Articles | Volume 19, issue 24
https://doi.org/10.5194/bg-19-5779-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-5779-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Chris Wilson
National Centre for Earth Observation, University of Leeds, Leeds, UK
School of Earth and Environment, University of Leeds, Leeds, UK
Edward Comyn-Platt
European Centre For Medium-Range Weather Forecasts, Reading, UK
UK Centre for Ecology & Hydrology, Wallingford, UK
Garry Hayman
UK Centre for Ecology & Hydrology, Wallingford, UK
Toby R. Marthews
UK Centre for Ecology & Hydrology, Wallingford, UK
A. Anthony Bloom
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Mark F. Lunt
School of GeoSciences, The University of Edinburgh, Edinburgh, UK
Nicola Gedney
Met Office Hadley Centre, Joint Centre for Hydrometeorological Research, Wallingford, UK
Simon J. Dadson
UK Centre for Ecology & Hydrology, Wallingford, UK
School of Geography and the Environment, University of Oxford, Oxford, UK
Joe McNorton
European Centre For Medium-Range Weather Forecasts, Reading, UK
Neil Humpage
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Hartmut Boesch
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
now at: Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Martyn P. Chipperfield
National Centre for Earth Observation, University of Leeds, Leeds, UK
School of Earth and Environment, University of Leeds, Leeds, UK
Paul I. Palmer
School of GeoSciences, The University of Edinburgh, Edinburgh, UK
National Centre for Earth Observation, The University of Edinburgh, Edinburgh, UK
Dai Yamazaki
Global Hydrological Forecast Center, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
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Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Robert J. Parker, Alex Webb, Hartmut Boesch, Peter Somkuti, Rocio Barrio Guillo, Antonio Di Noia, Nikoleta Kalaitzi, Jasdeep S. Anand, Peter Bergamaschi, Frederic Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Coleen Roehl, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch
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Robert J. Parker, Chris Wilson, A. Anthony Bloom, Edward Comyn-Platt, Garry Hayman, Joe McNorton, Hartmut Boesch, and Martyn P. Chipperfield
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Rachel L. Tunnicliffe, Anita L. Ganesan, Robert J. Parker, Hartmut Boesch, Nicola Gedney, Benjamin Poulter, Zhen Zhang, Jošt V. Lavrič, David Walter, Matthew Rigby, Stephan Henne, Dickon Young, and Simon O'Doherty
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Lee de Mora, Alistair A. Sellar, Andrew Yool, Julien Palmieri, Robin S. Smith, Till Kuhlbrodt, Robert J. Parker, Jeremy Walton, Jeremy C. Blackford, and Colin G. Jones
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This preprint is open for discussion and under review for Biogeosciences (BG).
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Douglas I. Kelley, Chantelle Burton, Francesca Di Giuseppe, Matthew W. Jones, Maria L. F. Barbosa, Esther Brambleby, Joe R. McNorton, Zhongwei Liu, Anna S. I. Bradley, Katie Blackford, Eleanor Burke, Andrew Ciavarella, Enza Di Tomaso, Jonathan Eden, Igor José M. Ferreira, Lukas Fiedler, Andrew J. Hartley, Theodore R. Keeping, Seppe Lampe, Anna Lombardi, Guilherme Mataveli, Yuquan Qu, Patrícia S. Silva, Fiona R. Spuler, Carmen B. Steinmann, Miguel Ángel Torres-Vázquez, Renata Veiga, Dave van Wees, Jakob B. Wessel, Emily Wright, Bibiana Bilbao, Mathieu Bourbonnais, Gao Cong, Carlos M. Di Bella, Kebonye Dintwe, Victoria M. Donovan, Sarah Harris, Elena A. Kukavskaya, Brigitte N’Dri, Cristina Santín, Galia Selaya, Johan Sjöström, John Abatzoglou, Niels Andela, Rachel Carmenta, Emilio Chuvieco, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Meier, Mark Parrington, Mojtaba Sadegh, Jesus San-Miguel-Ayanz, Fernando Sedano, Marco Turco, Guido R. van der Werf, Sander Veraverbeke, Liana O. Anderson, Hamish Clarke, Paulo M. Fernandes, and Crystal A. Kolden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-483, https://doi.org/10.5194/essd-2025-483, 2025
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Taku Umezawa, Yukio Terao, Masahito Ueyama, Satoshi Kameyama, Mark Lunt, and James Lawrence France
EGUsphere, https://doi.org/10.5194/egusphere-2025-3285, https://doi.org/10.5194/egusphere-2025-3285, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Haolin Wang, William Maslanka, Paul I. Palmer, Martin J. Wooster, Haofan Wang, Fei Yao, Liang Feng, Kai Wu, Xiao Lu, and Shaojia Fan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2594, https://doi.org/10.5194/egusphere-2025-2594, 2025
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We examine the impact of diurnally varying African biomass burning (BB) emissions on tropospheric ozone using GEOS-Chem simulations with a high-resolution satellite-derived emission inventory. Compared to coarser temporal resolutions, incorporating diurnal variations leads to significant changes in surface ozone and atmospheric oxidation capacity. Our findings highlight the importance of accurately representing BB emission timing in chemical transport models to improve ozone predictions.
Bernhard Lehner, Mira Anand, Etienne Fluet-Chouinard, Florence Tan, Filipe Aires, George H. Allen, Philippe Bousquet, Josep G. Canadell, Nick Davidson, Meng Ding, C. Max Finlayson, Thomas Gumbricht, Lammert Hilarides, Gustaf Hugelius, Robert B. Jackson, Maartje C. Korver, Liangyun Liu, Peter B. McIntyre, Szabolcs Nagy, David Olefeldt, Tamlin M. Pavelsky, Jean-Francois Pekel, Benjamin Poulter, Catherine Prigent, Jida Wang, Thomas A. Worthington, Dai Yamazaki, Xiao Zhang, and Michele Thieme
Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, https://doi.org/10.5194/essd-17-2277-2025, 2025
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The Global Lakes and Wetlands Database (GLWD) version 2 distinguishes a total of 33 non-overlapping wetland classes, providing a static map of the world’s inland surface waters. It contains cell fractions of wetland extents per class at a grid cell resolution of ~500 m. The total combined extent of all classes including all inland and coastal waterbodies and wetlands of all inundation frequencies – that is, the maximum extent – covers 18.2 × 106 km2, equivalent to 13.4 % of total global land area.
Raphaël Savelli, Dustin Carroll, Dimitris Menemenlis, Jonathan Lauderdale, Clément Bertin, Stephanie Dutkiewicz, Manfredi Manizza, Anthony Bloom, Karel Castro-Morales, Charles E. Miller, Marc Simard, Kevin W. Bowman, and Hong Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1707, https://doi.org/10.5194/egusphere-2025-1707, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Accounting for carbon and nutrients in rivers is essential for resolving carbon dioxide (CO2) exchanges between the ocean and the atmosphere. In this study, we add the effect of present-day rivers to a pioneering global-ocean biogeochemistry model. This study highlights the challenge for global ocean numerical models to cover the complexity of the flow of water and carbon across the Land-to-Ocean Aquatic Continuum.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Alok K. Pandey, David S. Stevenson, Alcide Zhao, Richard J. Pope, Ryan Hossaini, Krishan Kumar, and Martyn P. Chipperfield
Atmos. Chem. Phys., 25, 4785–4802, https://doi.org/10.5194/acp-25-4785-2025, https://doi.org/10.5194/acp-25-4785-2025, 2025
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Nitrogen dioxide is an air pollutant largely controlled by human activity that affects ozone, methane, and aerosols. Satellite instruments can quantify column NO2 and, by carefully matching the time and location of measurements, enable evaluation of model simulations. NO2 over south and east Asia is assessed, showing that the model captures not only many features of the measurements, but also important differences that suggest model deficiencies in representing several aspects of the atmospheric chemistry of NO2.
Mark F. Lunt, Stephen J. Harris, Jorg Hacker, Ian Joynes, Tim Robertson, Simon Thompson, and James L. France
EGUsphere, https://doi.org/10.5194/egusphere-2025-1926, https://doi.org/10.5194/egusphere-2025-1926, 2025
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To ensure robust use of measurement-based approaches to estimate methane emissions from individual sites, it is important to validate the accuracy of the methods used in the field. By using co-emitted carbon dioxide, we evaluate the performance of one such quantification method at liquefied natural gas terminals. We further demonstrate the potential for a more efficient quantification approach by considering the ratio of methane to carbon dioxide concentrations.
Liang Feng, Paul Palmer, Luke Smallman, Jingfeng Xiao, Paulo Cristofanelli, Ove Hermansen, John Lee, Casper Labuschagne, Simonetta Montaguti, Steffen Noe, Stephen Platt, Xinrong Ren, Martin Steinbacher, and Irene Xueref-Remy
EGUsphere, https://doi.org/10.5194/egusphere-2025-1793, https://doi.org/10.5194/egusphere-2025-1793, 2025
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2023 saw an unexpectedly high global atmospheric CO2 growth. Satellite data reveal a role for increased emissions over the tropics. Larger emissions over eastern Brazil can be explained by warmer temperatures, while changes in rainfall and soil moisture play more of a role in emission increases elsewhere in the tropics.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Wuhu Feng, and Martyn P. Chipperfield
Atmos. Chem. Phys., 25, 4391–4401, https://doi.org/10.5194/acp-25-4391-2025, https://doi.org/10.5194/acp-25-4391-2025, 2025
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Globally, lockdowns were implemented to limit the spread of COVID-19, leading to a decrease in emissions of key air pollutants. Here, we use novel satellite data and a chemistry model to investigate the impact of the pandemic on tropospheric ozone (O3), a key pollutant, in 2020. Overall, we found substantial decreases of up to 20 %, two-thirds of which came from emission reductions, while one-third was due to a decrease in the stratospheric O3 flux into the troposphere.
Michael P. Cartwright, Jeremy J. Harrison, David P. Moore, Richard J. Pope, Martyn P. Chipperfield, Chris Wilson, and Wuhu Feng
EGUsphere, https://doi.org/10.5194/egusphere-2025-1073, https://doi.org/10.5194/egusphere-2025-1073, 2025
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We use satellite measurements to estimate quantities of a gas called carbonyl sulfide (OCS) in the atmosphere. OCS is consumed during photosynthesis, much like carbon dioxide (CO2). Our data is focused mostly over the global oceans for the year 2018, and we find it compares well with past satellite observations, ground-based measurements and modelled OCS. We hope to extend this measurement record and use it in data-driven tools in the future to better understand the carbon cycle globally.
Samantha Petch, Liang Feng, Paul Palmer, Robert P. King, Tristan Quaife, and Keith Haines
EGUsphere, https://doi.org/10.22541/essoar.173343481.12875858/v1, https://doi.org/10.22541/essoar.173343481.12875858/v1, 2025
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The growth rate of atmospheric CO2 varies year to year, mainly due to land ecosystems. Understanding factors controlling the land carbon uptake is crucial. Our study examines the link between terrestrial water storage and the CO2 growth rate from 2002–2023, revealing a strong negative correlation. We highlight the key role of tropical forests, especially in tropical America, and assess how regional contributions shift over time.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Douwang Li, Zhe Wang, Siyi Zhao, Jiankai Zhang, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2025-955, https://doi.org/10.5194/egusphere-2025-955, 2025
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We find that wind variations at the equator (QBO) modulate the occurrence of Arctic polar stratospheric clouds (PSCs), which are key contributors to ozone depletion. During westerly QBO, the PSC occurrence is significantly greater than during easterly QBO. The QBO affects PSC mainly through temperature, while H2O and HNO3 have less effect. This suggests that future climate change may affect ozone recovery if it alters the QBO pattern. This study provides a new perspective on ozone prediction.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Chlöe Natasha Schooling, Paul I. Palmer, Auke Visser, and Nicolas Bousserez
EGUsphere, https://doi.org/10.5194/egusphere-2024-3949, https://doi.org/10.5194/egusphere-2024-3949, 2025
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This study presents a new method to estimate fossil fuel CO2 (ffCO2) emissions by modelling NOx chemistry. Our regression models predict NOx chemical rates and NO2:NO ratios with R² values above 0.95 using meteorological inputs. Incorporating these regressions reduces computational time compared to traditional methods and enables integration into model inversion frameworks. This scalable approach supports global emissions monitoring and climate change mitigation efforts.
Jamal Makkor, Mathias Palm, Matthias Buschmann, Emmanuel Mahieu, Martyn P. Chipperfield, and Justus Notholt
Atmos. Meas. Tech., 18, 1105–1114, https://doi.org/10.5194/amt-18-1105-2025, https://doi.org/10.5194/amt-18-1105-2025, 2025
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During the years 1950 and 1951, Marcel Migeotte took regular solar measurements in the form of paper rolls at the Jungfraujoch site. These historical spectra proved to be valuable for atmospheric research and needed to be saved for posterity. Therefore, a digitization method which used image-processing techniques was developed to extract them from the historical paper rolls. This allowed them to be saved in a machine-readable format that is easily accessible to the scientific community.
Shihan Sun, Paul I. Palmer, Richard Siddans, Brian J. Kerridge, Lucy Ventress, Achim Edtbauer, Akima Ringsdorf, Eva Y. Pfannerstill, and Jonathan Williams
EGUsphere, https://doi.org/10.5194/egusphere-2025-778, https://doi.org/10.5194/egusphere-2025-778, 2025
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Isoprene released by plants can impact atmospheric chemistry and climate. The Amazon rainforest is a major source of isoprene. We derived isoprene emissions using satellite retrievals of isoprene columns and a chemical transport model. We evaluated our isoprene emission estimates using ground-based isoprene observations and satellite retrievals of formaldehyde. We found that using satellite retrievals of isoprene can help better understand isoprene emissions over the Amazon.
Jessica Stacey, Richard Betts, Andrew Hartley, Lina Mercado, and Nicola Gedney
EGUsphere, https://doi.org/10.5194/egusphere-2025-51, https://doi.org/10.5194/egusphere-2025-51, 2025
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Plants typically transpire less with rising atmospheric carbon dioxide, leaving more water in the ground for human use, but many future water scarcity assessments ignore this effect. We use a land surface model to examine how plant responses to carbon dioxide and climate change affect future water scarcity. Our results suggest that including these plant responses increases overall water availability for most people, highlighting the importance of their inclusion in future water scarcity studies.
Masahito Ueyama, Taku Umezawa, Yukio Terao, Mark Lunt, and James Lawrence France
EGUsphere, https://doi.org/10.5194/egusphere-2024-3926, https://doi.org/10.5194/egusphere-2024-3926, 2025
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Methane (CH4) emissions were measured in Megacity Osaka, Japan, using mobile and eddy covariance methods. The CH4 emissions were much higher than those reported in local inventories, with natural gas contributing up to 74 % of the emissions. Several CH4 sources not accounted for in current inventories were identified. These results emphasize the need for more comprehensive emissions tracking in urban areas to enhance climate change mitigation efforts.
Alexander Kurganskiy, Liang Feng, Neil Humpage, Paul I. Palmer, A. Jerome P. Woodwark, Stamatia Doniki, and Damien Weidmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-94, https://doi.org/10.5194/egusphere-2025-94, 2025
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This study introduces GEMINI-UK, the first UK-wide network using ground-based instruments to monitor net fluxes of CO2 and methane. By simulating its performance, we show that GEMINI-UK will significantly reduce uncertainties in these flux estimates, complementing data from existing tall towers and future satellite missions. The network will strengthen the UK's ability to track greenhouse gases, evaluate climate policies, and meet net-zero goals.
Sarah E. Hancock, Daniel J. Jacob, Zichong Chen, Hannah Nesser, Aaron Davitt, Daniel J. Varon, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, María Cazorla, Laura Dawidowski, Sebastián Diez, James D. East, Elise Penn, Cynthia A. Randles, John Worden, Ilse Aben, Robert J. Parker, and Joannes D. Maasakkers
Atmos. Chem. Phys., 25, 797–817, https://doi.org/10.5194/acp-25-797-2025, https://doi.org/10.5194/acp-25-797-2025, 2025
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We quantify 2021 methane emissions in South America at up to 25 km × 25 km resolution using satellite methane observations. We find a 55 % upward adjustment to anthropogenic emission inventories, including those reported to the UN Framework Convention on Climate Change under the Paris Agreement. Our estimates match inventories for Brazil, Bolivia, and Paraguay but are much higher for other countries. Livestock emissions (65 % of anthropogenic emissions) show the largest discrepancies.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Petri Clusius, Metin Baykara, Carlton Xavier, Putian Zhou, Juniper Tyree, Benjamin Foreback, Mikko Äijälä, Frans Graeffe, Tuukka Petäjä, Markku Kulmala, Pauli Paasonen, Paul I. Palmer, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2025-39, https://doi.org/10.5194/egusphere-2025-39, 2025
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Cloud condensation nuclei are necessary to form clouds, and their size distribution affects cloud properties and therefore Earth’s energy budget. This study modelled the origins of cloud condensation nuclei at SMEAR II, Hyytiälä, Finland, and found that primary emissions and new particle formation separately contribute to more than half of the condensation nuclei, but they suppress each other, leading to current concentrations. Largest condensation nuclei originated mostly from emissions.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3717, https://doi.org/10.5194/egusphere-2024-3717, 2024
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Tropospheric ozone (O3) is a harmful secondary atmospheric pollutant and an important greenhouse gas. Here, we present an in-depth analysis of lower-tropospheric sub-column O3 (LTCO3, surface – 6 km) records from three satellite products produced by the Rutherford Appleton Laboratory (RAL) over Europe between 1996 and 2017. Overall, we detect moderate negative trends in the satellite records, but corresponding model simulations and ozonesonde measurements show negligible trends.
Ryan Hossaini, David Sherry, Zihao Wang, Martyn P. Chipperfield, Wuhu Feng, David E. Oram, Karina E. Adcock, Stephen A. Montzka, Isobel J. Simpson, Andrea Mazzeo, Amber A. Leeson, Elliot Atlas, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 13457–13475, https://doi.org/10.5194/acp-24-13457-2024, https://doi.org/10.5194/acp-24-13457-2024, 2024
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DCE (1,2-dichloroethane) is an industrial chemical used to produce PVC (polyvinyl chloride). We analysed DCE production data to estimate global DCE emissions (2002–2020). The emissions were included in an atmospheric model and evaluated by comparing simulated DCE to DCE measurements in the troposphere. We show that DCE contributes ozone-depleting Cl to the stratosphere and that this has increased with increasing DCE emissions. DCE’s impact on stratospheric O3 is currently small but non-zero.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Emma Sands, Richard J. Pope, Ruth M. Doherty, Fiona M. O'Connor, Chris Wilson, and Hugh Pumphrey
Atmos. Chem. Phys., 24, 11081–11102, https://doi.org/10.5194/acp-24-11081-2024, https://doi.org/10.5194/acp-24-11081-2024, 2024
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Changes in vegetation alongside biomass burning impact regional atmospheric composition and air quality. Using satellite remote sensing, we find a clear linear relationship between forest cover and isoprene and a pronounced non-linear relationship between burned area and nitrogen dioxide in the southern Amazon, a region of substantial deforestation. These quantified relationships can be used for model evaluation and further exploration of biosphere-atmosphere interactions in Earth System Models.
Neil Humpage, Hartmut Boesch, William Okello, Jia Chen, Florian Dietrich, Mark F. Lunt, Liang Feng, Paul I. Palmer, and Frank Hase
Atmos. Meas. Tech., 17, 5679–5707, https://doi.org/10.5194/amt-17-5679-2024, https://doi.org/10.5194/amt-17-5679-2024, 2024
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We used a Bruker EM27/SUN spectrometer within an automated weatherproof enclosure to measure greenhouse gas column concentrations over a 3-month period in Jinja, Uganda. The portability of the EM27/SUN allows us to evaluate satellite and model data in locations not covered by traditional validation networks. This is of particular value in tropical Africa, where extensive terrestrial ecosystems are a significant store of carbon and play a key role in the atmospheric budgets of CO2 and CH4.
Tia R. Scarpelli, Paul I. Palmer, Mark Lunt, Ingrid Super, and Arjan Droste
Atmos. Chem. Phys., 24, 10773–10791, https://doi.org/10.5194/acp-24-10773-2024, https://doi.org/10.5194/acp-24-10773-2024, 2024
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Under the Paris Agreement, countries must track their anthropogenic greenhouse gas emissions. This study describes a method to determine self-consistent estimates for combustion emissions and natural fluxes of CO2 from atmospheric data. We report consistent estimates inferred using this approach from satellite data and ground-based data over Europe, suggesting that satellite data can be used to determine national anthropogenic CO2 emissions for countries where ground-based CO2 data are absent.
Chris Wilson, Brian J. Kerridge, Richard Siddans, David P. Moore, Lucy J. Ventress, Emily Dowd, Wuhu Feng, Martyn P. Chipperfield, and John J. Remedios
Atmos. Chem. Phys., 24, 10639–10653, https://doi.org/10.5194/acp-24-10639-2024, https://doi.org/10.5194/acp-24-10639-2024, 2024
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The leaks from the Nord Stream gas pipelines in September 2022 released a large amount of methane (CH4) into the atmosphere. We provide observational data from a satellite instrument that shows a large CH4 plume over the North Sea off the coast of Scandinavia. We use this together with atmospheric models to quantify the CH4 leaked into the atmosphere from the pipelines. We find that 219–427 Gg CH4 was emitted, making this the largest individual fossil-fuel-related CH4 leak on record.
Richard J. Pope, Fiona M. O'Connor, Mohit Dalvi, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Brice Barret, Eric Le Flochmoen, Anne Boynard, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, Catherine Wespes, and Richard Rigby
Atmos. Chem. Phys., 24, 9177–9195, https://doi.org/10.5194/acp-24-9177-2024, https://doi.org/10.5194/acp-24-9177-2024, 2024
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Ozone is a potent air pollutant in the lower troposphere, with adverse impacts on human health. Satellite records of tropospheric ozone currently show large-scale inconsistencies in long-term trends. Our detailed study of the potential factors (e.g. satellite errors, where the satellite can observe ozone) potentially driving these inconsistencies found that, in North America, Europe, and East Asia, the underlying trends are typically small with large uncertainties.
Matthew W. Jones, Douglas I. Kelley, Chantelle A. Burton, Francesca Di Giuseppe, Maria Lucia F. Barbosa, Esther Brambleby, Andrew J. Hartley, Anna Lombardi, Guilherme Mataveli, Joe R. McNorton, Fiona R. Spuler, Jakob B. Wessel, John T. Abatzoglou, Liana O. Anderson, Niels Andela, Sally Archibald, Dolors Armenteras, Eleanor Burke, Rachel Carmenta, Emilio Chuvieco, Hamish Clarke, Stefan H. Doerr, Paulo M. Fernandes, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Harris, Piyush Jain, Crystal A. Kolden, Tiina Kurvits, Seppe Lampe, Sarah Meier, Stacey New, Mark Parrington, Morgane M. G. Perron, Yuquan Qu, Natasha S. Ribeiro, Bambang H. Saharjo, Jesus San-Miguel-Ayanz, Jacquelyn K. Shuman, Veerachai Tanpipat, Guido R. van der Werf, Sander Veraverbeke, and Gavriil Xanthopoulos
Earth Syst. Sci. Data, 16, 3601–3685, https://doi.org/10.5194/essd-16-3601-2024, https://doi.org/10.5194/essd-16-3601-2024, 2024
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This inaugural State of Wildfires report catalogues extreme fires of the 2023–2024 fire season. For key events, we analyse their predictability and drivers and attribute them to climate change and land use. We provide a seasonal outlook and decadal projections. Key anomalies occurred in Canada, Greece, and western Amazonia, with other high-impact events catalogued worldwide. Climate change significantly increased the likelihood of extreme fires, and mitigation is required to lessen future risk.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
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Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Yang Li, Wuhu Feng, Xin Zhou, Yajuan Li, and Martyn P. Chipperfield
Atmos. Chem. Phys., 24, 8277–8293, https://doi.org/10.5194/acp-24-8277-2024, https://doi.org/10.5194/acp-24-8277-2024, 2024
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The Tibetan Plateau (TP), the highest and largest plateau, experiences strong surface solar UV radiation, whose excess can cause harmful influences on local biota. Hence, it is critical to study TP ozone. We find ENSO, the strongest interannual phenomenon, tends to induce tropospheric temperature change and thus modulate tropopause variability, which in turn favours ozone change over the TP. Our results have implications for a better understanding of the interannual variability of TP ozone.
Brian Nathan, Joannes D. Maasakkers, Stijn Naus, Ritesh Gautam, Mark Omara, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Alba Lorente, Tobias Borsdorff, Robert J. Parker, and Ilse Aben
Atmos. Chem. Phys., 24, 6845–6863, https://doi.org/10.5194/acp-24-6845-2024, https://doi.org/10.5194/acp-24-6845-2024, 2024
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Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features intensive oil exploitation, although production has strongly decreased in recent years. We estimate methane emissions using 2018–2020 TROPOMI satellite observations with national and regional transport models. Despite the production decrease, we find relatively constant emissions from Lake Maracaibo between 2018 and 2020, indicating that there could be large emissions from abandoned infrastructure.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Danyang Gao, Albert S. Chen, Toby Richard Marthews, and Fayyaz Ali Memon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-166, https://doi.org/10.5194/hess-2024-166, 2024
Revised manuscript not accepted
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This work evaluated how runoff, flood and drought risks might change in China due to climate change. We found annual runoff is expected to increase notably under high emission scenario. Across most months, runoff is expected to increase, particularly during summer. Wetter summers and drier winters are expected in south China, while the opposite is expected in the north. Flood risks are expected to increase in the south, while drought risks are expected to rise in the south and centre.
Yuki Kimura, Yukiko Hirabayashi, and Dai Yamazaki
EGUsphere, https://doi.org/10.22541/essoar.170365204.46854879/v1, https://doi.org/10.22541/essoar.170365204.46854879/v1, 2024
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The limited number of ensemble members causes uncertainty in future climate predictions. To address this, using multiple simulations under a single future climate scenario can increase the sample size, but data availability is limited in the scenario-based future projection experiment of climate model intercomparison projects. Our proposed method integrates multiple climate scenarios at specific temperature increases, effectively reducing uncertainty in future flood hazard assessments globally.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Alba Lorente, Zichong Chen, Xiao Lu, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Margaux Winter, Shuang Ma, A. Anthony Bloom, John R. Worden, Robert N. Stavins, and Cynthia A. Randles
Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, https://doi.org/10.5194/acp-24-5069-2024, 2024
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We quantify 2019 methane emissions in the contiguous US (CONUS) at a ≈ 25 km × 25 km resolution using satellite methane observations. We find a 13 % upward correction to the 2023 US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) for 2019, with large corrections to individual states, urban areas, and landfills. This may present a challenge for US climate policies and goals, many of which target significant reductions in methane emissions.
Margaret R. Marvin, Paul I. Palmer, Fei Yao, Mohd Talib Latif, and Md Firoz Khan
Atmos. Chem. Phys., 24, 3699–3715, https://doi.org/10.5194/acp-24-3699-2024, https://doi.org/10.5194/acp-24-3699-2024, 2024
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We use an atmospheric chemistry model to investigate aerosols emitted from fire activity across Southeast Asia. We find that the limited nature of measurements in this region leads to large uncertainties that significantly hinder the model representation of these aerosols and their impacts on air quality. As a result, the number of monthly attributable deaths is underestimated by as many as 4500, particularly in March at the peak of the mainland burning season.
Richard J. Pope, Alexandru Rap, Matilda A. Pimlott, Brice Barret, Eric Le Flochmoen, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Anne Boynard, Christian Retscher, Wuhu Feng, Richard Rigby, Sandip S. Dhomse, Catherine Wespes, and Martyn P. Chipperfield
Atmos. Chem. Phys., 24, 3613–3626, https://doi.org/10.5194/acp-24-3613-2024, https://doi.org/10.5194/acp-24-3613-2024, 2024
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Tropospheric ozone is an important short-lived climate forcer which influences the incoming solar short-wave radiation and the outgoing long-wave radiation in the atmosphere (8–15 km) where the balance between the two yields a net positive (i.e. warming) effect at the surface. Overall, we find that the tropospheric ozone radiative effect ranges between 1.21 and 1.26 W m−2 with a negligible trend (2008–2017), suggesting that tropospheric ozone influences on climate have remained stable with time.
Emily Dowd, Alistair J. Manning, Bryn Orth-Lashley, Marianne Girard, James France, Rebecca E. Fisher, Dave Lowry, Mathias Lanoisellé, Joseph R. Pitt, Kieran M. Stanley, Simon O'Doherty, Dickon Young, Glen Thistlethwaite, Martyn P. Chipperfield, Emanuel Gloor, and Chris Wilson
Atmos. Meas. Tech., 17, 1599–1615, https://doi.org/10.5194/amt-17-1599-2024, https://doi.org/10.5194/amt-17-1599-2024, 2024
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We provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys of an active gas leak detected near Cheltenham, UK. GHGSat’s emission estimates broadly agree with the surface-based mobile survey and steps were taken to fix the leak, highlighting the importance of satellite data in identifying emissions and helping to reduce our human impact on climate change.
Ross Noel Bannister and Chris Wilson
EGUsphere, https://doi.org/10.5194/egusphere-2024-655, https://doi.org/10.5194/egusphere-2024-655, 2024
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Prior information is essential for the top-down estimation of CH4 surface fluxes. Errors in the prior are correlated in time/space, but accounting for correlations can be costly. We report on an efficient scheme to represent correlations in the inverse modelling system, INVICAT. The method is tested by assimilating CH4 observations using the scheme. Our findings show that accounting for spatio-temporal correlations improve CH4 flux estimates, demonstrating that the method should be further used.
Martyn P. Chipperfield and Slimane Bekki
Atmos. Chem. Phys., 24, 2783–2802, https://doi.org/10.5194/acp-24-2783-2024, https://doi.org/10.5194/acp-24-2783-2024, 2024
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We give a personal perspective on recent issues related to the depletion of stratospheric ozone and some newly emerging challenges. We first provide a brief review of historic work on understanding the ozone layer and review ozone recovery from the effects of halogenated source gases and the Montreal Protocol. We then discuss the recent observations of ozone depletion from Australian fires in early 2020 and the Hunga Tonga–Hunga Ha'apai volcano in January 2022.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Ailish M. Graham, Richard J. Pope, Martyn P. Chipperfield, Sandip S. Dhomse, Matilda Pimlott, Wuhu Feng, Vikas Singh, Ying Chen, Oliver Wild, Ranjeet Sokhi, and Gufran Beig
Atmos. Chem. Phys., 24, 789–806, https://doi.org/10.5194/acp-24-789-2024, https://doi.org/10.5194/acp-24-789-2024, 2024
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Our paper uses novel satellite datasets and high-resolution emissions datasets alongside a back-trajectory model to investigate the balance of local and external sources influencing NOx air pollution changes in Delhi. We find in the post-monsoon season that NOx from local and non-local transport emissions contributes most to poor air quality in Delhi. Therefore, air quality mitigation strategies in Delhi and surrounding regions are used to control this issue.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Menaka Revel, Xudong Zhou, Prakat Modi, Jean-François Cretaux, Stephane Calmant, and Dai Yamazaki
Earth Syst. Sci. Data, 16, 75–88, https://doi.org/10.5194/essd-16-75-2024, https://doi.org/10.5194/essd-16-75-2024, 2024
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As satellite technology advances, there is an incredible amount of remotely sensed data for observing terrestrial water. Satellite altimetry observations of water heights can be utilized to calibrate and validate large-scale hydrodynamic models. However, because large-scale models are discontinuous, comparing satellite altimetry to predicted water surface elevation is difficult. We developed a satellite altimetry mapping procedure for high-resolution river network data.
Andrea Pazmiño, Florence Goutail, Sophie Godin-Beekmann, Alain Hauchecorne, Jean-Pierre Pommereau, Martyn P. Chipperfield, Wuhu Feng, Franck Lefèvre, Audrey Lecouffe, Michel Van Roozendael, Nis Jepsen, Georg Hansen, Rigel Kivi, Kimberly Strong, and Kaley A. Walker
Atmos. Chem. Phys., 23, 15655–15670, https://doi.org/10.5194/acp-23-15655-2023, https://doi.org/10.5194/acp-23-15655-2023, 2023
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The vortex-averaged ozone loss over the last 3 decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from the SAOZ network and MSR2 reanalysis. Three metrics were developed to compute ozone trends since 2000. The study confirms the ozone recovery in the Antarctic and shows a potential sign of quantitative detection of ozone recovery in the Arctic that needs to be robustly confirmed in the future.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jerry C. Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
Earth Syst. Dynam., 14, 1295–1315, https://doi.org/10.5194/esd-14-1295-2023, https://doi.org/10.5194/esd-14-1295-2023, 2023
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We investigate the flux of carbon from the atmosphere into the land surface and ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same change in the global-mean near-surface temperature. Using this method, we show that the choice of scenario can impact the carbon allocation to the land, ocean, and atmosphere. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, and Richard Rigby
Atmos. Chem. Phys., 23, 14933–14947, https://doi.org/10.5194/acp-23-14933-2023, https://doi.org/10.5194/acp-23-14933-2023, 2023
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Ozone is a potent air pollutant, and we present the first study to investigate long-term changes in lower tropospheric column ozone (LTCO3) from space. We have constructed a merged LTCO3 dataset from GOME-1, SCIAMACHY and OMI between 1996 and 2017. Comparing LTCO3 between the 1996–2000 and 2013–2017 5-year averages, we find significant positive increases in the tropics/sub-tropics, while in the northern mid-latitudes, we find small-scale differences.
Sandip S. Dhomse and Martyn P. Chipperfield
Earth Syst. Sci. Data, 15, 5105–5120, https://doi.org/10.5194/essd-15-5105-2023, https://doi.org/10.5194/essd-15-5105-2023, 2023
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There are no long-term stratospheric profile data sets for two very important greenhouse gases: methane (CH4) and nitrous oxide (N2O). Along with radiative feedback, these species play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite measurements with a chemical model to construct long-term gap-free profile data sets for CH4 and N2O. We aim to construct similar data sets for other important trace gases (e.g. O3, Cly, NOy species).
Ewa M. Bednarz, Ryan Hossaini, and Martyn P. Chipperfield
Atmos. Chem. Phys., 23, 13701–13711, https://doi.org/10.5194/acp-23-13701-2023, https://doi.org/10.5194/acp-23-13701-2023, 2023
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We quantify, for the first time, the time-varying impact of uncontrolled emissions of chlorinated very short-lived substances (Cl-VSLSs) on stratospheric ozone using a state-of-the-art chemistry-climate model. We demonstrate that Cl-VSLSs already have a non-negligible impact on stratospheric ozone, including a local reduction of up to ~7 DU in Arctic ozone in the cold winter of 2019/20, and any so future growth in emissions will continue to offset some of the benefits of the Montreal Protocol.
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev., 16, 6187–6209, https://doi.org/10.5194/gmd-16-6187-2023, https://doi.org/10.5194/gmd-16-6187-2023, 2023
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Development and performance of the new DEST chemistry scheme of UM–UKCA is described. The scheme extends the standard StratTrop scheme by including important updates to the halogen chemistry, thus allowing process-oriented studies of stratospheric ozone depletion and recovery, including impacts from both controlled long-lived ozone-depleting substances and emerging issues around uncontrolled, very short-lived substances. It will thus aid studies in support of future ozone assessment reports.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Richard J. Pope, Brian J. Kerridge, Martyn P. Chipperfield, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Matilda A. Pimlott, Wuhu Feng, Edward Comyn-Platt, Garry D. Hayman, Stephen R. Arnold, and Ailish M. Graham
Atmos. Chem. Phys., 23, 13235–13253, https://doi.org/10.5194/acp-23-13235-2023, https://doi.org/10.5194/acp-23-13235-2023, 2023
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In the summer of 2018, Europe experienced several persistent large-scale ozone (O3) pollution episodes. Satellite tropospheric O3 and surface O3 data recorded substantial enhancements in 2018 relative to other years. Targeted model simulations showed that meteorological processes and emissions controlled the elevated surface O3, while mid-tropospheric O3 enhancements were dominated by stratospheric O3 intrusion and advection of North Atlantic O3-rich air masses into Europe.
Yajuan Li, Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Jianchun Bian, Yuan Xia, and Dong Guo
Atmos. Chem. Phys., 23, 13029–13047, https://doi.org/10.5194/acp-23-13029-2023, https://doi.org/10.5194/acp-23-13029-2023, 2023
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For the first time a regularized multivariate regression model is used to estimate stratospheric ozone trends. Regularized regression avoids the over-fitting issue due to correlation among explanatory variables. We demonstrate that there are considerable differences in satellite-based and chemical-model-based ozone trends, highlighting large uncertainties in our understanding about ozone variability. We argue that caution is needed when interpreting results with different methods and datasets.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Michael P. Cartwright, Richard J. Pope, Jeremy J. Harrison, Martyn P. Chipperfield, Chris Wilson, Wuhu Feng, David P. Moore, and Parvadha Suntharalingam
Atmos. Chem. Phys., 23, 10035–10056, https://doi.org/10.5194/acp-23-10035-2023, https://doi.org/10.5194/acp-23-10035-2023, 2023
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A 3-D chemical transport model, TOMCAT, is used to simulate global atmospheric carbonyl sulfide (OCS) distribution. Modelled OCS compares well with satellite observations of OCS from limb-sounding satellite observations. Model simulations also compare adequately with surface and atmospheric observations and suitably capture the seasonality of OCS and background concentrations.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
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We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Elizabeth Cooper, Rich Ellis, Eleanor Blyth, and Simon Dadson
EGUsphere, https://doi.org/10.5194/egusphere-2023-1596, https://doi.org/10.5194/egusphere-2023-1596, 2023
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We have tested a different way of simulating soil moisture and river flow. Instead of dividing the land up into over 10,000 squares to run our numerical model, we cluster the land into fewer, irregular areas with similar landscape characteristics. We show that different ways of clustering the landscape produce different patterns of soil moisture. We also show that with this method we can we match observations as well as our usual gridded approach for ten times less computational resource.
Md Safat Sikder, Jida Wang, George H. Allen, Yongwei Sheng, Dai Yamazaki, Chunqiao Song, Meng Ding, Jean-François Crétaux, and Tamlin M. Pavelsky
Earth Syst. Sci. Data, 15, 3483–3511, https://doi.org/10.5194/essd-15-3483-2023, https://doi.org/10.5194/essd-15-3483-2023, 2023
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We introduce Lake-TopoCat to reveal detailed lake hydrography information. It contains the location of lake outlets, the boundary of lake catchments, and a wide suite of attributes that depict detailed lake drainage relationships. It was constructed using lake boundaries from a global lake dataset, with the help of high-resolution hydrography data. This database may facilitate a variety of applications including water quality, agriculture and fisheries, and integrated lake–river modeling.
Alice Drinkwater, Paul I. Palmer, Liang Feng, Tim Arnold, Xin Lan, Sylvia E. Michel, Robert Parker, and Hartmut Boesch
Atmos. Chem. Phys., 23, 8429–8452, https://doi.org/10.5194/acp-23-8429-2023, https://doi.org/10.5194/acp-23-8429-2023, 2023
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Changes in atmospheric methane over the last few decades are largely unexplained. Previous studies have proposed different hypotheses to explain short-term changes in atmospheric methane. We interpret observed changes in atmospheric methane and stable isotope source signatures (2004–2020). We argue that changes over this period are part of a large-scale shift from high-northern-latitude thermogenic energy emissions to tropical biogenic emissions, particularly from North Africa and South America.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Ruosi Liang, Yuzhong Zhang, Wei Chen, Peixuan Zhang, Jingran Liu, Cuihong Chen, Huiqin Mao, Guofeng Shen, Zhen Qu, Zichong Chen, Minqiang Zhou, Pucai Wang, Robert J. Parker, Hartmut Boesch, Alba Lorente, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 8039–8057, https://doi.org/10.5194/acp-23-8039-2023, https://doi.org/10.5194/acp-23-8039-2023, 2023
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We compare and evaluate East Asian methane emissions inferred from different satellite observations (GOSAT and TROPOMI). The results show discrepancies over northern India and eastern China. Independent ground-based observations are more consistent with TROPOMI-derived emissions in northern India and GOSAT-derived emissions in eastern China.
Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
Earth Syst. Sci. Data, 15, 2781–2808, https://doi.org/10.5194/essd-15-2781-2023, https://doi.org/10.5194/essd-15-2781-2023, 2023
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Res-CN fills a gap in a comprehensive and extensive dataset of reservoir-catchment characteristics for 3254 Chinese reservoirs with 512 catchment-level attributes and significantly enhanced spatial and temporal coverage (e.g., 67 % increase in water level and 225 % in storage anomaly) of time series of reservoir water level (data available for 20 % of 3254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %), supporting a wide range of applications and disciplines.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
Atmos. Chem. Phys., 23, 7363–7382, https://doi.org/10.5194/acp-23-7363-2023, https://doi.org/10.5194/acp-23-7363-2023, 2023
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Surface observations of methane show that the seasonal cycle amplitude (SCA) of methane is decreasing in the northern high latitudes (NHLs) but increased globally (1995–2020). The NHL decrease is counterintuitive, as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate changes in SCA in the NHLs. We find well-mixed methane and changes in emissions from Canada, the Middle East, and Europe are the largest contributors to the SCA in NHLs.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
Liang Feng, Paul I. Palmer, Robert J. Parker, Mark F. Lunt, and Hartmut Bösch
Atmos. Chem. Phys., 23, 4863–4880, https://doi.org/10.5194/acp-23-4863-2023, https://doi.org/10.5194/acp-23-4863-2023, 2023
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Our understanding of recent changes in atmospheric methane has defied explanation. Since 2007, the atmospheric growth of methane has accelerated to record-breaking values in 2020 and 2021. We use satellite observations of methane to show that (1) increasing emissions over the tropics are mostly responsible for these recent atmospheric changes, and (2) changes in the OH sink during the 2020 Covid-19 lockdown can explain up to 34% of changes in atmospheric methane for that year.
Antonio G. Bruno, Jeremy J. Harrison, Martyn P. Chipperfield, David P. Moore, Richard J. Pope, Christopher Wilson, Emmanuel Mahieu, and Justus Notholt
Atmos. Chem. Phys., 23, 4849–4861, https://doi.org/10.5194/acp-23-4849-2023, https://doi.org/10.5194/acp-23-4849-2023, 2023
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A 3-D chemical transport model, TOMCAT; satellite data; and ground-based observations have been used to investigate hydrogen cyanide (HCN) variability. We found that the oxidation by O(1D) drives the HCN loss in the middle stratosphere and the currently JPL-recommended OH reaction rate overestimates HCN atmospheric loss. We also evaluated two different ocean uptake schemes. We found them to be unrealistic, and we need to scale these schemes to obtain good agreement with HCN observations.
Yuki Kimura, Yukiko Hirabayashi, Yuki Kita, Xudong Zhou, and Dai Yamazaki
Hydrol. Earth Syst. Sci., 27, 1627–1644, https://doi.org/10.5194/hess-27-1627-2023, https://doi.org/10.5194/hess-27-1627-2023, 2023
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Since both the frequency and magnitude of flood will increase by climate change, information on spatial distributions of potential inundation depths (i.e., flood-hazard map) is required. We developed a method for constructing realistic future flood-hazard maps which addresses issues due to biases in climate models. A larger population is estimated to face risk in the future flood-hazard map, suggesting that only focusing on flood-frequency change could cause underestimation of future risk.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 23, 823–846, https://doi.org/10.5194/nhess-23-823-2023, https://doi.org/10.5194/nhess-23-823-2023, 2023
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In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Menaka Revel, Xudong Zhou, Dai Yamazaki, and Shinjiro Kanae
Hydrol. Earth Syst. Sci., 27, 647–671, https://doi.org/10.5194/hess-27-647-2023, https://doi.org/10.5194/hess-27-647-2023, 2023
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The capacity to discern surface water improved as satellites became more available. Because remote sensing data is discontinuous, integrating models with satellite observations will improve knowledge of water resources. However, given the current limitations (e.g., parameter errors) of water resource modeling, merging satellite data with simulations is problematic. Integrating observations and models with the unique approaches given here can lead to a better estimation of surface water dynamics.
Kai Wu, Paul I. Palmer, Dien Wu, Denis Jouglet, Liang Feng, and Tom Oda
Atmos. Meas. Tech., 16, 581–602, https://doi.org/10.5194/amt-16-581-2023, https://doi.org/10.5194/amt-16-581-2023, 2023
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We evaluate the theoretical ability of the upcoming MicroCarb satellite to estimate urban CO2 emissions over Paris and London. We explore the relative performance of alternative two-sweep and three-sweep city observing modes and take into account the impacts of cloud cover and urban biological CO2 fluxes. Our results find both the two-sweep and three-sweep observing modes are able to reduce prior flux errors by 20 %–40 % depending on the prevailing wind direction and cloud coverage.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
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A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
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Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ewa M. Bednarz, Ryan Hossaini, Martyn P. Chipperfield, N. Luke Abraham, and Peter Braesicke
Atmos. Chem. Phys., 22, 10657–10676, https://doi.org/10.5194/acp-22-10657-2022, https://doi.org/10.5194/acp-22-10657-2022, 2022
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Atmospheric impacts of chlorinated very short-lived substances (Cl-VSLS) over the first two decades of the 21st century are assessed using the UM-UKCA chemistry–climate model. Stratospheric input of Cl from Cl-VSLS is estimated at ~130 ppt in 2019. The use of model set-up with constrained meteorology significantly increases the abundance of Cl-VSLS in the lower stratosphere relative to the free-running set-up. The growth in Cl-VSLS emissions significantly impacted recent HCl and COCl2 trends.
Yajuan Li, Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Andreas Chrysanthou, Yuan Xia, and Dong Guo
Atmos. Chem. Phys., 22, 10635–10656, https://doi.org/10.5194/acp-22-10635-2022, https://doi.org/10.5194/acp-22-10635-2022, 2022
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Chemical transport models forced with (re)analysis meteorological fields are ideally suited for interpreting the influence of important physical processes on the ozone variability. We use TOMCAT forced by ECMWF ERA-Interim and ERA5 reanalysis data sets to investigate the effects of reanalysis forcing fields on ozone changes. Our results show that models forced by ERA5 reanalyses may not yet be capable of reproducing observed changes in stratospheric ozone, particularly in the lower stratosphere.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Barry G. Latter, Diane S. Knappett, Dwayne E. Heard, Lucy J. Ventress, Richard Siddans, Wuhu Feng, and Martyn P. Chipperfield
Atmos. Chem. Phys., 22, 10467–10488, https://doi.org/10.5194/acp-22-10467-2022, https://doi.org/10.5194/acp-22-10467-2022, 2022
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We present a new method to derive global information of the hydroxyl radical (OH), an important atmospheric oxidant. OH controls the lifetime of trace gases important to air quality and climate. We use satellite observations of ozone, carbon monoxide, methane and water vapour in a simple expression to derive OH around 3–4 km altitude. The derived OH compares well to model and aircraft OH data. We then apply the method to 10 years of satellite data to study the inter-annual variability of OH.
Selena Georgiou, Edward T. A. Mitchard, Bart Crezee, Paul I. Palmer, Greta C. Dargie, Sofie Sjögersten, Corneille E. N. Ewango, Ovide B. Emba, Joseph T. Kanyama, Pierre Bola, Jean-Bosco N. Ndjango, Nicholas T. Girkin, Yannick E. Bocko, Suspense A. Ifo, and Simon L. Lewis
EGUsphere, https://doi.org/10.5194/egusphere-2022-580, https://doi.org/10.5194/egusphere-2022-580, 2022
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Two major vegetation types, hardwood trees and palms, overlay the Central Congo Basin peatland complex, each dominant in different locations. We investigated the influence of terrain and climatological variables on their distribution, using a regression model, and found elevation and seasonal rainfall and temperature contribute significantly. There are indications of an optimal range of net water input for palm swamp to dominate, above and below which hardwood swamp dominates.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, https://doi.org/10.5194/hess-26-3151-2022, 2022
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Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
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We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
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This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Joe McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Luca Cantarello, Richard Engelen, Vincent Huijnen, Antje Inness, Zak Kipling, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 5961–5981, https://doi.org/10.5194/acp-22-5961-2022, https://doi.org/10.5194/acp-22-5961-2022, 2022
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Concentrations of atmospheric methane continue to grow, in recent years at an increasing rate, for unknown reasons. Using newly available satellite observations and a state-of-the-art weather prediction model we perform global estimates of emissions from hotspots at high resolution. Results show that the system can accurately report on biases in national inventories and is used to conclude that the early COVID-19 slowdown period (March–June 2020) had little impact on global methane emissions.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
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The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
Richard J. Pope, Rebecca Kelly, Eloise A. Marais, Ailish M. Graham, Chris Wilson, Jeremy J. Harrison, Savio J. A. Moniz, Mohamed Ghalaieny, Steve R. Arnold, and Martyn P. Chipperfield
Atmos. Chem. Phys., 22, 4323–4338, https://doi.org/10.5194/acp-22-4323-2022, https://doi.org/10.5194/acp-22-4323-2022, 2022
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Nitrogen oxides (NOx) are potent air pollutants which directly impact on human health. In this study, we use satellite nitrogen dioxide (NO2) data to evaluate the spatial distribution and temporal evolution of the UK official NOx emissions inventory, with reasonable agreement. We also derived satellite-based NOx emissions for several UK cities. In the case of London and Birmingham, the NAEI NOx emissions are potentially too low by >50%.
Piera Raspollini, Enrico Arnone, Flavio Barbara, Massimo Bianchini, Bruno Carli, Simone Ceccherini, Martyn P. Chipperfield, Angelika Dehn, Stefano Della Fera, Bianca Maria Dinelli, Anu Dudhia, Jean-Marie Flaud, Marco Gai, Michael Kiefer, Manuel López-Puertas, David P. Moore, Alessandro Piro, John J. Remedios, Marco Ridolfi, Harjinder Sembhi, Luca Sgheri, and Nicola Zoppetti
Atmos. Meas. Tech., 15, 1871–1901, https://doi.org/10.5194/amt-15-1871-2022, https://doi.org/10.5194/amt-15-1871-2022, 2022
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The MIPAS instrument onboard the ENVISAT satellite provided 10 years of measurements of the atmospheric emission al limb that allow for the retrieval of latitude- and altitude-resolved atmospheric composition. We describe the improvements implemented in the retrieval algorithm used for the full mission reanalysis, which allows for the generation of the global distributions of 21 atmospheric constituents plus temperature with increased accuracy with respect to previously generated data.
Elias C. Massoud, A. Anthony Bloom, Marcos Longo, John T. Reager, Paul A. Levine, and John R. Worden
Hydrol. Earth Syst. Sci., 26, 1407–1423, https://doi.org/10.5194/hess-26-1407-2022, https://doi.org/10.5194/hess-26-1407-2022, 2022
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The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step toward improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
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Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Douglas P. Finch, Paul I. Palmer, and Tianran Zhang
Atmos. Meas. Tech., 15, 721–733, https://doi.org/10.5194/amt-15-721-2022, https://doi.org/10.5194/amt-15-721-2022, 2022
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We developed a machine learning model to detect plumes of nitrogen dioxide satellite observations over 2 years. We find over 310 000 plumes, mainly over cities, industrial regions, and areas of oil and gas production. Our model performs well in comparison to other datasets and in some cases finds emissions that are not included in other datasets. This method could be used to help locate and measure emission hotspots across the globe and help inform climate policies.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
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Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Haiyue Tan, Lin Zhang, Xiao Lu, Yuanhong Zhao, Bo Yao, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 22, 1229–1249, https://doi.org/10.5194/acp-22-1229-2022, https://doi.org/10.5194/acp-22-1229-2022, 2022
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Methane is the second most important anthropogenic greenhouse gas. Understanding methane emissions and concentration growth over China in the past decade is important to support its mitigation. This study analyzes the contributions of methane emissions from different regions and sources over the globe to methane changes over China in 2007–2018. Our results show strong international transport influences and emphasize the need of intensive methane measurements covering eastern China.
Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Ryan Hossaini, Graham W. Mann, Michelle L. Santee, and Mark Weber
Atmos. Chem. Phys., 22, 903–916, https://doi.org/10.5194/acp-22-903-2022, https://doi.org/10.5194/acp-22-903-2022, 2022
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Solar flux variations associated with 11-year sunspot cycle is believed to exert important external climate forcing. As largest variations occur at shorter wavelengths such as ultra-violet part of the solar spectrum, associated changes in stratospheric ozone are thought to provide direct evidence for solar climate interaction. Until now, most of the studies reported double-peak structured solar cycle signal (SCS), but relatively new satellite data suggest only single-peak-structured SCS.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Sandip S. Dhomse, Carlo Arosio, Wuhu Feng, Alexei Rozanov, Mark Weber, and Martyn P. Chipperfield
Earth Syst. Sci. Data, 13, 5711–5729, https://doi.org/10.5194/essd-13-5711-2021, https://doi.org/10.5194/essd-13-5711-2021, 2021
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High-quality long-term ozone profile data sets are key to estimating short- and long-term ozone variability. Almost all the satellite (and chemical model) data sets show some kind of bias with respect to each other. This is because of differences in measurement methodologies as well as simplified processes in the models. We use satellite data sets and chemical model output to generate 42 years of ozone profile data sets using a random-forest machine-learning algorithm that is named ML-TOMCAT.
Paul D. Hamer, Virginie Marécal, Ryan Hossaini, Michel Pirre, Gisèle Krysztofiak, Franziska Ziska, Andreas Engel, Stephan Sala, Timo Keber, Harald Bönisch, Elliot Atlas, Kirstin Krüger, Martyn Chipperfield, Valery Catoire, Azizan A. Samah, Marcel Dorf, Phang Siew Moi, Hans Schlager, and Klaus Pfeilsticker
Atmos. Chem. Phys., 21, 16955–16984, https://doi.org/10.5194/acp-21-16955-2021, https://doi.org/10.5194/acp-21-16955-2021, 2021
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Bromoform is a stratospheric ozone-depleting gas released by seaweed and plankton transported to the stratosphere via convection in the tropics. We study the chemical interactions of bromoform and its derivatives within convective clouds using a cloud-scale model and observations. Our findings are that soluble bromine gases are efficiently washed out and removed within the convective clouds and that most bromine is transported vertically to the upper troposphere in the form of bromoform.
Margarita Choulga, Greet Janssens-Maenhout, Ingrid Super, Efisio Solazzo, Anna Agusti-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Monica Crippa, Hugo Denier van der Gon, Richard Engelen, Diego Guizzardi, Jeroen Kuenen, Joe McNorton, Gabriel Oreggioni, and Antoon Visschedijk
Earth Syst. Sci. Data, 13, 5311–5335, https://doi.org/10.5194/essd-13-5311-2021, https://doi.org/10.5194/essd-13-5311-2021, 2021
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People worry that growing man-made carbon dioxide (CO2) concentrations lead to climate change. Global models, use of observations, and datasets can help us better understand behaviour of CO2. Here a tool to compute uncertainty in man-made CO2 sources per country per year and month is presented. An example of all sources separated into seven groups (intensive and average energy, industry, humans, ground and air transport, others) is presented. Results will be used to predict CO2 concentrations.
Mark F. Lunt, Alistair J. Manning, Grant Allen, Tim Arnold, Stéphane J.-B. Bauguitte, Hartmut Boesch, Anita L. Ganesan, Aoife Grant, Carole Helfter, Eiko Nemitz, Simon J. O'Doherty, Paul I. Palmer, Joseph R. Pitt, Chris Rennick, Daniel Say, Kieran M. Stanley, Ann R. Stavert, Dickon Young, and Matt Rigby
Atmos. Chem. Phys., 21, 16257–16276, https://doi.org/10.5194/acp-21-16257-2021, https://doi.org/10.5194/acp-21-16257-2021, 2021
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We present an evaluation of the UK's methane emissions between 2013 and 2020 using a network of tall tower measurement sites. We find emissions that are consistent in both magnitude and trend with the UK's reported emissions, with a declining trend driven by a decrease in emissions from England. The impact of various components of the modelling set-up on these findings are explored through a number of sensitivity studies.
Meike K. Rotermund, Vera Bense, Martyn P. Chipperfield, Andreas Engel, Jens-Uwe Grooß, Peter Hoor, Tilman Hüneke, Timo Keber, Flora Kluge, Benjamin Schreiner, Tanja Schuck, Bärbel Vogel, Andreas Zahn, and Klaus Pfeilsticker
Atmos. Chem. Phys., 21, 15375–15407, https://doi.org/10.5194/acp-21-15375-2021, https://doi.org/10.5194/acp-21-15375-2021, 2021
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Airborne total bromine (Brtot) and tracer measurements suggest Brtot-rich air masses persistently protruded into the lower stratosphere (LS), creating a high Brtot region over the North Atlantic in fall 2017. The main source is via isentropic transport by the Asian monsoon and to a lesser extent transport across the extratropical tropopause as quantified by a Lagrange model. The transport of Brtot via Central American hurricanes is also observed. Lastly, the impact of Brtot on LS O3 is assessed.
Mehliyar Sadiq, Paul I. Palmer, Mark F. Lunt, Liang Feng, Ingrid Super, Stijn N. C. Dellaert, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-816, https://doi.org/10.5194/acp-2021-816, 2021
Publication in ACP not foreseen
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We make use of high-resolution emission inventory of CO2 and co-emitted tracers, satellite measurements, together with nested atmospheric transport model simulation, to investigate how reactive trace gases such as nitrogen dioxide and carbon monoxide can be used as proxies to determine the combustion contribution to atmospheric CO2 over Europe. We find stronger correlation in ratios of nitrogen dioxide and carbon dioxide between emission and satellite observed and modelled column concentration.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, https://doi.org/10.5194/hess-25-5287-2021, 2021
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Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Daisuke Tokuda, Hyungjun Kim, Dai Yamazaki, and Taikan Oki
Geosci. Model Dev., 14, 5669–5693, https://doi.org/10.5194/gmd-14-5669-2021, https://doi.org/10.5194/gmd-14-5669-2021, 2021
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We developed TCHOIR, a hydrologic simulation framework, to solve fluvial- and thermodynamics of the river–lake continuum. This provides an algorithm for upscaling high-resolution topography as well, which enables the representation of those interactions at the global scale. Validation against in situ and satellite observations shows that the coupled mode outperforms river- or lake-only modes. TCHOIR will contribute to elucidating the role of surface hydrology in Earth’s energy and water cycle.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Caterina Mogno, Paul I. Palmer, Christoph Knote, Fei Yao, and Timothy J. Wallington
Atmos. Chem. Phys., 21, 10881–10909, https://doi.org/10.5194/acp-21-10881-2021, https://doi.org/10.5194/acp-21-10881-2021, 2021
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We use a 3-D atmospheric chemistry model to investigate how seasonal emissions sources and meteorological conditions affect the surface distribution of fine particulate matter (PM2.5) and organic aerosol (OA) over the Indo-Gangetic Plain. We find that all seasonal mean values of PM2.5 still exceed safe air quality levels, with human emissions contributing to PM2.5 all year round, open fires during post- and pre-monsoon, and biogenic emissions during monsoon. OA contributes up to 30 % to PM2.5.
Chris Wilson, Martyn P. Chipperfield, Manuel Gloor, Robert J. Parker, Hartmut Boesch, Joey McNorton, Luciana V. Gatti, John B. Miller, Luana S. Basso, and Sarah A. Monks
Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, https://doi.org/10.5194/acp-21-10643-2021, 2021
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Methane (CH4) is an important greenhouse gas emitted from wetlands like those found in the basin of the Amazon River. Using an atmospheric model and observations from GOSAT, we quantified CH4 emissions from Amazonia during the previous decade. We found that the largest emissions came from a region in the eastern basin and that emissions there were rising faster than in other areas of South America. This finding was supported by CH4 observations made on aircraft within the basin.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Martin Keller, Daven K. Henze, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Atmos. Chem. Phys., 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021, https://doi.org/10.5194/acp-21-9545-2021, 2021
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We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Jasdeep Singh Anand, Alessandro Anav, Marcello Vitale, Daniele Peano, Nadine Unger, Xu Yue, Robert J. Parker, and Hartmut Boesch
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-125, https://doi.org/10.5194/bg-2021-125, 2021
Publication in BG not foreseen
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Ozone damages plants, which prevents them from absorbing CO2 from the atmosphere. This poses a potential threat to preventing dangerous climate change. In this work, satellite observations of forest cover, ozone, climate, and growing season are combined with an empirical model to estimate the carbon lost due to ozone exposure over Europe. The estimated carbon losses agree well with prior modelled estimates, showing for the first time that satellites can be used to better understand this effect.
Elizabeth Cooper, Eleanor Blyth, Hollie Cooper, Rich Ellis, Ewan Pinnington, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 2445–2458, https://doi.org/10.5194/hess-25-2445-2021, https://doi.org/10.5194/hess-25-2445-2021, 2021
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Soil moisture estimates from land surface models are important for forecasting floods, droughts, weather, and climate trends. We show that by combining model estimates of soil moisture with measurements from field-scale, ground-based sensors, we can improve the performance of the land surface model in predicting soil moisture values.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
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We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754, https://doi.org/10.5194/bg-18-2727-2021, https://doi.org/10.5194/bg-18-2727-2021, 2021
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Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, and Roberto Ribas
Atmos. Chem. Phys., 21, 5117–5136, https://doi.org/10.5194/acp-21-5117-2021, https://doi.org/10.5194/acp-21-5117-2021, 2021
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This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
Akash Biswal, Vikas Singh, Shweta Singh, Amit P. Kesarkar, Khaiwal Ravindra, Ranjeet S. Sokhi, Martyn P. Chipperfield, Sandip S. Dhomse, Richard J. Pope, Tanbir Singh, and Suman Mor
Atmos. Chem. Phys., 21, 5235–5251, https://doi.org/10.5194/acp-21-5235-2021, https://doi.org/10.5194/acp-21-5235-2021, 2021
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Satellite and surface observations show a reduction in NO2 levels over India during the lockdown compared to business-as-usual years. A substantial reduction, proportional to the population, was observed over the urban areas. The changes in NO2 levels at the surface during the lockdown appear to be present in the satellite observations. However, TROPOMI showed a better correlation with surface NO2 and was more sensitive to the changes than OMI because of the finer resolution.
Ewan Pinnington, Javier Amezcua, Elizabeth Cooper, Simon Dadson, Rich Ellis, Jian Peng, Emma Robinson, Ross Morrison, Simon Osborne, and Tristan Quaife
Hydrol. Earth Syst. Sci., 25, 1617–1641, https://doi.org/10.5194/hess-25-1617-2021, https://doi.org/10.5194/hess-25-1617-2021, 2021
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Land surface models are important tools for translating meteorological forecasts and reanalyses into real-world impacts at the Earth's surface. We show that the hydrological predictions, in particular soil moisture, of these models can be improved by combining them with satellite observations from the NASA SMAP mission to update uncertain parameters. We find a 22 % reduction in error at a network of in situ soil moisture sensors after combining model predictions with satellite observations.
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 Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
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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.
Xudong Zhou, Wenchao Ma, Wataru Echizenya, and Dai Yamazaki
Nat. Hazards Earth Syst. Sci., 21, 1071–1085, https://doi.org/10.5194/nhess-21-1071-2021, https://doi.org/10.5194/nhess-21-1071-2021, 2021
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This article assesses different uncertainties in the analysis of flood risk and found the runoff generated before the river routing is the primary uncertainty source. This calls for attention to be focused on selecting an appropriate runoff for the flood analysis. The uncertainties are reflected in the flood water depth, inundation area and the exposure of the population and economy to the floods.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
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We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Julia Drewer, Melissa M. Leduning, Robert I. Griffiths, Tim Goodall, Peter E. Levy, Nicholas Cowan, Edward Comynn-Platt, Garry Hayman, Justin Sentian, Noreen Majalap, and Ute M. Skiba
Biogeosciences, 18, 1559–1575, https://doi.org/10.5194/bg-18-1559-2021, https://doi.org/10.5194/bg-18-1559-2021, 2021
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In Southeast Asia, oil palm plantations have largely replaced tropical forests. The impact of this shift in land use on greenhouse gas fluxes and soil microbial communities remains uncertain. We have found emission rates of the potent greenhouse gas nitrous oxide on mineral soil to be higher from oil palm plantations than logged forest over a 2-year study and concluded that emissions have increased over the last 42 years in Sabah, with the proportion of emissions from plantations increasing.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Margaret R. Marvin, Paul I. Palmer, Barry G. Latter, Richard Siddans, Brian J. Kerridge, Mohd Talib Latif, and Md Firoz Khan
Atmos. Chem. Phys., 21, 1917–1935, https://doi.org/10.5194/acp-21-1917-2021, https://doi.org/10.5194/acp-21-1917-2021, 2021
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We use an atmospheric chemistry model in combination with satellite and surface observations to investigate how biomass burning affects tropospheric ozone over Southeast Asia during its fire seasons. We find that nitrogen oxides from biomass burning were responsible for about 30 % of the regional ozone formation potential, and we estimate that ozone from biomass burning caused more than 400 excess premature deaths in Southeast Asia during the peak burning months of March and September 2014.
Simon J. Dadson, Eleanor Blyth, Douglas Clark, Helen Davies, Richard Ellis, Huw Lewis, Toby Marthews, and Ponnambalan Rameshwaran
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-60, https://doi.org/10.5194/hess-2021-60, 2021
Manuscript not accepted for further review
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Flood prediction helps national and regional planning and real-time flood response. In this study we apply and test a new way to make wide area predictions of flooding which can be combined with weather forecasting and climate models to give faster predictions of flooded areas. By simplifying the detailed floodplain topography we can keep track of the fraction of land flooded for hazard mapping purposes. When tested this approach accurately reproduces benchmark datasets for England.
Xueying Yu, Dylan B. Millet, Kelley C. Wells, Daven K. Henze, Hansen Cao, Timothy J. Griffis, Eric A. Kort, Genevieve Plant, Malte J. Deventer, Randall K. Kolka, D. Tyler Roman, Kenneth J. Davis, Ankur R. Desai, Bianca C. Baier, Kathryn McKain, Alan C. Czarnetzki, and A. Anthony Bloom
Atmos. Chem. Phys., 21, 951–971, https://doi.org/10.5194/acp-21-951-2021, https://doi.org/10.5194/acp-21-951-2021, 2021
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Methane concentrations have doubled since 1750. The US Upper Midwest is a key region contributing to such trends, but sources are poorly understood. We collected and analyzed aircraft data to resolve spatial and timing biases in wetland and livestock emission estimates and uncover errors in inventory treatment of manure management. We highlight the importance of intensive agriculture for the regional and US methane budgets and the potential for methane mitigation through improved management.
Sudhanshu Pandey, Sander Houweling, Alba Lorente, Tobias Borsdorff, Maria Tsivlidou, A. Anthony Bloom, Benjamin Poulter, Zhen Zhang, and Ilse Aben
Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, https://doi.org/10.5194/bg-18-557-2021, 2021
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We use atmospheric methane observations from the novel TROPOspheric Monitoring Instrument (TROPOMI; Sentinel-5p) to estimate methane emissions from South Sudan's wetlands. Our emission estimates are an order of magnitude larger than the estimate of process-based wetland models. We find that this underestimation by the models is likely due to their misrepresentation of the wetlands' inundation extent and temperature dependences.
James D. Lee, Will S. Drysdale, Doug P. Finch, Shona E. Wilde, and Paul I. Palmer
Atmos. Chem. Phys., 20, 15743–15759, https://doi.org/10.5194/acp-20-15743-2020, https://doi.org/10.5194/acp-20-15743-2020, 2020
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Efforts to prevent the COVID-19 virus spreading across the globe have included travel restrictions and the closure of workplaces, leading to a significant drop in emissions of primary air pollutants. This provides for a unique opportunity to examine how air pollutant concentrations respond to an abrupt and prolonged reduction. We examine how NO2 and O3 have been affected at several urban measurement sites in the UK. We look at the change in NO2 compared to previous years and the effect on O3.
Robert J. Parker, Alex Webb, Hartmut Boesch, Peter Somkuti, Rocio Barrio Guillo, Antonio Di Noia, Nikoleta Kalaitzi, Jasdeep S. Anand, Peter Bergamaschi, Frederic Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Coleen Roehl, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch
Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, https://doi.org/10.5194/essd-12-3383-2020, 2020
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This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset. We detail the processing, validation and evaluation involved in producing these data and highlight its many applications. With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
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.
Robert J. Parker, Chris Wilson, A. Anthony Bloom, Edward Comyn-Platt, Garry Hayman, Joe McNorton, Hartmut Boesch, and Martyn P. Chipperfield
Biogeosciences, 17, 5669–5691, https://doi.org/10.5194/bg-17-5669-2020, https://doi.org/10.5194/bg-17-5669-2020, 2020
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Wetlands contribute the largest uncertainty to the atmospheric methane budget. WetCHARTs is a simple, data-driven model that estimates wetland emissions using observations of precipitation and temperature. We perform the first detailed evaluation of WetCHARTs against satellite data and find it performs well in reproducing the observed wetland methane seasonal cycle for the majority of wetland regions. In regions where it performs poorly, we highlight incorrect wetland extent as a key reason.
Sandip S. Dhomse, Graham W. Mann, Juan Carlos Antuña Marrero, Sarah E. Shallcross, Martyn P. Chipperfield, Kenneth S. Carslaw, Lauren Marshall, N. Luke Abraham, and Colin E. Johnson
Atmos. Chem. Phys., 20, 13627–13654, https://doi.org/10.5194/acp-20-13627-2020, https://doi.org/10.5194/acp-20-13627-2020, 2020
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We confirm downward adjustment of SO2 emission to simulate the Pinatubo aerosol cloud with aerosol microphysics models. Similar adjustment is also needed to simulate the El Chichón and Agung volcanic cloud, indicating potential missing removal or vertical redistribution process in models. Important inhomogeneities in the CMIP6 forcing datasets after Agung and El Chichón eruptions are difficult to reconcile. Quasi-biennial oscillation plays an important role in modifying stratospheric warming.
Rachel L. Tunnicliffe, Anita L. Ganesan, Robert J. Parker, Hartmut Boesch, Nicola Gedney, Benjamin Poulter, Zhen Zhang, Jošt V. Lavrič, David Walter, Matthew Rigby, Stephan Henne, Dickon Young, and Simon O'Doherty
Atmos. Chem. Phys., 20, 13041–13067, https://doi.org/10.5194/acp-20-13041-2020, https://doi.org/10.5194/acp-20-13041-2020, 2020
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This study quantifies Brazil’s emissions of a potent atmospheric greenhouse gas, methane. This is in the field of atmospheric modelling and uses remotely sensed data and surface measurements of methane concentrations as well as an atmospheric transport model to interpret the data. Because of Brazil’s large emissions from wetlands, agriculture and biomass burning, these emissions affect global methane concentrations and thus are of global significance.
Benjamin Birner, Martyn P. Chipperfield, Eric J. Morgan, Britton B. Stephens, Marianna Linz, Wuhu Feng, Chris Wilson, Jonathan D. Bent, Steven C. Wofsy, Jeffrey Severinghaus, and Ralph F. Keeling
Atmos. Chem. Phys., 20, 12391–12408, https://doi.org/10.5194/acp-20-12391-2020, https://doi.org/10.5194/acp-20-12391-2020, 2020
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With new high-precision observations from nine aircraft campaigns and 3-D chemical transport modeling, we show that the argon-to-nitrogen ratio (Ar / N2) in the lowermost stratosphere provides a useful constraint on the “age of air” (the time elapsed since entry of an air parcel into the stratosphere). Therefore, Ar / N2 in combination with traditional age-of-air indicators, such as CO2 and N2O, could provide new insights into atmospheric mixing and transport.
Ruqian Miao, Qi Chen, Yan Zheng, Xi Cheng, Yele Sun, Paul I. Palmer, Manish Shrivastava, Jianping Guo, Qiang Zhang, Yuhan Liu, Zhaofeng Tan, Xuefei Ma, Shiyi Chen, Limin Zeng, Keding Lu, and Yuanhang Zhang
Atmos. Chem. Phys., 20, 12265–12284, https://doi.org/10.5194/acp-20-12265-2020, https://doi.org/10.5194/acp-20-12265-2020, 2020
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In this study we evaluated the model performances for simulating secondary inorganic aerosol (SIA) and organic aerosol (OA) in PM2.5 in China against comprehensive datasets. The potential biases from factors related to meteorology, emission, chemistry, and atmospheric removal are systematically investigated. This study provides a comprehensive understanding of modeling PM2.5, which is important for studies on the effectiveness of emission control strategies.
Matthew J. Rowlinson, Alexandru Rap, Douglas S. Hamilton, Richard J. Pope, Stijn Hantson, Steve R. Arnold, Jed O. Kaplan, Almut Arneth, Martyn P. Chipperfield, Piers M. Forster, and Lars Nieradzik
Atmos. Chem. Phys., 20, 10937–10951, https://doi.org/10.5194/acp-20-10937-2020, https://doi.org/10.5194/acp-20-10937-2020, 2020
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Tropospheric ozone is an important greenhouse gas which contributes to anthropogenic climate change; however, the effect of human emissions is uncertain because pre-industrial ozone concentrations are not well understood. We use revised inventories of pre-industrial natural emissions to estimate the human contribution to changes in tropospheric ozone. We find that tropospheric ozone radiative forcing is up to 34 % lower when using improved pre-industrial biomass burning and vegetation emissions.
Lee de Mora, Alistair A. Sellar, Andrew Yool, Julien Palmieri, Robin S. Smith, Till Kuhlbrodt, Robert J. Parker, Jeremy Walton, Jeremy C. Blackford, and Colin G. Jones
Geosci. Commun., 3, 263–278, https://doi.org/10.5194/gc-3-263-2020, https://doi.org/10.5194/gc-3-263-2020, 2020
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We use time series data from the first United Kingdom Earth System Model (UKESM1) to create six procedurally generated musical pieces for piano. Each of the six pieces help to explain either a scientific principle or a practical aspect of Earth system modelling. We describe the methods that were used to create these pieces, discuss the limitations of this pilot study and list several approaches to extend and expand upon this work.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Geosci. Model Dev., 13, 3839–3862, https://doi.org/10.5194/gmd-13-3839-2020, https://doi.org/10.5194/gmd-13-3839-2020, 2020
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Systematic errors in atmospheric models pose a challenge for inverse modeling studies of methane (CH4) emissions. We evaluated the CH4 simulation in the GEOS-Chem model at the horizontal resolutions of 4° × 5° and 2° × 2.5°. Our analysis identified resolution-dependent biases in the model, which we attributed to discrepancies between the two model resolutions in vertical transport in the troposphere and in stratosphere–troposphere exchange.
Cited articles
Becker, M., Papa, F., Frappart, F., Alsdorf, D., Calmant, S., da Silva,
J. S., Prigent, C., and Seyler, F.: Satellite-Based Estimates of Surface
Water Dynamics in the Congo River Basin, Int. J. Appl. Earth Obs., 66, 196–209, https://doi.org/10.1016/j.jag.2017.11.015, 2018. a
Berchet, A., Pison, I., Chevallier, F., Paris, J.-D., Bousquet, P., Bonne, J.-L., Arshinov, M. Y., Belan, B. D., Cressot, C., Davydov, D. K., Dlugokencky, E. J., Fofonov, A. V., Galanin, A., Lavrič, J., Machida, T., Parker, R., Sasakawa, M., Spahni, R., Stocker, B. D., and Winderlich, J.: Natural and anthropogenic methane fluxes in Eurasia: a mesoscale quantification by generalized atmospheric inversion, Biogeosciences, 12, 5393–5414, https://doi.org/10.5194/bg-12-5393-2015, 2015. a
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a, b, c
Beven, K. J.: Rainfall-Runoff Modelling: The Primer, 2nd Edition, Wiley, ISBN 9780470714591, 2012. a
Beven, K. J., Kirkby, M. J., Freer, J. E., and Lamb, R.: A history of TOPMODEL, Hydrol. Earth Syst. Sci., 25, 527–549, https://doi.org/10.5194/hess-25-527-2021, 2021. a
Bloom, A. A., Palmer, P. I., Fraser, A., Reay, D. S., and Frankenberg, C.:
Large-Scale Controls of Methanogenesis Inferred from Methane and
Gravity Spaceborne Data, Science, 327, 322–325,
https://doi.org/10.1126/science.1175176, 2010. a
Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden, J. R., Weidner, R., McDonald, K. C., and Jacob, D. J.: A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0), Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, 2017a. a, b, c
Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden,
J. R., Weidner, R. J., Mcdonald, K. C., and Jacob, D. J.: CMS: Global
0.5-Deg Wetland Methane Emissions and Uncertainty (WetCHARTs
v1.0), ORNL DAAC, Oak Ridge, Tennessee, USA, WetCHARTs [data set], https://doi.org/10.3334/ORNLDAAC/1502, 2017b. a
Borges, A. V., Darchambeau, F., Teodoru, C. R., Marwick, T. R., Tamooh, F.,
Geeraert, N., Omengo, F. O., Guérin, F., Lambert, T., Morana, C., Okuku,
E., and Bouillon, S.: Globally Significant Greenhouse-Gas Emissions from
African Inland Waters, Nat. Geosci., 8, 637–642,
https://doi.org/10.1038/ngeo2486, 2015. a
Bwangoy, J.-R. B., Hansen, M. C., Roy, D. P., Grandi, G. D., and Justice,
C. O.: Wetland Mapping in the Congo Basin Using Optical and Radar
Remotely Sensed Data and Derived Topographical Indices, Remote Sens.
Environ., 114, 73–86, https://doi.org/10.1016/j.rse.2009.08.004, 2010. a
Chipperfield, M. P.: New Version of the TOMCAT/SLIMCAT off-Line
Chemical Transport Model: Intercomparison of Stratospheric Tracer
Experiments, Q. J. Roy. Meteor. Soc., 132,
1179–1203, https://doi.org/10.1256/qj.05.51, 2006. a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011. a, b, c, d, e, f
Comyn-Platt, E., Hayman, G., Huntingford, C., Chadburn, S. E., Burke, E. J.,
Harper, A. B., Collins, W. J., Webber, C. P., Powell, T., Cox, P. M., Gedney,
N., and Sitch, S.: Carbon Budgets for 1.5 and 2 ∘C Targets
Lowered by Natural Wetland and Permafrost Feedbacks, Nat. Geosci., 11,
568–573, https://doi.org/10.1038/s41561-018-0174-9, 2018. a
Crowhurst, D., Dadson, S., Peng, J., and Washington, R.: Contrasting Controls
on Congo Basin Evaporation at the Two Rainfall Peaks, Clim. Dynam.,
56, 1609–1624, https://doi.org/10.1007/s00382-020-05547-1, 2021. a
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H., and Buontempo, C.: WFDE5: bias-adjusted ERA5 reanalysis data for impact studies, Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, 2020. a
Dargie, G. C., Lewis, S. L., Lawson, I. T., Mitchard, E. T. A., Page, S. E.,
Bocko, Y. E., and Ifo, S. A.: Age, Extent and Carbon Storage of the Central
Congo Basin Peatland Complex, Nature, 542, 86–90,
https://doi.org/10.1038/nature21048, 2017. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and
Vitart, F.: The ERA-Interim Reanalysis: Configuration and Performance
of the Data Assimilation System, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Dlugokencky, E. J., Bruhwiler, L., White, J. W. C., Emmons, L. K., Novelli,
P. C., Montzka, S. A., Masarie, K. A., Lang, P. M., Crotwell, A. M., Miller,
J. B., and Gatti, L. V.: Observational Constraints on Recent Increases in the
Atmospheric CH4 Burden, Geophys. Res. Lett., 36, L18803,
https://doi.org/10.1029/2009GL039780, 2009. a
ECMWF: GOSAT Methane Data (TANSO-FTS OCPR), Climate Data Store [data set], https://doi.org/10.24381/cds.b25419f8, last access: 8 December 2022. a
Etminan, M., Myhre, G., Highwood, E. J., and Shine, K. P.: Radiative Forcing of
Carbon Dioxide, Methane, and Nitrous Oxide: A Significant Revision of the
Methane Radiative Forcing, Geophys. Res. Lett., 43, 12614–12623,
https://doi.org/10.1002/2016GL071930, 2016. a
Folberth, G. A., Staniaszek, Z., Archibald, A. T., Gedney, N., Griffiths,
P. T., Jones, C. D., O’Connor, F. M., Parker, R. J., Sellar, A. A., and
Wiltshire, A.: Description and Evaluation of an Emission-Driven and Fully
Coupled Methane Cycle in UKESM1, J. Adv. Model. Earth
Sy., 14, e2021MS002982, https://doi.org/10.1029/2021MS002982,
2022. a
Ganesan, A. L., Schwietzke, S., Poulter, B., Arnold, T., Lan, X., Rigby, M.,
Vogel, F. R., van der Werf, G. R., Janssens-Maenhout, G., Boesch, H.,
Pandey, S., Manning, A. J., Jackson, R. B., Nisbet, E. G., and Manning,
M. R.: Advancing Scientific Understanding of the Global Methane
Budget in Support of the Paris Agreement, Global Biogeochem.
Cy., 33, 1475–1512, https://doi.org/10.1029/2018GB006065, 2019. a
Gauci, V., Figueiredo, V., Gedney, N., Pangala, S. R., Stauffer, T., Weedon,
G. P., and Enrich-Prast, A.: Non-Flooded Riparian Amazon Trees Are a
Regionally Significant Methane Source, Philos. T. Roy. Soc. A, 380,
20200446, https://doi.org/10.1098/rsta.2020.0446, 2022. a
Gedney, N. and Cox, P.: The Sensitivity of Global Climate Model Simulations to
the Representation of Soil Moisture Heterogeneity, J. Hydrometeorol., 4, 1265–1275,
https://doi.org/10.1175/1525-7541(2003)004<1265:TSOGCM>2.0.CO;2, 2003. a
Gedney, N., Cox, P. M., and Huntingford, C.: Climate Feedback from Wetland
Methane Emissions, Geophys. Res. Lett., 31, L20503, https://doi.org/10.1029/2004GL020919, 2004. a, b, c
Gedney, N., Huntingford, C., Comyn-Platt, E., and Wiltshire, A.: Significant
Feedbacks of Wetland Methane Release on Climate Change and the Causes of
Their Uncertainty, Environ. Res. Lett., 14, 084027,
https://doi.org/10.1088/1748-9326/ab2726, 2019. a, b, c
Haensler, A., Saeed, F., and Jacob, D.: Assessing the Robustness of Projected
Precipitation Changes over Central Africa on the Basis of a Multitude of
Global and Regional Climate Projections, Clim. Change, 121, 349–363,
https://doi.org/10.1007/s10584-013-0863-8, 2013. a
Harper, A. B., Cox, P. M., Friedlingstein, P., Wiltshire, A. J., Jones, C. D., Sitch, S., Mercado, L. M., Groenendijk, M., Robertson, E., Kattge, J., Bönisch, G., Atkin, O. K., Bahn, M., Cornelissen, J., Niinemets, Ü., Onipchenko, V., Peñuelas, J., Poorter, L., Reich, P. B., Soudzilovskaia, N. A., and Bodegom, P. V.: Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information, Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, 2016. a
IPCC, Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan,
C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M.,
Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T.,
Yelekçi, O., Yu, R., and Zhou, B.: Climate Change 2021: The
Physical Science Basis, Contribution of Working Group I to the
Sixth Assessment Report of the Intergovernmental Panel on Climate
Change, Tech. rep., .)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, in press, https://doi.org/10.1017/9781009157896, 2021. a
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G.,
Dlugokencky, E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler,
L., Cameron-Smith, P., Castaldi, S., Chevallier, F., Feng, L., Fraser, A.,
Heimann, M., Hodson, E. L., Houweling, S., Josse, B., Fraser, P. J., Krummel,
P. B., Lamarque, J.-F., Langenfelds, R. L., Le Quéré, C., Naik, V.,
O'Doherty, S., Palmer, P. I., Pison, I., Plummer, D., Poulter, B., Prinn,
R. G., Rigby, M., Ringeval, B., Santini, M., Schmidt, M., Shindell, D. T.,
Simpson, I. J., Spahni, R., Steele, L. P., Strode, S. A., Sudo, K., Szopa,
S., van der Werf, G. R., Voulgarakis, A., van Weele, M., Weiss, R. F.,
Williams, J. E., and Zeng, G.: Three Decades of Global Methane Sources and
Sinks, Nat. Geosci., 6, 813–823, https://doi.org/10.1038/ngeo1955, 2013. a
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near Infrared
Sensor for Carbon Observation Fourier-Transform Spectrometer on the
Greenhouse Gases Observing Satellite for Greenhouse Gases Monitoring,
Appl. Opt., 48, 6716–6733, https://doi.org/10.1364/AO.48.006716, 2009. a
Lee, H., Beighley, R. E., Alsdorf, D., Jung, H. C., Shum, C. K., Duan, J., Guo,
J., Yamazaki, D., and Andreadis, K.: Characterization of Terrestrial Water
Dynamics in the Congo Basin Using GRACE and Satellite Radar
Altimetry, Remote Sens. Environ., 115, 3530–3538,
https://doi.org/10.1016/j.rse.2011.08.015, 2011. a
Lowman, L. E. L., Wei, T. M., and Barros, A. P.: Rainfall Variability,
Wetland Persistence, and Water–Carbon Cycle Coupling in
the Upper Zambezi River Basin in Southern Africa, Remote Sens., 10, 692, https://doi.org/10.3390/rs10050692, 2018. a
Lu, X., Jacob, D. J., Zhang, Y., Maasakkers, J. D., Sulprizio, M. P., Shen, L., Qu, Z., Scarpelli, T. R., Nesser, H., Yantosca, R. M., Sheng, J., Andrews, A., Parker, R. J., Boesch, H., Bloom, A. A., and Ma, S.: Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observations, Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, 2021. a
Lunt, M. F., Palmer, P. I., Feng, L., Taylor, C. M., Boesch, H., and Parker, R. J.: An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data, Atmos. Chem. Phys., 19, 14721–14740, https://doi.org/10.5194/acp-19-14721-2019, 2019. a, b
Lunt, M. F., Palmer, P. I., Lorente, A., Borsdorff, T., Landgraf, J., Parker,
R. J., and Boesch, H.: Rain-Fed Pulses of Methane from East Africa during
2018–2019 Contributed to Atmospheric Growth Rate, Environ. Res. Lett., 16, 024021, https://doi.org/10.1088/1748-9326/abd8fa, 2021. a, b, c
Maasakkers, J. D., Jacob, D. J., Sulprizio, M. P., Scarpelli, T. R., Nesser, H., Sheng, J., Zhang, Y., Lu, X., Bloom, A. A., Bowman, K. W., Worden, J. R., and Parker, R. J.: 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane, Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, 2021. a
Marthews, T. R., Dadson, S. J., Lehner, B., Abele, S., and Gedney, N.: High-resolution global topographic index values for use in large-scale hydrological modelling, Hydrol. Earth Syst. Sci., 19, 91–104, https://doi.org/10.5194/hess-19-91-2015, 2015. a, b
Marthews, T. R., Dadson, S. J., Clark, D. B., Blyth, E. M., Hayman, G. D., Yamazaki, D., Becher, O. R. E., Martínez-de la Torre, A., Prigent, C., and Jiménez, C.: Inundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulations, Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, 2022. a, b
McCarthy, T. S.: Groundwater in the Wetlands of the Okavango Delta,
Botswana, and Its Contribution to the Structure and Function of the
Ecosystem, J. Hydrol., 320, 264–282,
https://doi.org/10.1016/j.jhydrol.2005.07.045, 2006. a
McNorton, J., Chipperfield, M. P., Gloor, M., Wilson, C., Feng, W., Hayman, G. D., Rigby, M., Krummel, P. B., O'Doherty, S., Prinn, R. G., Weiss, R. F., Young, D., Dlugokencky, E., and Montzka, S. A.: Role of OH variability in the stalling of the global atmospheric CH4 growth rate from 1999 to 2006, Atmos. Chem. Phys., 16, 7943–7956, https://doi.org/10.5194/acp-16-7943-2016, 2016. a, b, c, d
Melton, J. R., Wania, R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., Bohn, T., Avis, C. A., Beerling, D. J., Chen, G., Eliseev, A. V., Denisov, S. N., Hopcroft, P. O., Lettenmaier, D. P., Riley, W. J., Singarayer, J. S., Subin, Z. M., Tian, H., Zürcher, S., Brovkin, V., van Bodegom, P. M., Kleinen, T., Yu, Z. C., and Kaplan, J. O.: Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP), Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, 2013. a, b
Mohamed, Y. and Savenije, H. H. G.: Impact of Climate Variability on the
Hydrology of the Sudd Wetland: Signals Derived from Long Term
(1900–2000) Water Balance Computations, Wetl. Ecol.
Manag., 22, 191–198, https://doi.org/10.1007/s11273-014-9337-7, 2014. a
Nisbet, E. G., Dlugokencky, E. J., and Bousquet, P.: Methane on the
Rise–Again, Science, 343, 493–495,
https://doi.org/10.1126/science.1247828, 2014. a
NOAA: Curve Fitting Methods Applied to Time Series in NOAA/ESRL/GMD, Global Monitoring Laboratory, https://gml.noaa.gov/ccgg/mbl/crvfit/, last access: 8 December 2022. a
O'Connor, F. M., Boucher, O., Gedney, N., Jones, C. D., Folberth, G. A.,
Coppell, R., Friedlingstein, P., Collins, W. J., Chappellaz, J., Ridley, J.,
and Johnson, C. E.: Possible Role of Wetlands, Permafrost, and Methane
Hydrates in the Methane Cycle under Future Climate Change: A Review, Rev. Geophys., 48, RG4005, https://doi.org/10.1029/2010RG000326, 2010. a
Palmer, P. I., Feng, L., Lunt, M. F., Parker, R. J., Bösch, H., Lan, X.,
Lorente, A., and Borsdorff, T.: The Added Value of Satellite Observations of
Methane Forunderstanding the Contemporary Methane Budget, Philos. T. Roy. Soc. A, 379, 20210106, https://doi.org/10.1098/rsta.2021.0106, 2021. a
Pandey, S., Houweling, S., Lorente, A., Borsdorff, T., Tsivlidou, M., Bloom, A. A., Poulter, B., Zhang, Z., and Aben, I.: Using satellite data to identify the methane emission controls of South Sudan's wetlands, Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, 2021. a, b
Pangala, S. R., Enrich-Prast, A., Basso, L. S., Peixoto, R. B., Bastviken,
D., Hornibrook, E. R. C., Gatti, L. V., Marotta, H., Calazans, L. S. B.,
Sakuragui, C. M., Bastos, W. R., Malm, O., Gloor, E., Miller, J. B., and
Gauci, V.: Large Emissions from Floodplain Trees Close the Amazon Methane
Budget, Nature, 552, 230–234, https://doi.org/10.1038/nature24639, 2017. a
Parker, R. and Boesch, H.: University of Leicester GOSAT Proxy XCH4 v9.0, Centre for Environmental Data Analysis, CEDA [data set], http://dx.doi.org/10.5285/, 2020. a
Parker, R., Boesch, H., Cogan, A., Fraser, A., Feng, L., Palmer, P. I.,
Messerschmidt, J., Deutscher, N., Griffith, D. W. T., Notholt, J., Wennberg,
P. O., and Wunch, D.: Methane Observations from the Greenhouse Gases
Observing SATellite: Comparison to Ground-Based TCCON Data and Model
Calculations, Geophys. Res. Lett., 38, L15807, https://doi.org/10.1029/2011GL047871, 2011. a
Parker, R. J., Boesch, H., Byckling, K., Webb, A. J., Palmer, P. I., Feng, L., Bergamaschi, P., Chevallier, F., Notholt, J., Deutscher, N., Warneke, T., Hase, F., Sussmann, R., Kawakami, S., Kivi, R., Griffith, D. W. T., and Velazco, V.: Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties, Atmos. Meas. Tech., 8, 4785–4801, https://doi.org/10.5194/amt-8-4785-2015, 2015. a
Parker, R. J., Boesch, H., McNorton, J., Comyn-Platt, E., Gloor, M., Wilson,
C., Chipperfield, M. P., Hayman, G. D., and Bloom, A. A.: Evaluating
Year-to-Year Anomalies in Tropical Wetland Methane Emissions Using Satellite
CH4 Observations, Remote Sens. Environ., 211, 261–275,
https://doi.org/10.1016/j.rse.2018.02.011, 2018. a, b
Parker, R. J., Webb, A., Boesch, H., Somkuti, P., Barrio Guillo, R., Di Noia, A., Kalaitzi, N., Anand, J. S., Bergamaschi, P., Chevallier, F., Palmer, P. I., Feng, L., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Kivi, R., Morino, I., Notholt, J., Oh, Y.-S., Ohyama, H., Petri, C., Pollard, D. F., Roehl, C., Sha, M. K., Shiomi, K., Strong, K., Sussmann, R., Té, Y., Velazco, V. A., Warneke, T., Wennberg, P. O., and Wunch, D.: A decade of GOSAT Proxy satellite CH4 observations, Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, 2020a. a, b, c
Parker, R. J., Wilson, C., Bloom, A. A., Comyn-Platt, E., Hayman, G., McNorton, J., Boesch, H., and Chipperfield, M. P.: Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations, Biogeosciences, 17, 5669–5691, https://doi.org/10.5194/bg-17-5669-2020, 2020b. a, b, c, d, e, f, g, h, i, j, k, l, m
Patra, P. K., Houweling, S., Krol, M., Bousquet, P., Belikov, D., Bergmann, D., Bian, H., Cameron-Smith, P., Chipperfield, M. P., Corbin, K., Fortems-Cheiney, A., Fraser, A., Gloor, E., Hess, P., Ito, A., Kawa, S. R., Law, R. M., Loh, Z., Maksyutov, S., Meng, L., Palmer, P. I., Prinn, R. G., Rigby, M., Saito, R., and Wilson, C.: TransCom model simulations of CH4 and related species: linking transport, surface flux and chemical loss with CH4 variability in the troposphere and lower stratosphere, Atmos. Chem. Phys., 11, 12813–12837, https://doi.org/10.5194/acp-11-12813-2011, 2011. a
Poulter, B., Bousquet, P., Canadell, J. G., Ciais, P., Peregon, A., Saunois,
M., Arora, V. K., Beerling, D. J., Brovkin, V., Jones, C. D., Joos, F.,
Gedney, N., Ito, A., Kleinen, T., Koven, C. D., McDonald, K., Melton, J. R.,
Peng, C., Peng, S., Prigent, C., Schroeder, R., Riley, W. J., Saito, M.,
Spahni, R., Tian, H., Taylor, L., Viovy, N., Wilton, D., Wiltshire, A., Xu,
X., Zhang, B., Zhang, Z., and Zhu, Q.: Global Wetland Contribution to
2000–2012 Atmospheric Methane Growth Rate Dynamics, Environ. Res. Lett., 12, 094013, https://doi.org/10.1088/1748-9326/aa8391, 2017. a
Prather, M. J., Holmes, C. D., and Hsu, J.: Reactive Greenhouse Gas Scenarios:
Systematic Exploration of Uncertainties and the Role of Atmospheric
Chemistry, Geophys. Res. Lett., 39, L09803, https://doi.org/10.1029/2012GL051440, 2012. a
Rebelo, L.-M., Senay, G. B., and McCartney, M. P.: Flood Pulsing in the
Sudd Wetland: Analysis of Seasonal Variations in Inundation and
Evaporation in South Sudan, Earth Interact., 16, 1–19,
https://doi.org/10.1175/2011EI382.1, 2012. a
Salovaara, K. J., Thessler, S., Malik, R. N., and Tuomisto, H.: Classification
of Amazonian Primary Rain Forest Vegetation Using Landsat ETM+
Satellite Imagery, Remote Sens. Environ., 97, 39–51,
https://doi.org/10.1016/j.rse.2005.04.013, 2005. a
Saunois, M., Bousquet, P., Poulter, B., Peregon, A., Ciais, P., Canadell, J. G., Dlugokencky, E. J., Etiope, G., Bastviken, D., Houweling, S., Janssens-Maenhout, G., Tubiello, F. N., Castaldi, S., Jackson, R. B., Alexe, M., Arora, V. K., Beerling, D. J., Bergamaschi, P., Blake, D. R., Brailsford, G., Brovkin, V., Bruhwiler, L., Crevoisier, C., Crill, P., Covey, K., Curry, C., Frankenberg, C., Gedney, N., Höglund-Isaksson, L., Ishizawa, M., Ito, A., Joos, F., Kim, H.-S., Kleinen, T., Krummel, P., Lamarque, J.-F., Langenfelds, R., Locatelli, R., Machida, T., Maksyutov, S., McDonald, K. C., Marshall, J., Melton, J. R., Morino, I., Naik, V., O'Doherty, S., Parmentier, F.-J. W., Patra, P. K., Peng, C., Peng, S., Peters, G. P., Pison, I., Prigent, C., Prinn, R., Ramonet, M., Riley, W. J., Saito, M., Santini, M., Schroeder, R., Simpson, I. J., Spahni, R., Steele, P., Takizawa, A., Thornton, B. F., Tian, H., Tohjima, Y., Viovy, N., Voulgarakis, A., van Weele, M., van der Werf, G. R., Weiss, R., Wiedinmyer, C., Wilton, D. J., Wiltshire, A., Worthy, D., Wunch, D., Xu, X., Yoshida, Y., Zhang, B., Zhang, Z., and Zhu, Q.: The global methane budget 2000–2012, Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, 2016. a, b
Saunois, M., Stavert, A. R., Poulter, B., Bousquet, P., Canadell, J. G., Jackson, R. B., Raymond, P. A., Dlugokencky, E. J., Houweling, S., Patra, P. K., Ciais, P., Arora, V. K., Bastviken, D., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Carlson, K. M., Carrol, M., Castaldi, S., Chandra, N., Crevoisier, C., Crill, P. M., Covey, K., Curry, C. L., Etiope, G., Frankenberg, C., Gedney, N., Hegglin, M. I., Höglund-Isaksson, L., Hugelius, G., Ishizawa, M., Ito, A., Janssens-Maenhout, G., Jensen, K. M., Joos, F., Kleinen, T., Krummel, P. B., Langenfelds, R. L., Laruelle, G. G., Liu, L., Machida, T., Maksyutov, S., McDonald, K. C., McNorton, J., Miller, P. A., Melton, J. R., Morino, I., Müller, J., Murguia-Flores, F., Naik, V., Niwa, Y., Noce, S., O'Doherty, S., Parker, R. J., Peng, C., Peng, S., Peters, G. P., Prigent, C., Prinn, R., Ramonet, M., Regnier, P., Riley, W. J., Rosentreter, J. A., Segers, A., Simpson, I. J., Shi, H., Smith, S. J., Steele, L. P., Thornton, B. F., Tian, H., Tohjima, Y., Tubiello, F. N., Tsuruta, A., Viovy, N., Voulgarakis, A., Weber, T. S., van Weele, M., van der Werf, G. R., Weiss, R. F., Worthy, D., Wunch, D., Yin, Y., Yoshida, Y., Zhang, W., Zhang, Z., Zhao, Y., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: The Global Methane Budget 2000–2017, Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, 2020. a, b, c, d, e
Schneising, O.: TROPOMI/WFMD Methane Data Product, IUP [data set], https://www.iup.uni-bremen.de/carbon_ghg/products/tropomi_wfmd/, last access: 8 December 2022. a
Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Hermans, C., Iraci, L. T., Kivi, R., Landgraf, J., Morino, I., Notholt, J., Petri, C., Pollard, D. F., Roche, S., Shiomi, K., Strong, K., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D.: A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, 2019. a
Schroeder, R., McDonald, K. C., Chapman, B. D., Jensen, K., Podest, E.,
Tessler, Z. D., Bohn, T. J., and Zimmermann, R.: Development and
Evaluation of a Multi-Year Fractional Surface Water Data Set
Derived from Active/Passive Microwave Remote Sens. Data, Remote Sens., 7, 16688–16732, https://doi.org/10.3390/rs71215843, 2015. a
Sellar, A. A., Jones, C. G., Mulcahy, J. P., Tang, Y., Yool, A., Wiltshire, A.,
O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., de
Mora, L., Kuhlbrodt, T., Rumbold, S. T., Kelley, D. I., Ellis, R., Johnson,
C. E., Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald,
A. T., Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M., Edwards,
J., Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B., Hendry,
M. A., Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble, J.,
Liddicoat, S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson, E.,
Siahaan, A., Smith, R. S., Swaminathan, R., Woodhouse, M. T., Zeng, G., and
Zerroukat, M.: UKESM1: Description and Evaluation of the U.K.
Earth System Model, J. Adv. Model. Earth Sys., 11,
4513–4558, https://doi.org/10.1029/2019MS001739, 2019. a
Sheng, J.-X., Jacob, D. J., Turner, A. J., Maasakkers, J. D., Benmergui, J., Bloom, A. A., Arndt, C., Gautam, R., Zavala-Araiza, D., Boesch, H., and Parker, R. J.: 2010–2016 methane trends over Canada, the United States, and Mexico observed by the GOSAT satellite: contributions from different source sectors, Atmos. Chem. Phys., 18, 12257–12267, https://doi.org/10.5194/acp-18-12257-2018, 2018. a
Sosnowski, A., Ghoneim, E., Burke, J. J., Hines, E., and Halls, J.: Remote
Regions, Remote Data: A Spatial Investigation of Precipitation, Dynamic Land
Covers, and Conflict in the Sudd Wetland of South Sudan, Appl.
Geograph., 69, 51–64, https://doi.org/10.1016/j.apgeog.2016.02.007, 2016. a
Stocker, B. D., Spahni, R., and Joos, F.: DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands, Geosci. Model Dev., 7, 3089–3110, https://doi.org/10.5194/gmd-7-3089-2014, 2014. a
Sutcliffe, J. and Brown, E.: Water Losses from the Sudd, Hydrol.
Sci. J., 63, 527–541, https://doi.org/10.1080/02626667.2018.1438612, 2018. a
Tathy, J. P., Cros, B., Delmas, R. A., Marenco, A., Servant, J., and Labat, M.:
Methane Emission from Flooded Forest in Central Africa, J. Geophys. Res.-Atmos., 97, 6159–6168, https://doi.org/10.1029/90JD02555, 1992. a
Thoning, K. W., Tans, P. P., and Komhyr, W. D.: Atmospheric Carbon Dioxide at
Mauna Loa Observatory: 2. Analysis of the NOAA GMCC Data,
1974–1985, J. Geophys. Res.-Atmos., 94,
8549–8565, https://doi.org/10.1029/JD094iD06p08549, 1989. a
Turetsky, M. R., Kotowska, A., Bubier, J., Dise, N. B., Crill, P., Hornibrook,
E. R. C., Minkkinen, K., Moore, T. R., Myers-Smith, I. H., Nykänen, H.,
Olefeldt, D., Rinne, J., Saarnio, S., Shurpali, N., Tuittila, E.-S.,
Waddington, J. M., White, J. R., Wickland, K. P., and Wilmking, M.: A
Synthesis of Methane Emissions from 71 Northern, Temperate, and Subtropical
Wetlands, Global Change Biol., 20, 2183–2197, https://doi.org/10.1111/gcb.12580,
2014. a, b, c
UK Met Office: JULES Source Code, metoffice [code], https://code.metoffice.gov.uk/trac/jules/log/main/trunk?rev=10836, last access: 8 December 2022a. a
UK Met Office: Rose Suites, metoffice [code], https://code.metoffice.gov.uk/trac/roses-u/, last access: 8 December 2022b. a
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and Viterbo,
P.: The WFDEI Meteorological Forcing Data Set: WATCH Forcing Data
Methodology Applied to ERA-Interim Reanalysis Data, Water Resour.
Res., 50, 7505–7514, https://doi.org/10.1002/2014WR015638, 2014.
a, b
Wilson, C., Chipperfield, M. P., Gloor, M., Parker, R. J., Boesch, H., McNorton, J., Gatti, L. V., Miller, J. B., Basso, L. S., and Monks, S. A.: Large and increasing methane emissions from eastern Amazonia derived from satellite data, 2010–2018, Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, 2021. a, b
Wolski, P., Todd, M. C., Murray-Hudson, M. A., and Tadross, M.: Multi-Decadal
Oscillations in the Hydro-Climate of the Okavango River System during the
Past and under a Changing Climate, J. Hydrol., 475, 294–305,
https://doi.org/10.1016/j.jhydrol.2012.10.018, 2012. a
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A Physically Based Description
of Floodplain Inundation Dynamics in a Global River Routing Model, Water
Resour. Res., 47, W04501, https://doi.org/10.1029/2010WR009726, 2011. a
Yan, X., Akiyama, H., Yagi, K., and Akimoto, H.: Global Estimations of the
Inventory and Mitigation Potential of Methane Emissions from Rice Cultivation
Conducted Using the 2006 Intergovernmental Panel on Climate Change
Guidelines, Global Biogeochem. Cy., 23, GB2002, https://doi.org/10.1029/2008GB003299, 2009. a
Zhang, Z., F.-C., E., Jensen, K., McDonald, K., Hugelius, G., Gumbricht, T., Carroll, M., Prigent, C., Bartsch, A., and Poulter, B.: Development of a global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M) (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.3998454, 2020. a
Zhang, Z., Fluet-Chouinard, E., Jensen, K., McDonald, K., Hugelius, G., Gumbricht, T., Carroll, M., Prigent, C., Bartsch, A., and Poulter, B.: Development of the global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M), Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, 2021. a
Zhou, X., Prigent, C., and Yamazaki, D.: Toward Improved Comparisons Between
Land-Surface-Water-Area Estimates From a Global River Model
and Satellite Observations, Water Resour. Res., 57,
e2020WR029256, https://doi.org/10.1029/2020WR029256, 2021. a
Zimba, H., Kawawa, B., Chabala, A., Phiri, W., Selsam, P., Meinhardt, M., and
Nyambe, I.: Assessment of Trends in Inundation Extent in the Barotse
Floodplain, Upper Zambezi River Basin: A Remote Sensing-Based Approach,
Journal of Hydrology-Regional Studies, 15, 149–170,
https://doi.org/10.1016/j.ejrh.2018.01.002, 2018. a
Short summary
Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
Wetlands are the largest natural source of methane, one of the most important climate gases. The...
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