–3176, https://doi.org/10.5194/gmd-9-3161-2016, https://doi.org/10.5194/gmd-9-3161-2016, 2016
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This study presents a citizen science computing project, known as weather@home Australia–New Zealand, which runs climate models on thousands of home computers. By harnessing the power of volunteers' computers, this project is capable of simulating extreme weather events over Australia and New Zealand under different climate scenarios.
Fang Zhao, Ning Zeng, Ghassem Asrar, Pierre Friedlingstein, Akihiko Ito, Atul Jain, Eugenia Kalnay, Etsushi Kato, Charles D. Koven, Ben Poulter, Rashid Rafique, Stephen Sitch, Shijie Shu, Beni Stocker, Nicolas Viovy, Andy Wiltshire, and Sonke Zaehle
Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, https://doi.org/10.5194/bg-13-5121-2016, 2016
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The increasing seasonality of atmospheric CO2 is strongly linked with enhanced land vegetation activities in the last 5 decades, for which the importance of increasing CO2, climate and land use/cover change was evaluated in single model studies (Zeng et al., 2014; Forkel et al., 2016). Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
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How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
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Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
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Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes. A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project – FireMIP.
Veronika Eyring, Mattia Righi, Axel Lauer, Martin Evaldsson, Sabrina Wenzel, Colin Jones, Alessandro Anav, Oliver Andrews, Irene Cionni, Edouard L. Davin, Clara Deser, Carsten Ehbrecht, Pierre Friedlingstein, Peter Gleckler, Klaus-Dirk Gottschaldt, Stefan Hagemann, Martin Juckes, Stephan Kindermann, John Krasting, Dominik Kunert, Richard Levine, Alexander Loew, Jarmo Mäkelä, Gill Martin, Erik Mason, Adam S. Phillips, Simon Read, Catherine Rio, Romain Roehrig, Daniel Senftleben, Andreas Sterl, Lambertus H. van Ulft, Jeremy Walton, Shiyu Wang, and Keith D. Williams
Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, https://doi.org/10.5194/gmd-9-1747-2016, 2016
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A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) in CMIP has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations.
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
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We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
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We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
C. D. Koven, J. Q. Chambers, K. Georgiou, R. Knox, R. Negron-Juarez, W. J. Riley, V. K. Arora, V. Brovkin, P. Friedlingstein, and C. D. Jones
Biogeosciences, 12, 5211–5228, https://doi.org/10.5194/bg-12-5211-2015, https://doi.org/10.5194/bg-12-5211-2015, 2015
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Terrestrial carbon feedbacks are a large uncertainty in climate change. We separate modeled feedback responses into those governed by changed carbon inputs (productivity) and changed outputs (turnover). The disaggregated responses show that both are important in controlling inter-model uncertainty. Interactions between productivity and turnover are also important, and research must focus on these interactions for more accurate projections of carbon cycle feedbacks.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
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In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
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Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
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ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
I. N. Fletcher, L. E. O. C. Aragão, A. Lima, Y. Shimabukuro, and P. Friedlingstein
Biogeosciences, 11, 1449–1459, https://doi.org/10.5194/bg-11-1449-2014, https://doi.org/10.5194/bg-11-1449-2014, 2014
D. Dalmonech, A. M. Foley, A. Anav, P. Friedlingstein, A. D. Friend, M. Kidston, M. Willeit, and S. Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-2083-2014, https://doi.org/10.5194/bgd-11-2083-2014, 2014
Revised manuscript has not been submitted
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
B. B. B. Booth, D. Bernie, D. McNeall, E. Hawkins, J. Caesar, C. Boulton, P. Friedlingstein, and D. M. H. Sexton
Earth Syst. Dynam., 4, 95–108, https://doi.org/10.5194/esd-4-95-2013, https://doi.org/10.5194/esd-4-95-2013, 2013
Related subject area
Subject: Gases | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Impact of western Pacific subtropical high on ozone pollution over eastern China
High-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint model
Simulation of radon-222 with the GEOS-Chem global model: emissions, seasonality, and convective transport
Regional CO2 fluxes from 2010 to 2015 inferred from GOSAT XCO2 retrievals using a new version of the Global Carbon Assimilation System
The friagem event in the central Amazon and its influence on micrometeorological variables and atmospheric chemistry
Modeling atmospheric ammonia using agricultural emissions with improved spatial variability and temporal dynamics
Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion
Large-eddy simulation of traffic-related air pollution at a very high-resolution in a mega-city: Evaluation against mobile sensors and insights for influencing factors
COVID-19 lockdowns highlight a risk of increasing ozone pollution in European urban areas
Errors in top-down estimates of emissions using a known source
The impact of urban land-surface on extreme air pollution over central Europe
Impacts of future land use and land cover change on mid-21st-century surface ozone air quality: distinguishing between the biogeophysical and biogeochemical effects
Technical note: Emission mapping of key sectors in Ho Chi Minh city, Vietnam using satellite derived urban land-use data
Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observations
What have we missed when studying the impact of aerosols on surface ozone via changing photolysis rates?
Stratospheric impact on the Northern Hemisphere winter and spring ozone interannual variability in the troposphere
Design and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experiments
Ozone pollution over China and India: seasonality and sources
Influences of oceanic ozone deposition on tropospheric photochemistry
Investigating the regional contributions to air pollution in Beijing: a dispersion modelling study using CO as a tracer
Evaluation of NU-WRF model performance on air quality simulation under various model resolutions – an investigation within the framework of MICS-Asia Phase III
Urban canopy meteorological forcing and its impact on ozone and PM2.5: role of vertical turbulent transport
Uncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network design
Climate benefits of proposed carbon dioxide mitigation strategies for international shipping and aviation
Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions
Analysis of summer O3 in the Madrid air basin with the LOTOS-EUROS chemical transport model
Analysis of temporal and spatial variability of atmospheric CO2 concentration within Paris from the GreenLITE™ laser imaging experiment
A typical weather pattern for ozone pollution events in North China
The control of anthropogenic emissions contributed to 80 % of the decrease in PM2.5 concentrations in Beijing from 2013 to 2017
Trans-Pacific transport and evolution of aerosols: spatiotemporal characteristics and source contributions
Foreign influences on tropospheric ozone over East Asia through global atmospheric transport
Estimating ground-level CO concentrations across China based on the national monitoring network and MOPITT: potentially overlooked CO hotspots in the Tibetan Plateau
Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 XCO2 retrievals
Diagnosing spatial error structures in CO2 mole fractions and XCO2 column mole fractions from atmospheric transport
How marine emissions of bromoform impact the remote atmosphere
An atmospheric inversion over the city of Cape Town: sensitivity analyses
Modelling CO2 weather – why horizontal resolution matters
Calibration of a multi-physics ensemble for estimating the uncertainty of a greenhouse gas atmospheric transport model
Analysis of atmospheric CH4 in Canadian Arctic and estimation of the regional CH4 fluxes
Accounting for the vertical distribution of emissions in atmospheric CO2 simulations
Urban source term estimation for mercury using a boundary-layer budget method
Characterizing uncertainties in atmospheric inversions of fossil fuel CO2 emissions in California
Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study
Attributing differences in the fate of lateral boundary ozone in AQMEII3 models to physical process representations
Impacts of physical parameterization on prediction of ethane concentrations for oil and gas emissions in WRF-Chem
An important mechanism of regional O3 transport for summer smog over the Yangtze River Delta in eastern China
Rapid and reliable assessment of methane impacts on climate
Impact of physical parameterizations and initial conditions on simulated atmospheric transport and CO2 mole fractions in the US Midwest
Seasonal ozone vertical profiles over North America using the AQMEII3 group of air quality models: model inter-comparison and stratospheric intrusions
Quantifying the vertical transport of CHBr3 and CH2Br2 over the western Pacific
Zhongjing Jiang, Jing Li, Xiao Lu, Cheng Gong, Lin Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 2601–2613, https://doi.org/10.5194/acp-21-2601-2021, https://doi.org/10.5194/acp-21-2601-2021, 2021
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This study demonstrates that the intensity of the western Pacific subtropical high (WPSH), a major synoptic pattern in the northern Pacific during summer, can induce a dipole change in surface ozone pollution over eastern China. Ozone concentration increases in the north and decreases in the south during the strong WPSH phase, and vice versa. The change in chemical processes associated with the WPSH change plays a decisive role, whereas the natural emission of ozone precursors accounts for ~ 30 %.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
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Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Bo Zhang, Hongyu Liu, James H. Crawford, Gao Chen, T. Duncan Fairlie, Scott Chambers, Chang-Hee Kang, Alastair G. Williams, Kai Zhang, David B. Considine, Melissa P. Sulprizio, and Robert M. Yantosca
Atmos. Chem. Phys., 21, 1861–1887, https://doi.org/10.5194/acp-21-1861-2021, https://doi.org/10.5194/acp-21-1861-2021, 2021
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We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn emissions and characterize convective transport in the model. We demonstrate the potential of a customized global 222Rn emission scenario to improve simulated surface 222Rn concentrations and seasonality. We assess convective transport using observed 222Rn vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985, https://doi.org/10.5194/acp-21-1963-2021, https://doi.org/10.5194/acp-21-1963-2021, 2021
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We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
Guilherme F. Camarinha-Neto, Julia C. P. Cohen, Cléo Q. Dias-Júnior, Matthias Sörgel, José Henrique Cattanio, Alessandro Araújo, Stefan Wolff, Paulo A. F. Kuhn, Rodrigo A. F. Souza, Luciana V. Rizzo, and Paulo Artaxo
Atmos. Chem. Phys., 21, 339–356, https://doi.org/10.5194/acp-21-339-2021, https://doi.org/10.5194/acp-21-339-2021, 2021
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It was observed that friagem phenomena (incursion of cold waves from the high latitudes of the Southern Hemisphere to the Amazon region), very common in the dry season of the Amazon region, produced significant changes in microclimate and atmospheric chemistry. Moreover, the effects of the friagem change the surface O3 and CO2 mixing ratios and therefore interfere deeply in the microclimatic conditions and the chemical composition of the atmosphere above the rainforest.
Xinrui Ge, Martijn Schaap, Richard Kranenburg, Arjo Segers, Gert Jan Reinds, Hans Kros, and Wim de Vries
Atmos. Chem. Phys., 20, 16055–16087, https://doi.org/10.5194/acp-20-16055-2020, https://doi.org/10.5194/acp-20-16055-2020, 2020
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This article is about improving the modeling of agricultural ammonia emissions. By considering land use, meteorology and agricultural practices, ammonia emission totals officially reported by countries are distributed in space and time. We illustrated the first step for a better understanding of the variability of ammonia emission, with the possibility of being applied at a European scale, which is of great significance for ammonia budget research and future policy-making.
Ashok K. Luhar, David M. Etheridge, Zoë M. Loh, Julie Noonan, Darren Spencer, Lisa Smith, and Cindy Ong
Atmos. Chem. Phys., 20, 15487–15511, https://doi.org/10.5194/acp-20-15487-2020, https://doi.org/10.5194/acp-20-15487-2020, 2020
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With the sharp rise in coal seam gas (CSG) production in Queensland’s Surat Basin, there is much interest in quantifying methane emissions from this area and from unconventional gas production in general. We develop and apply a regional Bayesian inverse model that uses hourly methane concentration data from two sites and modelled backward dispersion to quantify emissions. The model requires a narrow prior and suggests that the emissions from the CSG areas are 33% larger than bottom-up estimates.
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1168, https://doi.org/10.5194/acp-2020-1168, 2020
Revised manuscript accepted for ACP
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Urban air quality varies drastically at street scale but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in a megacity, Nanjing. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Stuart K. Grange, James D. Lee, Will S. Drysdale, Alastair C. Lewis, Christoph Hueglin, Lukas Emmenegger, and David C. Carslaw
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1171, https://doi.org/10.5194/acp-2020-1171, 2020
Revised manuscript accepted for ACP
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The changes in mobility across Europe due to the COVID-19 lockdowns had consequences for air quality. We compare what was experienced, to estimates of
what would have beenwithout the lockdowns. Nitrogen dioxide (NO2), an important vehicle-sourced pollutant, decreased by a third. However, ozone (O3) increased in response to the lower NO2. Because NO2 is decreasing over time, increases in O3 can be expected in European urban areas and will require management to avoid future negative outcomes.
Wayne M. Angevine, Jeff Peischl, Alice Crawford, Christopher P. Loughner, Ilana B. Pollack, and Chelsea R. Thompson
Atmos. Chem. Phys., 20, 11855–11868, https://doi.org/10.5194/acp-20-11855-2020, https://doi.org/10.5194/acp-20-11855-2020, 2020
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Emissions of air pollutants must be known for a wide variety of applications. Different methods of estimating emissions often disagree substantially. In this study, we apply standard methods to a well-known source, a power plant. We explore the uncertainty implied by the different answers that come from the different methods, different samples taken over several years, and different pollutants. We find that the overall uncertainty of emissions estimates is about 30 %.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Tereza Nováková, Kateřina Šindelářová, Filip Švábik, Michal Belda, Tomáš Halenka, and Michal Žák
Atmos. Chem. Phys., 20, 11655–11681, https://doi.org/10.5194/acp-20-11655-2020, https://doi.org/10.5194/acp-20-11655-2020, 2020
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The paper shows how extreme meteorological conditions change due to the urban land-cover forcing and how this translates to the impact on the extreme air pollution over central European cities. It focuses on ozone, nitrogen dioxide, and particulate matter with a diameter of less than 2.5 μm and shows that, while for the extreme daily maximum 8 h ozone, changes are same as for the mean ones, much larger modifications are calculated for extreme NO2 and PM2.5 compared to their mean changes.
Lang Wang, Amos P. K. Tai, Chi-Yung Tam, Mehliyar Sadiq, Peng Wang, and Kevin K. W. Cheung
Atmos. Chem. Phys., 20, 11349–11369, https://doi.org/10.5194/acp-20-11349-2020, https://doi.org/10.5194/acp-20-11349-2020, 2020
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We investigate the effects of future land use and land cover change (LULCC) on surface ozone air quality worldwide and find that LULCC can significantly influence ozone in North America and Europe via modifying surface energy balance, boundary-layer meteorology, and regional circulation. The strength of such “biogeophysical effects” of LULCC is strongly dependent on forest type and generally greater than the “biogeochemical effects” via changing deposition and emission fluxes alone.
Trang Thi Quynh Nguyen, Wataru Takeuchi, and Prakhar Misra
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-895, https://doi.org/10.5194/acp-2020-895, 2020
Revised manuscript accepted for ACP
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This study provides annual emissions of transportation, manufacturing industries and construction and residential sectors at 1 km resolution from 2009 to 2016 for Ho Chi Minh city, Vietnam. We consider both Scope 1 – all direct emissions from the activities occurring within the city and Scope 2 that is indirect emissions from electricity purchased. Our originality is the use of satellite derived urban land-use morphological maps which allow emission mapping in study area.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boech, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-775, https://doi.org/10.5194/acp-2020-775, 2020
Revised manuscript accepted for ACP
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We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Jinhui Gao, Ying Li, Bin Zhu, Bo Hu, Lili Wang, and Fangwen Bao
Atmos. Chem. Phys., 20, 10831–10844, https://doi.org/10.5194/acp-20-10831-2020, https://doi.org/10.5194/acp-20-10831-2020, 2020
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Light extinction of aerosols can decease surface ozone mainly via reducing photochemical production of ozone. However, it also leads to high levels of ozone aloft being entrained down to the surface which partly counteracts the reduction in surface ozone. The impact of aerosols is more sensitive to local ozone, which suggests that while controlling the levels of aerosols, controlling the local ozone precursors is an effective way to suppress the increase of ozone over China at present.
Junhua Liu, Jose M. Rodriguez, Luke D. Oman, Anne R. Douglass, Mark A. Olsen, and Lu Hu
Atmos. Chem. Phys., 20, 6417–6433, https://doi.org/10.5194/acp-20-6417-2020, https://doi.org/10.5194/acp-20-6417-2020, 2020
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Our paper quantifies and identifies the importance of stratospheric ozone influence on the tropospheric ozone IAV in Northern Hemisphere mid-high latitudes. Our analysis provides an in-depth understanding of how 3-D dynamics influences the O3 redistribution in the troposphere. These findings are particularly important considering the potential changes in these dynamical conditions in the future as a result of climate change
Jun Park and Hyun Mee Kim
Atmos. Chem. Phys., 20, 5175–5195, https://doi.org/10.5194/acp-20-5175-2020, https://doi.org/10.5194/acp-20-5175-2020, 2020
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Observation network experiments were conducted to optimize the surface CO2 flux in Asia. The impacts of the redistribution of and additions to the existing observation network were evaluated. The addition experiments revealed that considering both the normalized self-sensitivity and ecoregion information can yield better simulated surface CO2 fluxes compared to random addition. This study provides useful information for future observation network design to estimate the surface CO2 flux.
Meng Gao, Jinhui Gao, Bin Zhu, Rajesh Kumar, Xiao Lu, Shaojie Song, Yuzhong Zhang, Beixi Jia, Peng Wang, Gufran Beig, Jianlin Hu, Qi Ying, Hongliang Zhang, Peter Sherman, and Michael B. McElroy
Atmos. Chem. Phys., 20, 4399–4414, https://doi.org/10.5194/acp-20-4399-2020, https://doi.org/10.5194/acp-20-4399-2020, 2020
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A regional fully coupled meteorology–chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O3) pollution and its sources in both China and India.
Ryan J. Pound, Tomás Sherwen, Detlev Helmig, Lucy J. Carpenter, and Mat J. Evans
Atmos. Chem. Phys., 20, 4227–4239, https://doi.org/10.5194/acp-20-4227-2020, https://doi.org/10.5194/acp-20-4227-2020, 2020
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Ozone is an important pollutant with impacts on health and the environment. Ozone is lost to plants, land and the oceans. Loss to the ocean is slow compared to all other types of land cover and has not received as much attention. We build on previous work to more accurately model ozone loss to the ocean. We find changes in the concentration of ozone over the oceans, notably the Southern Ocean, which improves model performance.
Marios Panagi, Zoë L. Fleming, Paul S. Monks, Matthew J. Ashfold, Oliver Wild, Michael Hollaway, Qiang Zhang, Freya A. Squires, and Joshua D. Vande Hey
Atmos. Chem. Phys., 20, 2825–2838, https://doi.org/10.5194/acp-20-2825-2020, https://doi.org/10.5194/acp-20-2825-2020, 2020
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In this paper, using dispersion modelling with emission inventories it was determined that on average 45 % of the total CO pollution that affects Beijing is transported from other areas. About half of the CO comes from beyond the immediate surrounding areas. Finally three classification types of pollution were identified and used to analyse the APHH winter campaign. The results can inform targeted control measures to be implemented in Beijing and the other regions to tackle air quality problems.
Zhining Tao, Mian Chin, Meng Gao, Tom Kucsera, Dongchul Kim, Huisheng Bian, Jun-ichi Kurokawa, Yuesi Wang, Zirui Liu, Gregory R. Carmichael, Zifa Wang, and Hajime Akimoto
Atmos. Chem. Phys., 20, 2319–2339, https://doi.org/10.5194/acp-20-2319-2020, https://doi.org/10.5194/acp-20-2319-2020, 2020
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One goal of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III is to identify strengths and weaknesses of current air quality models to provide insights into reducing uncertainties. This study identified that a 15 km grid would be the optimal horizontal resolution in terms of performance and resource usage to capture average and extreme air quality over East Asia and is thus suggested for use in future MICS-Asia modeling activities if the investigation domain remains the same.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Kateřina Šindelářová, Tereza Nováková, Michal Belda, Tomáš Halenka, Michal Žák, and Petr Pišoft
Atmos. Chem. Phys., 20, 1977–2016, https://doi.org/10.5194/acp-20-1977-2020, https://doi.org/10.5194/acp-20-1977-2020, 2020
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Urban surfaces alter meteorological conditions which consequently alter air pollution due to modified transport and chemical reactions. Here, we focus on a major component of this influence, enhanced vertical eddy diffusion. Using a regional climate model coupled to a chemistry transport model, we investigate how different representations of turbulent transport translate to urban canopy impact on ozone and PM2.5 concentrations and whether turbulence remains the most important component.
Ingrid Super, Stijn N. C. Dellaert, Antoon J. H. Visschedijk, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys., 20, 1795–1816, https://doi.org/10.5194/acp-20-1795-2020, https://doi.org/10.5194/acp-20-1795-2020, 2020
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Emission data contain uncertainties introduced by the methodology and the data used. We quantified uncertainties in gridded emissions using the uncertainty in underlying data, showing that disaggregation in space and time significantly increases the uncertainty. Understanding uncertainties helps to interpret atmospheric measurements and the gap with modelled concentrations. Moreover, our analyses help identify regions with large uncertainties, which require further scrutiny.
Catherine C. Ivanovich, Ilissa B. Ocko, Pedro Piris-Cabezas, and Annie Petsonk
Atmos. Chem. Phys., 19, 14949–14965, https://doi.org/10.5194/acp-19-14949-2019, https://doi.org/10.5194/acp-19-14949-2019, 2019
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The Paris Agreement set the goal of remaining well below a 2 °C global temperature rise, but it is unclear how future emissions from international shipping and aviation will contribute to this threshold. Here we estimate that the sectors' future emissions of carbon dioxide will contribute a combined 0.12 °C by the end of the century should no action be taken, but proposed mitigation policies have the potential to reduce this warming by almost 90 %.
Frédéric Chevallier, Marine Remaud, Christopher W. O'Dell, David Baker, Philippe Peylin, and Anne Cozic
Atmos. Chem. Phys., 19, 14233–14251, https://doi.org/10.5194/acp-19-14233-2019, https://doi.org/10.5194/acp-19-14233-2019, 2019
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We present a way to rate the CO2 flux estimates made from inversion of a global atmospheric transport model. Our approach relies on accurate aircraft measurements in the free troposphere. It shows that some satellite soundings can now provide inversion results that are, despite their uncertainty, comparable in credibility to traditional inversions using the accurate but sparse surface network and that these inversions are, therefore, complementary for studies of the global carbon budget.
Miguel Escudero, Arjo Segers, Richard Kranenburg, Xavier Querol, Andrés Alastuey, Rafael Borge, David de la Paz, Gotzon Gangoiti, and Martijn Schaap
Atmos. Chem. Phys., 19, 14211–14232, https://doi.org/10.5194/acp-19-14211-2019, https://doi.org/10.5194/acp-19-14211-2019, 2019
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In this work we optimise LOTOS-EUROS CTM for simulating tropospheric O3 during summer in the Madrid metropolitan area, one of the largest conurbations in the Mediterranean. Comparing the outputs from five set-ups with different combinations of spatial resolution, meteorological data and vertical structure, we conclude that the model benefits from fine horizontal resolution and highly resolved vertical structure. Running optimized configuration run, we interpret O3 variability during July 2016.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, T. Scott Zaccheo, Jeremy Dobler, Michel Ramonet, Johannes Staufer, Diego Santaren, Irène Xueref-Remy, and Philippe Ciais
Atmos. Chem. Phys., 19, 13809–13825, https://doi.org/10.5194/acp-19-13809-2019, https://doi.org/10.5194/acp-19-13809-2019, 2019
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CO2 emissions within urban areas impact nearby and downwind concentrations. A different system, based on bi-wavelength laser measurements, has been deployed over Paris. It samples CO2 concentrations along horizontal lines, between a transceiver and a reflector. In this paper, we analyze the measurements provided by this system, together with the more classical in situ sampling and high-resolution modeling. We focus on the temporal and spatial variability of atmospheric CO2 concentrations.
Cheng Gong and Hong Liao
Atmos. Chem. Phys., 19, 13725–13740, https://doi.org/10.5194/acp-19-13725-2019, https://doi.org/10.5194/acp-19-13725-2019, 2019
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Severe O3 pollution events (OPEs) were observed frequently in summer in North China. We found a typical weather pattern that was responsible for the 21 OPEs observed in North China in May to July of 2014–2017. This weather pattern is characterized by high daily maximum temperature, low relative humidity and an anomalous high-pressure system at 500 hPa. Under such a weather pattern, chemical production of O3 is high between 800 and 900 hPa, which is then transported downward to enhance O3 levels.
Ziyue Chen, Danlu Chen, Mei-Po Kwan, Bin Chen, Bingbo Gao, Yan Zhuang, Ruiyuan Li, and Bing Xu
Atmos. Chem. Phys., 19, 13519–13533, https://doi.org/10.5194/acp-19-13519-2019, https://doi.org/10.5194/acp-19-13519-2019, 2019
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We employed Kolmogorov–Zurbenko filtering and WRF-CMAQ to quantify the relative contribution of meteorological variations and emission reduction to PM2.5 reduction in Beijing from 2013 to 2017, which is crucial to evaluate the Five-year Clean Air Action Plan. Both models suggested that despite favourable meteorological conditions, the control of anthropogenic emissions accounted for around 80 % of PM2.5 reduction in Beijing. Therefore, such a long-term clean air plan should be continued.
Zhiyuan Hu, Jianping Huang, Chun Zhao, Yuanyuan Ma, Qinjian Jin, Yun Qian, L. Ruby Leung, Jianrong Bi, and Jianmin Ma
Atmos. Chem. Phys., 19, 12709–12730, https://doi.org/10.5194/acp-19-12709-2019, https://doi.org/10.5194/acp-19-12709-2019, 2019
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This study investigates aerosol chemical compositions and relative contributions to total aerosols in the western US. The results show that trans-Pacific aerosols have a maximum concentration in the boreal spring, with the greatest contribution from dust. Over western North America, the trans-Pacific aerosols dominate the column-integrated aerosol mass and number concentration. However, near the surface, aerosols mainly originated from local emissions.
Han Han, Jane Liu, Huiling Yuan, Tijian Wang, Bingliang Zhuang, and Xun Zhang
Atmos. Chem. Phys., 19, 12495–12514, https://doi.org/10.5194/acp-19-12495-2019, https://doi.org/10.5194/acp-19-12495-2019, 2019
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In the East Asian middle and upper troposphere, foreign ozone is 0.8–4.8 times more than its native counterpart in all the seasons. At the East Asian surface, the annual mean concentrations of foreign ozone and native ozone are comparable, being approximately 20 ppbv. The seasonal and interannual variations in foreign ozone over East Asia are closely related to the East Asian monsoon.
Dongren Liu, Baofeng Di, Yuzhou Luo, Xunfei Deng, Hanyue Zhang, Fumo Yang, Michael L. Grieneisen, and Yu Zhan
Atmos. Chem. Phys., 19, 12413–12430, https://doi.org/10.5194/acp-19-12413-2019, https://doi.org/10.5194/acp-19-12413-2019, 2019
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The spatiotemporal distributions of daily ground-level CO concentrations across China during 2013–2016 are derived by fusing the data from remote sensing and ground monitoring. The population–weighted CO was predicted to be 0.99 ± 0.30 mg m−3 and showed a decreasing trend of −0.021 ± 0.004 mg m−3 per year. The CO pollution was the most severe in the North China Plain. The hotspots in the Tibetan Plateau overlooked by the remote sensing were depicted by the data-fusion approach.
Hengmao Wang, Fei Jiang, Jun Wang, Weimin Ju, and Jing M. Chen
Atmos. Chem. Phys., 19, 12067–12082, https://doi.org/10.5194/acp-19-12067-2019, https://doi.org/10.5194/acp-19-12067-2019, 2019
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The differences in inverted global and regional carbon fluxes from GOSAT and OCO-2 XCO2 from 1 January to 31 December 2015 are studied. We find significant differences for inverted terrestrial carbon fluxes on both global and regional scales. Overall, GOSAT XCO2 has a better performance than OCO-2, and GOSAT data can effectively improve carbon flux estimates in the Northern Hemisphere, while OCO-2 data, with the specific version used in this study, show only slight improvement.
Thomas Lauvaux, Liza I. Díaz-Isaac, Marc Bocquet, and Nicolas Bousserez
Atmos. Chem. Phys., 19, 12007–12024, https://doi.org/10.5194/acp-19-12007-2019, https://doi.org/10.5194/acp-19-12007-2019, 2019
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A small-size ensemble of mesoscale simulations has been filtered to characterize the spatial structures of transport errors in atmospheric CO2 mixing ratios. The extracted error structures in in situ and column CO2 show similar length scales compared to other meteorological variables, including seasonality, which could be used as proxies in regional inversion systems.
Yue Jia, Susann Tegtmeier, Elliot Atlas, and Birgit Quack
Atmos. Chem. Phys., 19, 11089–11103, https://doi.org/10.5194/acp-19-11089-2019, https://doi.org/10.5194/acp-19-11089-2019, 2019
Alecia Nickless, Peter J. Rayner, Robert J. Scholes, Francois Engelbrecht, and Birgit Erni
Atmos. Chem. Phys., 19, 7789–7816, https://doi.org/10.5194/acp-19-7789-2019, https://doi.org/10.5194/acp-19-7789-2019, 2019
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Different frameworks for an atmospheric inversion study over Cape Town, South Africa, are considered. We focused particularly on how sensitive the estimates of CO2 fluxes were to changes in the way the uncertainty in these estimates was specified and the impact different prior information had on the final flux estimates. We used atmospheric measurements from two new sites located near Cape Town: Robben Island and Hangklip lighthouses, which were specifically deployed for this inversion study.
Anna Agustí-Panareda, Michail Diamantakis, Sébastien Massart, Frédéric Chevallier, Joaquín Muñoz-Sabater, Jérôme Barré, Roger Curcoll, Richard Engelen, Bavo Langerock, Rachel M. Law, Zoë Loh, Josep Anton Morguí, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Coleen Roehl, Alex T. Vermeulen, Thorsten Warneke, and Debra Wunch
Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, https://doi.org/10.5194/acp-19-7347-2019, 2019
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This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO2 patterns associated with evolving weather. The modelling of CO2 weather is crucial to interpret the variability from ground-based and satellite CO2 observations, which can then be used to infer CO2 fluxes in atmospheric inversions. The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO2 flux distribution.
Liza I. Díaz-Isaac, Thomas Lauvaux, Marc Bocquet, and Kenneth J. Davis
Atmos. Chem. Phys., 19, 5695–5718, https://doi.org/10.5194/acp-19-5695-2019, https://doi.org/10.5194/acp-19-5695-2019, 2019
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We demonstrate that transport model errors, one of the main contributors to the uncertainty in regional CO2 inversions, can be represented by a small-size ensemble carefully calibrated with meteorological data. Our results also confirm transport model errors represent a significant fraction of the model–data mismatch in CO2 mole fractions and hence in regional inverse CO2 fluxes.
Misa Ishizawa, Douglas Chan, Doug Worthy, Elton Chan, Felix Vogel, and Shamil Maksyutov
Atmos. Chem. Phys., 19, 4637–4658, https://doi.org/10.5194/acp-19-4637-2019, https://doi.org/10.5194/acp-19-4637-2019, 2019
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The Canadian Arctic has the potential for enhanced methane (CH4) emissions under global warming. However, the regional CH4 emission (fluxes) estimates range widely. This study analyzes recent Canadian Arctic CH4 observations and estimates the regional emissions. The additional observations yield robust CH4 flux estimates and enable the partitioning of the CH4 sources into wetland and forest fires. The results indicate that years with warmer summer conditions result in more wetland CH4 emissions.
Dominik Brunner, Gerrit Kuhlmann, Julia Marshall, Valentin Clément, Oliver Fuhrer, Grégoire Broquet, Armin Löscher, and Yasjka Meijer
Atmos. Chem. Phys., 19, 4541–4559, https://doi.org/10.5194/acp-19-4541-2019, https://doi.org/10.5194/acp-19-4541-2019, 2019
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Atmospheric transport models are increasingly being used to estimate CO2 emissions from atmospheric CO2 measurements. This study demonstrates the importance of distributing CO2 emissions vertically in the model according to realistic profiles, since a major proportion of CO2 is emitted through tall stacks from power plants and industrial sources. With the traditional approach of emitting all CO2 at the surface, models may significantly overestimate the atmospheric CO2 levels.
Basil Denzler, Christian Bogdal, Cyrill Kern, Anna Tobler, Jing Huo, and Konrad Hungerbühler
Atmos. Chem. Phys., 19, 3821–3831, https://doi.org/10.5194/acp-19-3821-2019, https://doi.org/10.5194/acp-19-3821-2019, 2019
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Mercury poses a threat to human health and the environment. Therefore, the reduction of emissions is a declared aim. Here, we quantified mercury emission for the city of Zurich, Switzerland, based on atmospheric measurements and box modeling. This so-called top-down approach allows us to better constrain mercury emissions from diffuse distributed sources. This is applicable to other regions and presents a cost-effective way of quantifying emissions, as a first step in the reduction thereof.
Kieran Brophy, Heather Graven, Alistair J. Manning, Emily White, Tim Arnold, Marc L. Fischer, Seongeun Jeong, Xinguang Cui, and Matthew Rigby
Atmos. Chem. Phys., 19, 2991–3006, https://doi.org/10.5194/acp-19-2991-2019, https://doi.org/10.5194/acp-19-2991-2019, 2019
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We investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of California's fossil fuel CO2 emissions. Our results indicate that uncertainties in posterior total state fossil fuel CO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider.
Anna Karion, Thomas Lauvaux, Israel Lopez Coto, Colm Sweeney, Kimberly Mueller, Sharon Gourdji, Wayne Angevine, Zachary Barkley, Aijun Deng, Arlyn Andrews, Ariel Stein, and James Whetstone
Atmos. Chem. Phys., 19, 2561–2576, https://doi.org/10.5194/acp-19-2561-2019, https://doi.org/10.5194/acp-19-2561-2019, 2019
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In this study, we use atmospheric methane concentration observations collected during an airborne campaign to compare different model-based emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We find that the tracer dispersion model has a significant impact on the results because the models differ in their simulation of vertical dispersion. Additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models.
Peng Liu, Christian Hogrefe, Ulas Im, Jesper H. Christensen, Johannes Bieser, Uarporn Nopmongcol, Greg Yarwood, Rohit Mathur, Shawn Roselle, and Tanya Spero
Atmos. Chem. Phys., 18, 17157–17175, https://doi.org/10.5194/acp-18-17157-2018, https://doi.org/10.5194/acp-18-17157-2018, 2018
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This study represents an intercomparison of four regional-scale air quality simulations in order to understand the model similarities and differences in estimating the impact of ozone imported from outside of the US on the surface ozone within the US at process level. Vertical turbulent mixing stands out as a primary contributor to the model differences in inert tracers.
Maryam Abdi-Oskouei, Gabriele Pfister, Frank Flocke, Negin Sobhani, Pablo Saide, Alan Fried, Dirk Richter, Petter Weibring, James Walega, and Gregory Carmichael
Atmos. Chem. Phys., 18, 16863–16883, https://doi.org/10.5194/acp-18-16863-2018, https://doi.org/10.5194/acp-18-16863-2018, 2018
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This study presents a quantification of model uncertainties due to configurations and errors in the emission inventories. The analysis includes performing simulations with different configurations and comparisons with airborne and ground-based observations with a focus on capturing transport and emissions from the oil and gas sector. The presented results reflect the challenges that one may face when attempting to improve emission inventories by contrasting measured with modeled concentrations.
Jun Hu, Yichen Li, Tianliang Zhao, Jane Liu, Xiao-Ming Hu, Duanyang Liu, Yongcheng Jiang, Jianming Xu, and Luyu Chang
Atmos. Chem. Phys., 18, 16239–16251, https://doi.org/10.5194/acp-18-16239-2018, https://doi.org/10.5194/acp-18-16239-2018, 2018
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Using observational and modeling studies, the importance of the mechanism driving regional O3 transport in the residual layer (RL) with respect to summer smog over the Yangtze River Delta region in eastern China was revealed. This mechanism was also examined in association with diurnal change in the atmospheric boundary layer. Regional O3 transport through the nocturnal RL is believed to have great implications for understanding urban and regional O3 pollution in this area.
Ilissa B. Ocko, Vaishali Naik, and David Paynter
Atmos. Chem. Phys., 18, 15555–15568, https://doi.org/10.5194/acp-18-15555-2018, https://doi.org/10.5194/acp-18-15555-2018, 2018
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As communities worldwide analyse options to reduce methane emissions from energy use, agriculture, and waste management, there is an immediate need to build confidence in rapid assessment tools other than standard climate metrics – which misrepresent impacts over all timescales. In this paper, we show that a simplified climate model can easily and rapidly provide scientifically robust climate responses to changes in methane emissions, thereby improving mitigation analysis and decision-making.
Liza I. Díaz-Isaac, Thomas Lauvaux, and Kenneth J. Davis
Atmos. Chem. Phys., 18, 14813–14835, https://doi.org/10.5194/acp-18-14813-2018, https://doi.org/10.5194/acp-18-14813-2018, 2018
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Atmospheric inversions rely on the accurate representation of the atmospheric dynamics in order to produce reliable surface fluxes. In this work, we evaluate the sensitivity of a state-of-the-art mesoscale atmospheric model to the different physics parameterizations and forcing. We conclude that no model configuration is optimal across an entire region. Therefore, we recommend an ensemble approach or the assimilation of meteorological observations in future inversion studies.
Marina Astitha, Ioannis Kioutsioukis, Ghezae Araya Fisseha, Roberto Bianconi, Johannes Bieser, Jesper H. Christensen, Owen R. Cooper, Stefano Galmarini, Christian Hogrefe, Ulas Im, Bryan Johnson, Peng Liu, Uarporn Nopmongcol, Irina Petropavlovskikh, Efisio Solazzo, David W. Tarasick, and Greg Yarwood
Atmos. Chem. Phys., 18, 13925–13945, https://doi.org/10.5194/acp-18-13925-2018, https://doi.org/10.5194/acp-18-13925-2018, 2018
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This work is unique in the detailed analyses of modeled ozone vertical profiles from sites in North America through the collaboration of four research groups from the US and EU. We assess the air quality models' performance and model inter-comparison for ozone vertical profiles and stratospheric ozone intrusions. Lastly, we designate the important role of lateral boundary conditions in the ozone vertical profiles using chemically inert tracers.
Robyn Butler, Paul I. Palmer, Liang Feng, Stephen J. Andrews, Elliot L. Atlas, Lucy J. Carpenter, Valeria Donets, Neil R. P. Harris, Stephen A. Montzka, Laura L. Pan, Ross J. Salawitch, and Sue M. Schauffler
Atmos. Chem. Phys., 18, 13135–13153, https://doi.org/10.5194/acp-18-13135-2018, https://doi.org/10.5194/acp-18-13135-2018, 2018
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Natural sources of short-lived bromoform and dibromomethane are important for determining the inorganic bromine budget in the stratosphere that drives ozone loss. Two new modelling techniques describe how different geographical source regions influence their atmospheric variability over the western Pacific. We find that it is driven primarily by open ocean sources, and we use atmospheric observations to help estimate their contributions to the upper tropospheric inorganic bromine budget.
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Short summary
Simple representations of the global coupled climate–carbon-cycle system are required for climate policy analysis. Existing models have often failed to capture important physical dependencies of the climate response to carbon dioxide emissions. In this paper we propose a simple but novel modification to impulse-response climate–carbon-cycle models to capture these physical dependencies. This simple model creates an important tool for both climate policy and climate science analysis.
Simple representations of the global coupled climate–carbon-cycle system are required for...
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