Articles | Volume 7, issue 5
https://doi.org/10.5194/gmd-7-2485-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-2485-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
24 Oct 2014
Development and technical paper |
| 24 Oct 2014
Development of a variational flux inversion system (INVICAT v1.0) using the TOMCAT chemical transport model
C. Wilson
School of Geography, University of Leeds, Leeds, UK
School of Earth and Environment, University of Leeds, Leeds, UK
M. P. Chipperfield
School of Earth and Environment, University of Leeds, Leeds, UK
M. Gloor
School of Geography, University of Leeds, Leeds, UK
F. Chevallier
Laboratoire des Sciences du Climat et l'Environnement, CEA-CNRS-UVSQ, UMR8212, IPSL, Gif-sur-Yvette, France
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Sarah A. Monks, Stephen R. Arnold, Michael J. Hollaway, Richard J. Pope, Chris Wilson, Wuhu Feng, Kathryn M. Emmerson, Brian J. Kerridge, Barry L. Latter, Georgina M. Miles, Richard Siddans, and Martyn P. Chipperfield
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some model biases are found that require further investigation.
Shreeya Verma, Julia Marshall, Mark Parrington, Anna Agustí-Panareda, Sebastien Massart, Martyn P. Chipperfield, Christopher Wilson, and Christoph Gerbig
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R. Hossaini, P. K. Patra, A. A. Leeson, G. Krysztofiak, N. L. Abraham, S. J. Andrews, A. T. Archibald, J. Aschmann, E. L. Atlas, D. A. Belikov, H. Bönisch, L. J. Carpenter, S. Dhomse, M. Dorf, A. Engel, W. Feng, S. Fuhlbrügge, P. T. Griffiths, N. R. P. Harris, R. Hommel, T. Keber, K. Krüger, S. T. Lennartz, S. Maksyutov, H. Mantle, G. P. Mills, B. Miller, S. A. Montzka, F. Moore, M. A. Navarro, D. E. Oram, K. Pfeilsticker, J. A. Pyle, B. Quack, A. D. Robinson, E. Saikawa, A. Saiz-Lopez, S. Sala, B.-M. Sinnhuber, S. Taguchi, S. Tegtmeier, R. T. Lidster, C. Wilson, and F. Ziska
Atmos. Chem. Phys., 16, 9163–9187, https://doi.org/10.5194/acp-16-9163-2016, https://doi.org/10.5194/acp-16-9163-2016, 2016
Joe McNorton, Martyn P. Chipperfield, Manuel Gloor, Chris Wilson, Wuhu Feng, Garry D. Hayman, Matt Rigby, Paul B. Krummel, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, Ed Dlugokencky, and Steve A. Montzka
Atmos. Chem. Phys., 16, 7943–7956, https://doi.org/10.5194/acp-16-7943-2016, https://doi.org/10.5194/acp-16-7943-2016, 2016
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Methane (CH4) is an important greenhouse gas. The growth of atmospheric CH4 stalled from 1999 to 2006, with current explanations focussed mainly on changing surface fluxes. We combine models with observations and meteorological data to assess the atmospheric contribution to CH4 changes. We find that variations in mean atmospheric hydroxyl concentration can explain part of the stall in growth. Our study highlights the role of multi-annual variability in atmospheric chemistry in global CH4 trends.
S. A. Monks, S. R. Arnold, L. K. Emmons, K. S. Law, S. Turquety, B. N. Duncan, J. Flemming, V. Huijnen, S. Tilmes, J. Langner, J. Mao, Y. Long, J. L. Thomas, S. D. Steenrod, J. C. Raut, C. Wilson, M. P. Chipperfield, G. S. Diskin, A. Weinheimer, H. Schlager, and G. Ancellet
Atmos. Chem. Phys., 15, 3575–3603, https://doi.org/10.5194/acp-15-3575-2015, https://doi.org/10.5194/acp-15-3575-2015, 2015
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Multi-model simulations of Arctic CO, O3 and OH are evaluated using observations. Models show highly variable concentrations but the relative importance of emission regions and types is robust across the models, demonstrating the importance of biomass burning as a source. Idealised tracer experiments suggest that some of the model spread is due to variations in simulated transport from Europe in winter and from Asia throughout the year.
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
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Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
R. L. Thompson, P. K. Patra, K. Ishijima, E. Saikawa, M. Corazza, U. Karstens, C. Wilson, P. Bergamaschi, E. Dlugokencky, C. Sweeney, R. G. Prinn, R. F. Weiss, S. O'Doherty, P. J. Fraser, L. P. Steele, P. B. Krummel, M. Saunois, M. Chipperfield, and P. Bousquet
Atmos. Chem. Phys., 14, 4349–4368, https://doi.org/10.5194/acp-14-4349-2014, https://doi.org/10.5194/acp-14-4349-2014, 2014
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
Short summary
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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.
Andrea Pazmino, 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, Kaley A. Walker, and Steve Colwell
EGUsphere, https://doi.org/10.5194/egusphere-2023-788, https://doi.org/10.5194/egusphere-2023-788, 2023
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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The vortex-averaged ozone loss over the last three decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from SAOZ network and MSR2 reanalysis. Three metrics were developed to compute ozone trend since 2000. The study confirms the ozone recovery in the Antarctic and shows a first quantitative detection of ozone recovery in the Arctic that needs to be robustly confirmed in the future.
Thi-Tuyet-Trang Chau, Marion Gehlen, Nicolas Metzl, and Frédéric Chevallier
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-146, https://doi.org/10.5194/essd-2023-146, 2023
Preprint under review for ESSD
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CMEMS-LSCE leads as the first global observation-based reconstructions of six carbonate system variables for the years 1985–2021 at monthly and 0.25-degree resolutions. The high-resolution reconstructions outperform their 1-degree counterpart in reproducing horizontal and temporal gradients of observations over various oceanic regions to nearshore time series stations. New datasets can be exploited in numerous studies including mornitoring changes in ocean carbon uptake and ocean acidification.
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.
Ewa M. Bednarz, Ryan Hossaini, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2023-496, https://doi.org/10.5194/egusphere-2023-496, 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-VSLS) on stratospheric ozone using a state-of-the-art chemistry-climate model. We demonstrate that Cl-VSLS are already having a non-negligible impact on stratospheric ozone, including a 6 DU reduction of Artic 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.
Yajuan Li, Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Jianchun Bian, Yuan Xia, and Dong Guo
EGUsphere, https://doi.org/10.5194/egusphere-2023-591, https://doi.org/10.5194/egusphere-2023-591, 2023
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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For the first time a regularised multivariate regression model is used to estimate stratospheric ozone trends. Regularised regression avoids the over-fitting issue due to correlation among explanatory variables. We demonstrate that there are considerable differences in satellite and chemical model-based ozone trends highlighting large uncertainties in our understanding about ozone variability, and we argue that a caution is needed while interpreting results with different methods and data sets.
Ailish Melissa Graham, Richard J. Pope, Martyn P. Chipperfield, Sandip S. Dhomse, Matila Pimlott, Wuhu Feng, Vikas Singh, Ying Chen, Oliver Wild, Ranjeet Sokhi, and Gufran Beig
EGUsphere, https://doi.org/10.5194/egusphere-2023-382, https://doi.org/10.5194/egusphere-2023-382, 2023
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Our manuscript makes use of novel satellite data sets 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, with a focus on different emission sectors. We find that in the post-monsoon, NOx, which is mostly from the transport sector, is imported into Delhi. Therefore air quality mitigation strategies in Delhi and the surrounding regions to successfully control this issue.
Sandip S. Dhomse and Martyn P. Chipperfield
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-47, https://doi.org/10.5194/essd-2023-47, 2023
Preprint under review for ESSD
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There are no long-term stratospheric profile data set for two very important greenhouse gases : Methane (CH4) and Nitrous oxide (N2O). Along with radiative feeback, they also play key species that play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite and chemical model to construct long term gap free profile data sets for CH4 and N2O.
Cédric Bacour, Natasha MacBean, Frédéric Chevallier, Sébastien Léonard, Ernest N. Koffi, and Philippe Peylin
Biogeosciences, 20, 1089–1111, https://doi.org/10.5194/bg-20-1089-2023, https://doi.org/10.5194/bg-20-1089-2023, 2023
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The impact of assimilating different dataset combinations on regional to global-scale C budgets is explored with the ORCHIDEE model. Assimilating simultaneously multiple datasets is preferable to optimize the values of the model parameters and avoid model overfitting. The challenges in constraining soil C disequilibrium using atmospheric CO2 data are highlighted for an accurate prediction of the land sink distribution.
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.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
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, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-329, https://doi.org/10.5194/amt-2022-329, 2023
Revised manuscript accepted for AMT
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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 precessing orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors show broad consistency over a two and half year overlapping time record. This suggest that data from the two satellites may be used together for scientific analysis.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
EGUsphere, https://doi.org/10.5194/egusphere-2023-132, https://doi.org/10.5194/egusphere-2023-132, 2023
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Surface observations of methane show the seasonal cycle amplitude (SCA) of methane is decreasing in the Northern High Latitudes (NHL) but increasing globally between 1995–2020. The decrease in the NHL is counter-intuitive as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate change in SCA in the NHL. We find well-mixed methane and changes in emissions from Canada, Middle East, and Europe are the largest contributors to the SCA in NHL.
Matthew Joseph 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, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Juergen 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 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 Discuss., https://doi.org/10.5194/essd-2022-412, https://doi.org/10.5194/essd-2022-412, 2023
Preprint under review for ESSD
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential to 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 resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-19, https://doi.org/10.5194/egusphere-2023-19, 2023
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Tropical forests like Amazon are historically an important carbon sink, helping to mitigate global climate change. Using an atmospheric model and regional and global atmospheric CO2 observations, we quantified Amazonian carbon emissions between 2010 and 2018. We estimated that Amazon acted as a small carbon source to the atmosphere, mostly due to fire emissions. However, the forest uptake compensated 50 % of these fire emissions. We do not find an increasing time trend of carbon 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. Discuss., https://doi.org/10.5194/acp-2022-827, https://doi.org/10.5194/acp-2022-827, 2023
Preprint under review for ACP
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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.
Xiaojuan Lin, Ronald van der A, Jos de Laat, Henk Eskes, Frédéric Chevallier, Philippe Ciais, Zhu Deng, Yuanhao Geng, Xuanren Song, Xiliang Ni, Da Huo, Xinyu Dou, and Zhu Liu
EGUsphere, https://doi.org/10.5194/egusphere-2022-1490, https://doi.org/10.5194/egusphere-2022-1490, 2023
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Satellite observations provide evidence for CO2 emission signals from isolated power plants. We use these satellite observations to quantify emissions. We found that for power plants with multiple observations, the correlation of estimated and reported emissions is significantly improved compared to a single observation case. This demonstrates that accurate estimation of power plant emissions can be achieved by monitoring from future satellite missions with more frequent observations.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
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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.
Ewa M. Bednarz, Ryan Hossaini, Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-215, https://doi.org/10.5194/gmd-2022-215, 2022
Preprint under review for GMD
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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 hence aid studies in support of future WMO Ozone Assessment reports.
Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters
Atmos. Chem. Phys., 22, 14735–14750, https://doi.org/10.5194/acp-22-14735-2022, https://doi.org/10.5194/acp-22-14735-2022, 2022
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We assimilate MOPITT CO satellite data in the TM5-4D-Var inverse modelling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and they correlate strongly with soil moisture. Our results reveal an important role for robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.
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.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Elise Potier, Grégoire Broquet, Yilong Wang, Diego Santaren, Antoine Berchet, Isabelle Pison, Julia Marshall, Philippe Ciais, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5261–5288, https://doi.org/10.5194/amt-15-5261-2022, https://doi.org/10.5194/amt-15-5261-2022, 2022
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Atmospheric inversion at local–regional scales over Europe and pseudo-data assimilation are used to evaluate how CO2 and 14CO2 ground-based measurement networks could complement satellite CO2 imagers to monitor fossil fuel (FF) CO2 emissions. This combination significantly improves precision in the FF emission estimates in areas with a dense network but does not strongly support the separation of the FF from the biogenic signals or the spatio-temporal extrapolation of the satellite information.
François-Marie Bréon, Leslie David, Pierre Chatelanaz, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5219–5234, https://doi.org/10.5194/amt-15-5219-2022, https://doi.org/10.5194/amt-15-5219-2022, 2022
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The estimate of atmospheric CO2 from space measurement is difficult. Current methods are based on a detailed description of the atmospheric radiative transfer. These are affected by significant biases and errors and are very computer intensive. Instead we have proposed using a neural network approach. A first attempt led to confusing results. Here we provide an interpretation for these results and describe a new version that leads to high-quality estimates.
Anthony Rey-Pommier, Frédéric Chevallier, Philippe Ciais, Grégoire Broquet, Theodoros Christoudias, Jonilda Kushta, Didier Hauglustaine, and Jean Sciare
Atmos. Chem. Phys., 22, 11505–11527, https://doi.org/10.5194/acp-22-11505-2022, https://doi.org/10.5194/acp-22-11505-2022, 2022
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Emission inventories for air pollutants can be uncertain in developing countries. In order to overcome these uncertainties, we model nitrogen oxide emissions in Egypt using satellite retrievals. We detect a weekly cycle reflecting Egyptian social norms, an annual cycle consistent with electricity consumption and an activity drop due to the COVID-19 pandemic. However, discrepancies with inventories remain high, illustrating the needs for additional data to improve the potential of our method.
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.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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%.
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. Discuss., https://doi.org/10.5194/acp-2022-215, https://doi.org/10.5194/acp-2022-215, 2022
Revised manuscript accepted for ACP
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A 3-D chemical transport model, TOMCAT, is used to simulate global atmospheric carbonyl sulfide (OCS) distribution. We test the validity of using gross primary productivity to estimate OCS vegetative uptake and show that the array of emissions used offers an improvement on a control set of emissions. Model simulations also compare adequately with surface and atmospheric observations, suitably capturing seasonality of OCS and background concentration.
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.
Marine Remaud, Frédéric Chevallier, Fabienne Maignan, Sauveur Belviso, Antoine Berchet, Alexandra Parouffe, Camille Abadie, Cédric Bacour, Sinikka Lennartz, and Philippe Peylin
Atmos. Chem. Phys., 22, 2525–2552, https://doi.org/10.5194/acp-22-2525-2022, https://doi.org/10.5194/acp-22-2525-2022, 2022
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Carbonyl sulfide (COS) has been recognized as a promising indicator of the plant gross primary production (GPP). Here, we assimilate both COS and CO2 measurements into an atmospheric transport model to obtain information on GPP, plant respiration and COS budget. A possible scenario for the period 2008–2019 leads to a global COS biospheric sink of 800 GgS yr−1 and higher oceanic emissions between 400 and 600 GgS yr−1.
Thi Tuyet Trang Chau, Marion Gehlen, and Frédéric Chevallier
Biogeosciences, 19, 1087–1109, https://doi.org/10.5194/bg-19-1087-2022, https://doi.org/10.5194/bg-19-1087-2022, 2022
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Air–sea CO2 fluxes and associated uncertainty over the open ocean to coastal shelves are estimated with a new ensemble-based reconstruction of pCO2 trained on observation-based data. The regional distribution and seasonality of CO2 sources and sinks are consistent with those suggested in previous studies as well as mechanisms discussed therein. The ensemble-based uncertainty field allows identifying critical regions where improvements in pCO2 and air–sea CO2 flux estimates should be a priority.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
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.
Hélène Peiro, Sean Crowell, Andrew Schuh, David F. Baker, Chris O'Dell, Andrew R. Jacobson, Frédéric Chevallier, Junjie Liu, Annmarie Eldering, David Crisp, Feng Deng, Brad Weir, Sourish Basu, Matthew S. Johnson, Sajeev Philip, and Ian Baker
Atmos. Chem. Phys., 22, 1097–1130, https://doi.org/10.5194/acp-22-1097-2022, https://doi.org/10.5194/acp-22-1097-2022, 2022
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Satellite CO2 observations are constantly improved. We study an ensemble of different atmospheric models (inversions) from 2015 to 2018 using separate ground-based data or two versions of the OCO-2 satellite. Our study aims to determine if different satellite data corrections can yield different estimates of carbon cycle flux. A difference in the carbon budget between the two versions is found over tropical Africa, which seems to show the impact of corrections applied in satellite data.
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.
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.
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.
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.
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.
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.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
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Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
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.
Diego Santaren, Grégoire Broquet, François-Marie Bréon, Frédéric Chevallier, Denis Siméoni, Bo Zheng, and Philippe Ciais
Atmos. Meas. Tech., 14, 403–433, https://doi.org/10.5194/amt-14-403-2021, https://doi.org/10.5194/amt-14-403-2021, 2021
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Atmospheric transport inversions with synthetic data are used to assess the potential of new satellite observations of atmospheric CO2 to monitor anthropogenic emissions from regions, cities and large industrial plants. The analysis, applied to a large ensemble of sources in western Europe, shows a strong dependence of the results on different characteristics of the spaceborne instrument, on the source emission budgets and spreads, and on the wind conditions.
Leslie David, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 14, 117–132, https://doi.org/10.5194/amt-14-117-2021, https://doi.org/10.5194/amt-14-117-2021, 2021
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This paper shows that a neural network (NN) approach can be used to process spaceborne observations from the OCO-2 satellite and retrieve both surface pressure and atmospheric CO2 content. The accuracy evaluation indicates that the retrievals have an accuracy that is at least as good as those of the operational approach, which relies on complex algorithms and is computer intensive. The NN approach is therefore a promising alternative for the processing of CO2-monitoring missions.
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.
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.
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.
Yajuan Li, Martyn P. Chipperfield, Wuhu Feng, Sandip S. Dhomse, Richard J. Pope, Faquan Li, and Dong Guo
Atmos. Chem. Phys., 20, 8627–8639, https://doi.org/10.5194/acp-20-8627-2020, https://doi.org/10.5194/acp-20-8627-2020, 2020
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The Tibetan Plateau (TP) exerts important thermal and dynamical effects on atmospheric circulation, climate change as well as the ozone distribution. In this study, we use updated observations and model simulations to investigate the ozone trends and variations over the TP. Wintertime TP ozone variations are largely controlled by tropical to high-latitude transport processes, whereas summertime concentrations are a combined effect of photochemical decay and tropical processes.
Bo Zheng, Frédéric Chevallier, Philippe Ciais, Grégoire Broquet, Yilong Wang, Jinghui Lian, and Yuanhong Zhao
Atmos. Chem. Phys., 20, 8501–8510, https://doi.org/10.5194/acp-20-8501-2020, https://doi.org/10.5194/acp-20-8501-2020, 2020
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The Paris Climate Agreement requires all parties to report CO2 emissions regularly. Given the self-reporting nature of this system, it is critical to evaluate the emission reports with independent observation systems. Here we present the direct observations of city CO2 plumes from space and the quantification of CO2 emissions from these observations over the largest emitter country China. The emissions from 46 hot-spot regions representing 13 % of China's total emissions can be well constrained.
Daniele Visioni, Giovanni Pitari, Vincenzo Rizi, Marco Iarlori, Irene Cionni, Ilaria Quaglia, Hideharu Akiyoshi, Slimane Bekki, Neal Butchart, Martin Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando Garcia, Patrick Joeckel, Douglas Kinnison, Jean-François Lamarque, Marion Marchand, Martine Michou, Olaf Morgenstern, Tatsuya Nagashima, Fiona M. O'Connor, Luke D. Oman, David Plummer, Eugene Rozanov, David Saint-Martin, Robyn Schofield, John Scinocca, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Holger Tost, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-525, https://doi.org/10.5194/acp-2020-525, 2020
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In this work we analyse the trend in ozone profiles taken at L'Aquila (Italy, 42.4° N) for seventeen years, between 2000 and 2016 and compare them against already available measured ozone trends. We try to understand and explain the observed trends at various heights in light of the simulations from seventeen different model, highlighting the contribution of changes in circulation and chemical ozone loss during this time period.
James Keeble, N. Luke Abraham, Alexander T. Archibald, Martyn P. Chipperfield, Sandip Dhomse, Paul T. Griffiths, and John A. Pyle
Atmos. Chem. Phys., 20, 7153–7166, https://doi.org/10.5194/acp-20-7153-2020, https://doi.org/10.5194/acp-20-7153-2020, 2020
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The Montreal Protocol was agreed in 1987 to limit and then stop the production of man-made CFCs, which destroy stratospheric ozone. As a result, the atmospheric abundances of CFCs are now declining in the atmosphere. However, the atmospheric abundance of CFC-11 is not declining as expected under complete compliance with the Montreal Protocol. Using the UM-UKCA chemistry–climate model, we explore the impact of future unregulated production of CFC-11 on ozone recovery.
Andreas Chrysanthou, Amanda C. Maycock, and Martyn P. Chipperfield
Weather Clim. Dynam., 1, 155–174, https://doi.org/10.5194/wcd-1-155-2020, https://doi.org/10.5194/wcd-1-155-2020, 2020
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We perform 50-year-long time-slice experiments using the Met Office HadGEM3 global climate model in order to decompose the Brewer–Dobson circulation (BDC) response to an abrupt quadrupling of CO2 in three distinct components, (a) the rapid adjustment, associated with CO2 radiative effects; (b) a global uniform sea surface temperature warming; and (c) sea surface temperature patterns. This demonstrates a potential for fast and slow timescales of the response of the BDC to greenhouse gas forcing.
Clara Orbe, David A. Plummer, Darryn W. Waugh, Huang Yang, Patrick Jöckel, Douglas E. Kinnison, Beatrice Josse, Virginie Marecal, Makoto Deushi, Nathan Luke Abraham, Alexander T. Archibald, Martyn P. Chipperfield, Sandip Dhomse, Wuhu Feng, and Slimane Bekki
Atmos. Chem. Phys., 20, 3809–3840, https://doi.org/10.5194/acp-20-3809-2020, https://doi.org/10.5194/acp-20-3809-2020, 2020
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Atmospheric composition is strongly influenced by global-scale winds that are not always properly simulated in computer models. A common approach to correct for this bias is to relax or
nudgeto the observed winds. Here we systematically evaluate how well this technique performs across a large suite of chemistry–climate models in terms of its ability to reproduce key aspects of both the tropospheric and stratospheric circulations.
Alexander T. Archibald, Fiona M. O'Connor, Nathan Luke Abraham, Scott Archer-Nicholls, Martyn P. Chipperfield, Mohit Dalvi, Gerd A. Folberth, Fraser Dennison, Sandip S. Dhomse, Paul T. Griffiths, Catherine Hardacre, Alan J. Hewitt, Richard S. Hill, Colin E. Johnson, James Keeble, Marcus O. Köhler, Olaf Morgenstern, Jane P. Mulcahy, Carlos Ordóñez, Richard J. Pope, Steven T. Rumbold, Maria R. Russo, Nicholas H. Savage, Alistair Sellar, Marc Stringer, Steven T. Turnock, Oliver Wild, and Guang Zeng
Geosci. Model Dev., 13, 1223–1266, https://doi.org/10.5194/gmd-13-1223-2020, https://doi.org/10.5194/gmd-13-1223-2020, 2020
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Here we present a description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in the UK Earth System Model (UKESM1). UKCA StratTrop represents a substantial step forward compared to previous versions of UKCA. We show here that it is fully suited to the challenges of representing interactions in a coupled Earth system model and identify key areas and components for future development that will make it even better in the future.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
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The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Frédéric Chevallier, Marine Remaud, Christopher W. O'Dell, David Baker, Philippe Peylin, and Anne Cozic
Atmos. Chem. Phys., 19, 14233–14251, https://doi.org/10.5194/acp-19-14233-2019, https://doi.org/10.5194/acp-19-14233-2019, 2019
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We present a way to rate the CO2 flux estimates made from inversion of a global atmospheric transport model. Our approach relies on accurate aircraft measurements in the free troposphere. It shows that some satellite soundings can now provide inversion results that are, despite their uncertainty, comparable in credibility to traditional inversions using the accurate but sparse surface network and that these inversions are, therefore, complementary for studies of the global carbon budget.
Peter J. Rayner, Anna M. Michalak, and Frédéric Chevallier
Atmos. Chem. Phys., 19, 13911–13932, https://doi.org/10.5194/acp-19-13911-2019, https://doi.org/10.5194/acp-19-13911-2019, 2019
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This paper describes the methods for combining models and data to understand how nutrients and pollutants move through natural systems. The methods are analogous to the process of weather forecasting in which previous information is combined with new observations and a model to improve our knowledge of the internal state of the physical system. The methods appear highly diverse but the paper shows that they are all examples of a single underlying formalism.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Bo Zheng, Frederic Chevallier, Yi Yin, Philippe Ciais, Audrey Fortems-Cheiney, Merritt N. Deeter, Robert J. Parker, Yilong Wang, Helen M. Worden, and Yuanhong Zhao
Earth Syst. Sci. Data, 11, 1411–1436, https://doi.org/10.5194/essd-11-1411-2019, https://doi.org/10.5194/essd-11-1411-2019, 2019
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We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric carbon monoxide (CO) variations to its sources and sinks in order to achieve a full closure of the global CO budget during 2000–2017. We identify a declining trend in the global CO budget since 2000, driven by reduced anthropogenic emissions in the US, Europe, and China, as well as by reduced biomass burning emissions globally, especially in equatorial Africa.
Andreas Chrysanthou, Amanda C. Maycock, Martyn P. Chipperfield, Sandip Dhomse, Hella Garny, Douglas Kinnison, Hideharu Akiyoshi, Makoto Deushi, Rolando R. Garcia, Patrick Jöckel, Oliver Kirner, Giovanni Pitari, David A. Plummer, Laura Revell, Eugene Rozanov, Andrea Stenke, Taichu Y. Tanaka, Daniele Visioni, and Yousuke Yamashita
Atmos. Chem. Phys., 19, 11559–11586, https://doi.org/10.5194/acp-19-11559-2019, https://doi.org/10.5194/acp-19-11559-2019, 2019
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We perform the first multi-model comparison of the impact of nudged meteorology on the stratospheric residual circulation (RC) in chemistry–climate models. Nudging meteorology does not constrain the mean strength of RC compared to free-running simulations, and despite the lack of agreement in the mean circulation, nudging tightly constrains the inter-annual variability in the tropical upward mass flux in the lower stratosphere. In summary, nudging strongly affects the representation of RC.
Kévin Lamy, Thierry Portafaix, Béatrice Josse, Colette Brogniez, Sophie Godin-Beekmann, Hassan Bencherif, Laura Revell, Hideharu Akiyoshi, Slimane Bekki, Michaela I. Hegglin, Patrick Jöckel, Oliver Kirner, Ben Liley, Virginie Marecal, Olaf Morgenstern, Andrea Stenke, Guang Zeng, N. Luke Abraham, Alexander T. Archibald, Neil Butchart, Martyn P. Chipperfield, Glauco Di Genova, Makoto Deushi, Sandip S. Dhomse, Rong-Ming Hu, Douglas Kinnison, Michael Kotkamp, Richard McKenzie, Martine Michou, Fiona M. O'Connor, Luke D. Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Eugene Rozanov, David Saint-Martin, Kengo Sudo, Taichu Y. Tanaka, Daniele Visioni, and Kohei Yoshida
Atmos. Chem. Phys., 19, 10087–10110, https://doi.org/10.5194/acp-19-10087-2019, https://doi.org/10.5194/acp-19-10087-2019, 2019
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In this study, we simulate the ultraviolet radiation evolution during the 21st century on Earth's surface using the output from several numerical models which participated in the Chemistry-Climate Model Initiative. We present four possible futures which depend on greenhouse gases emissions. The role of ozone-depleting substances, greenhouse gases and aerosols are investigated. Our results emphasize the important role of aerosols for future ultraviolet radiation in the Northern Hemisphere.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Richard Coppell, Emanuel Gloor, and Joseph Holden
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-51, https://doi.org/10.5194/gmd-2019-51, 2019
Publication in GMD not foreseen
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(1) We developed a new Sphagnum model for ecosystem exchange. (2) The model is implemented in TRIFFID which is part of the JULES land surface model. (3) Outputs compare well to empirical field data. (4) JULES can now better incorporate peatland-climate feedbacks.
Matthew J. Rowlinson, Alexandru Rap, Stephen R. Arnold, Richard J. Pope, Martyn P. Chipperfield, Joe McNorton, Piers Forster, Hamish Gordon, Kirsty J. Pringle, Wuhu Feng, Brian J. Kerridge, Barry L. Latter, and Richard Siddans
Atmos. Chem. Phys., 19, 8669–8686, https://doi.org/10.5194/acp-19-8669-2019, https://doi.org/10.5194/acp-19-8669-2019, 2019
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Wildfires and meteorology have a substantial effect on atmospheric concentrations of greenhouse gases such as methane and ozone. During the 1997 El Niño event, unusually large fire emissions indirectly increased global methane through carbon monoxide emission, which decreased the oxidation capacity of the atmosphere. There were also large regional changes to tropospheric ozone concentrations, but contrasting effects of fire and meteorology resulted in a small change to global radiative forcing.
Anna Agustí-Panareda, Michail Diamantakis, Sébastien Massart, Frédéric Chevallier, Joaquín Muñoz-Sabater, Jérôme Barré, Roger Curcoll, Richard Engelen, Bavo Langerock, Rachel M. Law, Zoë Loh, Josep Anton Morguí, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Coleen Roehl, Alex T. Vermeulen, Thorsten Warneke, and Debra Wunch
Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, https://doi.org/10.5194/acp-19-7347-2019, 2019
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This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO2 patterns associated with evolving weather. The modelling of CO2 weather is crucial to interpret the variability from ground-based and satellite CO2 observations, which can then be used to infer CO2 fluxes in atmospheric inversions. The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO2 flux distribution.
Felix R. Vogel, Matthias Frey, Johannes Staufer, Frank Hase, Grégoire Broquet, Irène Xueref-Remy, Frédéric Chevallier, Philippe Ciais, Mahesh Kumar Sha, Pascale Chelin, Pascal Jeseck, Christof Janssen, Yao Té, Jochen Groß, Thomas Blumenstock, Qiansi Tu, and Johannes Orphal
Atmos. Chem. Phys., 19, 3271–3285, https://doi.org/10.5194/acp-19-3271-2019, https://doi.org/10.5194/acp-19-3271-2019, 2019
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Providing timely information on greenhouse gas emissions to stakeholders at sub-national scale is an emerging challenge and understanding urban CO2 levels is one key aspect. This study uses atmospheric observations of total column CO2 and compares them to numerical simulations to investigate CO2 levels in the Paris metropolitan area due to natural fluxes and anthropogenic emissions. Our measurements reveal the influence of locally added CO2, which our model is also able to predict.
Evgenia Galytska, Alexey Rozanov, Martyn P. Chipperfield, Sandip. S. Dhomse, Mark Weber, Carlo Arosio, Wuhu Feng, and John P. Burrows
Atmos. Chem. Phys., 19, 767–783, https://doi.org/10.5194/acp-19-767-2019, https://doi.org/10.5194/acp-19-767-2019, 2019
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In this study we analysed ozone changes in the tropical mid-stratosphere as observed by the SCIAMACHY instrument during 2004–2012. We used simulations from TOMCAT model with different chemical and dynamical forcings to reveal primary causes of ozone changes. We also considered measured NO2 and modelled NOx, NOx, and N2O data. With modelled AoA data we identified seasonal changes in the upwelling speed and explained how those changes affect N2O chemistry which leads to observed ozone changes.
Debora Griffin, Kaley A. Walker, Ingo Wohltmann, Sandip S. Dhomse, Markus Rex, Martyn P. Chipperfield, Wuhu Feng, Gloria L. Manney, Jane Liu, and David Tarasick
Atmos. Chem. Phys., 19, 577–601, https://doi.org/10.5194/acp-19-577-2019, https://doi.org/10.5194/acp-19-577-2019, 2019
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Ozone in the stratosphere is important to protect the Earth from UV radiation. Using measurements taken by the Atmospheric Chemistry Experiment satellite between 2005 and 2013, we examine different methods to calculate the ozone loss in the high Arctic and establish the altitude at which most of the ozone is destroyed. Our results show that the different methods agree within the uncertainties. Recommendations are made on which methods are most appropriate to use.
Benjamin Gaubert, Britton B. Stephens, Sourish Basu, Frédéric Chevallier, Feng Deng, Eric A. Kort, Prabir K. Patra, Wouter Peters, Christian Rödenbeck, Tazu Saeki, David Schimel, Ingrid Van der Laan-Luijkx, Steven Wofsy, and Yi Yin
Biogeosciences, 16, 117–134, https://doi.org/10.5194/bg-16-117-2019, https://doi.org/10.5194/bg-16-117-2019, 2019
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We have compared global carbon budgets calculated from numerical inverse models and CO2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO2 from aircraft measurements. We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.
Joe McNorton, Chris Wilson, Manuel Gloor, Rob J. Parker, Hartmut Boesch, Wuhu Feng, Ryan Hossaini, and Martyn P. Chipperfield
Atmos. Chem. Phys., 18, 18149–18168, https://doi.org/10.5194/acp-18-18149-2018, https://doi.org/10.5194/acp-18-18149-2018, 2018
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Since 2007 atmospheric methane (CH4) has been unexpectedly increasing following a 6-year hiatus. We have used an atmospheric model to attribute regional sources and global sinks of CH4 using observations for the 2003–2015 period. Model results show the renewed growth is best explained by decreased atmospheric removal, decreased biomass burning emissions, and an increased energy sector (mainly from Africa–Middle East and Southern Asia–Oceania) and wetland emissions (mainly from northern Eurasia).
Christopher W. O'Dell, Annmarie Eldering, Paul O. Wennberg, David Crisp, Michael R. Gunson, Brendan Fisher, Christian Frankenberg, Matthäus Kiel, Hannakaisa Lindqvist, Lukas Mandrake, Aronne Merrelli, Vijay Natraj, Robert R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Drouin, Fabiano Oyafuso, Albert Chang, James McDuffie, Michael Smyth, David F. Baker, Sourish Basu, Frédéric Chevallier, Sean M. R. Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, Coleen M. Roehl, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Osamu Uchino, and Voltaire A. Velazco
Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, https://doi.org/10.5194/amt-11-6539-2018, 2018
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
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The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Marine Remaud, Frédéric Chevallier, Anne Cozic, Xin Lin, and Philippe Bousquet
Geosci. Model Dev., 11, 4489–4513, https://doi.org/10.5194/gmd-11-4489-2018, https://doi.org/10.5194/gmd-11-4489-2018, 2018
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We compare several versions of a global atmospheric transport model for the simulation of CO2. The representation of subgrid-scale processes modulates the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere. It has the largest impact over Brazil. Refining the horizontal resolution improves the simulation near emission hotspots or along the coastlines. The sensitivities to the land surface model and to the increase in vertical resolution are marginal.
Paul I. Palmer, Simon O'Doherty, Grant Allen, Keith Bower, Hartmut Bösch, Martyn P. Chipperfield, Sarah Connors, Sandip Dhomse, Liang Feng, Douglas P. Finch, Martin W. Gallagher, Emanuel Gloor, Siegfried Gonzi, Neil R. P. Harris, Carole Helfter, Neil Humpage, Brian Kerridge, Diane Knappett, Roderic L. Jones, Michael Le Breton, Mark F. Lunt, Alistair J. Manning, Stephan Matthiesen, Jennifer B. A. Muller, Neil Mullinger, Eiko Nemitz, Sebastian O'Shea, Robert J. Parker, Carl J. Percival, Joseph Pitt, Stuart N. Riddick, Matthew Rigby, Harjinder Sembhi, Richard Siddans, Robert L. Skelton, Paul Smith, Hannah Sonderfeld, Kieran Stanley, Ann R. Stavert, Angelina Wenger, Emily White, Christopher Wilson, and Dickon Young
Atmos. Chem. Phys., 18, 11753–11777, https://doi.org/10.5194/acp-18-11753-2018, https://doi.org/10.5194/acp-18-11753-2018, 2018
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This paper provides an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) experiment. GAUGE was designed to quantify nationwide GHG emissions of the UK, bringing together measurements and atmospheric transport models. This novel experiment is the first of its kind. We anticipate it will inform the blueprint for countries that are building a measurement infrastructure in preparation for global stocktakes, which are a key part of the Paris Agreement.
Birgit Hassler, Stefanie Kremser, Greg E. Bodeker, Jared Lewis, Kage Nesbit, Sean M. Davis, Martyn P. Chipperfield, Sandip S. Dhomse, and Martin Dameris
Earth Syst. Sci. Data, 10, 1473–1490, https://doi.org/10.5194/essd-10-1473-2018, https://doi.org/10.5194/essd-10-1473-2018, 2018
Maarten Krol, Marco de Bruine, Lars Killaars, Huug Ouwersloot, Andrea Pozzer, Yi Yin, Frederic Chevallier, Philippe Bousquet, Prabir Patra, Dmitry Belikov, Shamil Maksyutov, Sandip Dhomse, Wuhu Feng, and Martyn P. Chipperfield
Geosci. Model Dev., 11, 3109–3130, https://doi.org/10.5194/gmd-11-3109-2018, https://doi.org/10.5194/gmd-11-3109-2018, 2018
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The TransCom inter-comparison project regularly carries out studies to quantify errors in simulated atmospheric transport. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, six models simulated five tracers from which atmospheric transport times can easily be deduced. Results highlight that inter-model differences associated with atmospheric transport are still large and require further analysis.
Jens-Uwe Grooß, Rolf Müller, Reinhold Spang, Ines Tritscher, Tobias Wegner, Martyn P. Chipperfield, Wuhu Feng, Douglas E. Kinnison, and Sasha Madronich
Atmos. Chem. Phys., 18, 8647–8666, https://doi.org/10.5194/acp-18-8647-2018, https://doi.org/10.5194/acp-18-8647-2018, 2018
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We investigate a discrepancy between model simulations and observations of HCl in the dark polar stratosphere. In early winter, the less-well-studied period of the onset of chlorine activation, observations show a much faster depletion of HCl than simulations of three models. This points to some unknown process that is currently not represented in the models. Various hypotheses for potential causes are investigated that partly reduce the discrepancy. The impact on polar ozone depletion is low.
Richard J. Pope, Martyn P. Chipperfield, Stephen R. Arnold, Norbert Glatthor, Wuhu Feng, Sandip S. Dhomse, Brian J. Kerridge, Barry G. Latter, and Richard Siddans
Atmos. Chem. Phys., 18, 8389–8408, https://doi.org/10.5194/acp-18-8389-2018, https://doi.org/10.5194/acp-18-8389-2018, 2018
Sandip S. Dhomse, Douglas Kinnison, Martyn P. Chipperfield, Ross J. Salawitch, Irene Cionni, Michaela I. Hegglin, N. Luke Abraham, Hideharu Akiyoshi, Alex T. Archibald, Ewa M. Bednarz, Slimane Bekki, Peter Braesicke, Neal Butchart, Martin Dameris, Makoto Deushi, Stacey Frith, Steven C. Hardiman, Birgit Hassler, Larry W. Horowitz, Rong-Ming Hu, Patrick Jöckel, Beatrice Josse, Oliver Kirner, Stefanie Kremser, Ulrike Langematz, Jared Lewis, Marion Marchand, Meiyun Lin, Eva Mancini, Virginie Marécal, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Laura E. Revell, Eugene Rozanov, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Simone Tilmes, Daniele Visioni, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 18, 8409–8438, https://doi.org/10.5194/acp-18-8409-2018, https://doi.org/10.5194/acp-18-8409-2018, 2018
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We analyse simulations from the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion by anthropogenic chlorine and bromine. The simulations from 20 models project that global column ozone will return to 1980 values in 2047 (uncertainty range 2042–2052). Return dates in other regions vary depending on factors related to climate change and importance of chlorine and bromine. Column ozone in the tropics may continue to decline.
Sourish Basu, David F. Baker, Frédéric Chevallier, Prabir K. Patra, Junjie Liu, and John B. Miller
Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, https://doi.org/10.5194/acp-18-7189-2018, 2018
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CO2 measurements from the global surface network and CO2 estimates from satellites such as the Orbiting Carbon Observatory 2 (OCO-2) are currently used to quantify the surface sources and sinks of CO2, using what we know about atmospheric transport of gases. In this work, we quantify the uncertainties in those surface source/sink estimates that stem from errors in our atmospheric transport models, using an observing system simulation experiment (OSSE).
Yilong Wang, Grégoire Broquet, Philippe Ciais, Frédéric Chevallier, Felix Vogel, Lin Wu, Yi Yin, Rong Wang, and Shu Tao
Atmos. Chem. Phys., 18, 4229–4250, https://doi.org/10.5194/acp-18-4229-2018, https://doi.org/10.5194/acp-18-4229-2018, 2018
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This paper assesses the potential of atmospheric 14CO2 observations and a global inversion system to solve for fossil fuel CO2 (FFCO2) emissions in Europe. The estimate of monthly emission budgets is largely improved in high emitting regions. The results are sensitive to the observation network and the prior uncertainty. Using a high-resolution transport model and a systematic evaluation of the uncertainty in current emission inventories should improve the potential to retrieve FFCO2 emissions.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
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The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Irène Xueref-Remy, Elsa Dieudonné, Cyrille Vuillemin, Morgan Lopez, Christine Lac, Martina Schmidt, Marc Delmotte, Frédéric Chevallier, François Ravetta, Olivier Perrussel, Philippe Ciais, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, T. Gerard Spain, and Christophe Ampe
Atmos. Chem. Phys., 18, 3335–3362, https://doi.org/10.5194/acp-18-3335-2018, https://doi.org/10.5194/acp-18-3335-2018, 2018
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Urbanized and industrialized areas are the largest source of fossil CO2. This work analyses the atmospheric CO2 variability observed from the first in situ network deployed in the Paris megacity area. Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO2 records.
Grégoire Broquet, François-Marie Bréon, Emmanuel Renault, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Frédéric Chevallier, Lin Wu, and Philippe Ciais
Atmos. Meas. Tech., 11, 681–708, https://doi.org/10.5194/amt-11-681-2018, https://doi.org/10.5194/amt-11-681-2018, 2018
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This study assesses the potential of space-borne imagery of CO2 atmospheric concentrations for monitoring the emissions from the Paris area. Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO2 emissions for urban areas with CO2 observations from satellites, and calls for more technological innovations in the remote sensing of CO2 and in the models that exploit it.
Andreas Engel, Harald Bönisch, Jennifer Ostermöller, Martyn P. Chipperfield, Sandip Dhomse, and Patrick Jöckel
Atmos. Chem. Phys., 18, 601–619, https://doi.org/10.5194/acp-18-601-2018, https://doi.org/10.5194/acp-18-601-2018, 2018
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We present a new method to derive equivalent effective stratospheric chlorine (EESC), which is based on an improved formulation of the propagation of trends of species with chemical loss from the troposphere to the stratosphere. EESC calculated with the new method shows much better agreement with model-derived ESC. Based on this new formulation, we expect the halogen impact on midlatitude stratospheric ozone to return to 1980 values about 10 years later, then using the current formulation.
Daniel R. Moon, Giorgio S. Taverna, Clara Anduix-Canto, Trevor Ingham, Martyn P. Chipperfield, Paul W. Seakins, Maria-Teresa Baeza-Romero, and Dwayne E. Heard
Atmos. Chem. Phys., 18, 327–338, https://doi.org/10.5194/acp-18-327-2018, https://doi.org/10.5194/acp-18-327-2018, 2018
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One geoengineering mitigation strategy for global temperature rises is to inject particles into the stratosphere to scatter solar radiation back to space. However, the injection of such particles must not perturb ozone. We measured the rate of uptake of HO2 radicals, an important stratospheric intermediate, onto TiO2 particles. Using the atmospheric model TOMCAT, we showed that surface reactions between HO2 and TiO2 would have a negligible effect on stratospheric concentrations of HO2 and ozone.
Demerval S. Moreira, Karla M. Longo, Saulo R. Freitas, Marcia A. Yamasoe, Lina M. Mercado, Nilton E. Rosário, Emauel Gloor, Rosane S. M. Viana, John B. Miller, Luciana V. Gatti, Kenia T. Wiedemann, Lucas K. G. Domingues, and Caio C. S. Correia
Atmos. Chem. Phys., 17, 14785–14810, https://doi.org/10.5194/acp-17-14785-2017, https://doi.org/10.5194/acp-17-14785-2017, 2017
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Fire in the Amazon forest produces a large amount of smoke that is released into the atmosphere and covers a large portion of South America for about 3 months each year. The smoke affects the energy and CO2 budgets. Using a numerical atmospheric model, we demonstrated that the smoke changes the forest from a source to a sink of CO2 to the atmosphere. The smoke ultimately acts to at least partially compensate for the forest carbon lost due to fire emissions.
Chao Yue, Philippe Ciais, Ana Bastos, Frederic Chevallier, Yi Yin, Christian Rödenbeck, and Taejin Park
Atmos. Chem. Phys., 17, 13903–13919, https://doi.org/10.5194/acp-17-13903-2017, https://doi.org/10.5194/acp-17-13903-2017, 2017
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The year 2015 appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since 2000 according to satellite observation, but the atmospheric CO2 growth rate is also the highest since 1959. We found that this is due to a only moderate land carbon sink, because high growing-season sink in northern lands has been partly offset by autumn and winter release and the late-year El Niño has led to an abrupt transition to land source in the tropics.
Sarah A. Monks, Stephen R. Arnold, Michael J. Hollaway, Richard J. Pope, Chris Wilson, Wuhu Feng, Kathryn M. Emmerson, Brian J. Kerridge, Barry L. Latter, Georgina M. Miles, Richard Siddans, and Martyn P. Chipperfield
Geosci. Model Dev., 10, 3025–3057, https://doi.org/10.5194/gmd-10-3025-2017, https://doi.org/10.5194/gmd-10-3025-2017, 2017
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The TOMCAT chemical transport model has been updated with the chemical degradation of ethene, propene, toluene, butane and monoterpenes. The tropospheric chemical mechanism is documented and the model is evaluated against surface, balloon, aircraft and satellite data. The model is generally able to capture the main spatial and seasonal features of carbon monoxide, ozone, volatile organic compounds and reactive nitrogen. However,
some model biases are found that require further investigation.
Anna M. Michalak, Nina A. Randazzo, and Frédéric Chevallier
Atmos. Chem. Phys., 17, 7405–7421, https://doi.org/10.5194/acp-17-7405-2017, https://doi.org/10.5194/acp-17-7405-2017, 2017
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The use of inverse modeling for quantifying emissions of greenhouse gases is increasing. Estimates are very difficult to evaluate objectively, however, due to limited atmospheric observations and the lack of direct emissions measurements at compatible scales. Diagnostic tools have been proposed to partially circumvent these limitations. This paper presents the first systematic review of the scope and applicability of these tools for atmospheric inversions of long-lived greenhouse gases.
Jerónimo Escribano, Olivier Boucher, Frédéric Chevallier, and Nicolás Huneeus
Atmos. Chem. Phys., 17, 7111–7126, https://doi.org/10.5194/acp-17-7111-2017, https://doi.org/10.5194/acp-17-7111-2017, 2017
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Top-down estimates of mineral dust flux usually rely on a single observational dataset whose observational errors propagate onto the emission estimates. Aerosol optical depth from five satellites are assimilated one by one into a source inversion system over northern Africa. We find a relatively large dispersion in flux estimates among the five experiments, which can likely be attributed to differences in the assimilated observational datasets and their associated error statistics.
Wenshou Tian, Yuanpu Li, Fei Xie, Jiankai Zhang, Martyn P. Chipperfield, Wuhu Feng, Yongyun Hu, Sen Zhao, Xin Zhou, Yun Yang, and Xuan Ma
Atmos. Chem. Phys., 17, 6705–6722, https://doi.org/10.5194/acp-17-6705-2017, https://doi.org/10.5194/acp-17-6705-2017, 2017
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Although the principal mechanisms responsible for the formation of the Antarctic ozone hole are well understood, the factors or processes that generate interannual variations in ozone levels in the southern high-latitude stratosphere remain under debate. This study finds that the SST variations across the East Asian marginal seas (5° S–35° N, 100–140° E) could modulate the southern high-latitude stratospheric ozone interannual changes.
Shreeya Verma, Julia Marshall, Mark Parrington, Anna Agustí-Panareda, Sebastien Massart, Martyn P. Chipperfield, Christopher Wilson, and Christoph Gerbig
Atmos. Chem. Phys., 17, 6663–6678, https://doi.org/10.5194/acp-17-6663-2017, https://doi.org/10.5194/acp-17-6663-2017, 2017
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Aircraft profiles are a useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, these are available only up to about 9–13 km altitude and therefore need to be extended synthetically into the stratosphere using other sources. In this study, we analyse three different data sources that are available for extension of CH4 profiles by comparing the error introduced by each into the total column and provide recommendations regarding the best approach.
Liang Feng, Paul I. Palmer, Hartmut Bösch, Robert J. Parker, Alex J. Webb, Caio S. C. Correia, Nicholas M. Deutscher, Lucas G. Domingues, Dietrich G. Feist, Luciana V. Gatti, Emanuel Gloor, Frank Hase, Rigel Kivi, Yi Liu, John B. Miller, Isamu Morino, Ralf Sussmann, Kimberly Strong, Osamu Uchino, Jing Wang, and Andreas Zahn
Atmos. Chem. Phys., 17, 4781–4797, https://doi.org/10.5194/acp-17-4781-2017, https://doi.org/10.5194/acp-17-4781-2017, 2017
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We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4:XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. Our results show that assimilation of GOSAT data significantly reduced the posterior uncertainty and changed the a priori spatial distribution of CH4 emissions.
Yi Yin, Frederic Chevallier, Philippe Ciais, Gregoire Broquet, Anne Cozic, Sophie Szopa, and Yilong Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-166, https://doi.org/10.5194/acp-2017-166, 2017
Revised manuscript not accepted
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CO inverse modelling studies have so far reported significant discrepancies between model concentrations optimised with the Measurement of Pollution in the Troposphere (MOPITT) satellite retrievals and surface in-situ measurements. Here, we assess how well a global CTM fits a large variety of independent CO observations before and after assimilating MOPITTv6 retrievals to optimise CO sources/sink and discuss potential sources of errors and their implications for global CO modelling studies.
Jochen Stutz, Bodo Werner, Max Spolaor, Lisa Scalone, James Festa, Catalina Tsai, Ross Cheung, Santo F. Colosimo, Ugo Tricoli, Rasmus Raecke, Ryan Hossaini, Martyn P. Chipperfield, Wuhu Feng, Ru-Shan Gao, Eric J. Hintsa, James W. Elkins, Fred L. Moore, Bruce Daube, Jasna Pittman, Steven Wofsy, and Klaus Pfeilsticker
Atmos. Meas. Tech., 10, 1017–1042, https://doi.org/10.5194/amt-10-1017-2017, https://doi.org/10.5194/amt-10-1017-2017, 2017
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A new limb-scanning Differential Optical Absorption Spectroscopy (DOAS) instrument was developed for NASA’s Global Hawk unmanned aerial system during the Airborne Tropical TRopopause EXperiment to study trace gases in the tropical tropopause layer. A new technique that uses in situ and DOAS O3 observations together with radiative transfer calculations allows the retrieval of mixing ratios from the slant column densities of BrO and NO2 at high accuracies of 0.5 ppt and 15 ppt, respectively.
Olaf Morgenstern, Michaela I. Hegglin, Eugene Rozanov, Fiona M. O'Connor, N. Luke Abraham, Hideharu Akiyoshi, Alexander T. Archibald, Slimane Bekki, Neal Butchart, Martyn P. Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando R. Garcia, Steven C. Hardiman, Larry W. Horowitz, Patrick Jöckel, Beatrice Josse, Douglas Kinnison, Meiyun Lin, Eva Mancini, Michael E. Manyin, Marion Marchand, Virginie Marécal, Martine Michou, Luke D. Oman, Giovanni Pitari, David A. Plummer, Laura E. Revell, David Saint-Martin, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Geosci. Model Dev., 10, 639–671, https://doi.org/10.5194/gmd-10-639-2017, https://doi.org/10.5194/gmd-10-639-2017, 2017
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We present a review of the make-up of 20 models participating in the Chemistry–Climate Model Initiative (CCMI). In comparison to earlier such activities, most of these models comprise a whole-atmosphere chemistry, and several of them include an interactive ocean module. This makes them suitable for studying the interactions of tropospheric air quality, stratospheric ozone, and climate. The paper lays the foundation for other studies using the CCMI simulations for scientific analysis.
Bodo Werner, Jochen Stutz, Max Spolaor, Lisa Scalone, Rasmus Raecke, James Festa, Santo Fedele Colosimo, Ross Cheung, Catalina Tsai, Ryan Hossaini, Martyn P. Chipperfield, Giorgio S. Taverna, Wuhu Feng, James W. Elkins, David W. Fahey, Ru-Shan Gao, Erik J. Hintsa, Troy D. Thornberry, Free Lee Moore, Maria A. Navarro, Elliot Atlas, Bruce C. Daube, Jasna Pittman, Steve Wofsy, and Klaus Pfeilsticker
Atmos. Chem. Phys., 17, 1161–1186, https://doi.org/10.5194/acp-17-1161-2017, https://doi.org/10.5194/acp-17-1161-2017, 2017
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The paper reports on inorganic and organic bromine measured in the tropical tropopause layer (TTL) over the eastern Pacific in early 2013. Bryinorg is found to increase from a mean of 2.63 ± 1.04 ppt for θ in the range of 350–360 K to 5.11 ± 1.57 ppt for θ=390 ± 400 K, whereas in the subtropical lower stratosphere, it reaches 7.66 ± 2.95 ppt for θ in the range of 390–400 K. Within the TTL, total bromine is found to range from 20.3 ppt to 22.3 ppt.
Tamás Kovács, Wuhu Feng, Anna Totterdill, John M. C. Plane, Sandip Dhomse, Juan Carlos Gómez-Martín, Gabriele P. Stiller, Florian J. Haenel, Christopher Smith, Piers M. Forster, Rolando R. García, Daniel R. Marsh, and Martyn P. Chipperfield
Atmos. Chem. Phys., 17, 883–898, https://doi.org/10.5194/acp-17-883-2017, https://doi.org/10.5194/acp-17-883-2017, 2017
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Sulfur hexafluoride (SF6) is a very potent greenhouse gas, which is present in the atmosphere only through its industrial use, for example as an electrical insulator. To estimate accurately the impact of SF6 emissions on climate we need to know how long it persists in the atmosphere before being removed. Previous estimates of the SF6 lifetime indicate a large degree of uncertainty. Here we use a detailed atmospheric model to calculate a current best estimate of the SF6 lifetime.
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
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The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Lamia Ammoura, Irène Xueref-Remy, Felix Vogel, Valérie Gros, Alexia Baudic, Bernard Bonsang, Marc Delmotte, Yao Té, and Frédéric Chevallier
Atmos. Chem. Phys., 16, 15653–15664, https://doi.org/10.5194/acp-16-15653-2016, https://doi.org/10.5194/acp-16-15653-2016, 2016
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We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed. We apply it to estimate monthly ratios between CO2, CO and some VOCs from atmospheric measurement datasets acquired in the centre of Paris between 2010 and 2014. We find that this approach is little sensitive to the regional background level definition. With this new method, we may reveal spatial and seasonal variability in the ratios in Paris.
Martyn P. Chipperfield, Qing Liang, Matthew Rigby, Ryan Hossaini, Stephen A. Montzka, Sandip Dhomse, Wuhu Feng, Ronald G. Prinn, Ray F. Weiss, Christina M. Harth, Peter K. Salameh, Jens Mühle, Simon O'Doherty, Dickon Young, Peter G. Simmonds, Paul B. Krummel, Paul J. Fraser, L. Paul Steele, James D. Happell, Robert C. Rhew, James Butler, Shari A. Yvon-Lewis, Bradley Hall, David Nance, Fred Moore, Ben R. Miller, James W. Elkins, Jeremy J. Harrison, Chris D. Boone, Elliot L. Atlas, and Emmanuel Mahieu
Atmos. Chem. Phys., 16, 15741–15754, https://doi.org/10.5194/acp-16-15741-2016, https://doi.org/10.5194/acp-16-15741-2016, 2016
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Carbon tetrachloride (CCl4) is a compound which, when released into the atmosphere, can cause depletion of the stratospheric ozone layer. Its emissions are controlled under the Montreal Protocol, and its atmospheric abundance is slowly decreasing. However, this decrease is not as fast as expected based on estimates of its emissions and its atmospheric lifetime. We have used an atmospheric model to look at the uncertainties in the CCl4 lifetime and to examine the impact on its atmospheric decay.
Johannes Staufer, Grégoire Broquet, François-Marie Bréon, Vincent Puygrenier, Frédéric Chevallier, Irène Xueref-Rémy, Elsa Dieudonné, Morgan Lopez, Martina Schmidt, Michel Ramonet, Olivier Perrussel, Christine Lac, Lin Wu, and Philippe Ciais
Atmos. Chem. Phys., 16, 14703–14726, https://doi.org/10.5194/acp-16-14703-2016, https://doi.org/10.5194/acp-16-14703-2016, 2016
Bradley O. Christoffersen, Manuel Gloor, Sophie Fauset, Nikolaos M. Fyllas, David R. Galbraith, Timothy R. Baker, Bart Kruijt, Lucy Rowland, Rosie A. Fisher, Oliver J. Binks, Sanna Sevanto, Chonggang Xu, Steven Jansen, Brendan Choat, Maurizio Mencuccini, Nate G. McDowell, and Patrick Meir
Geosci. Model Dev., 9, 4227–4255, https://doi.org/10.5194/gmd-9-4227-2016, https://doi.org/10.5194/gmd-9-4227-2016, 2016
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We developed a plant hydraulics model for tropical forests based on established plant physiological theory, and parameterized it by conducting a pantropical hydraulic trait survey. We show that a substantial amount of trait diversity can be represented in the model by a reduced set of trait dimensions. The fully parameterized model is able capture tree-level variation in water status and improves simulations of total ecosystem transpiration, showing how to incorporate hydraulic traits in models.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Richard J. Pope, Nigel A. D. Richards, Martyn P. Chipperfield, David P. Moore, Sarah A. Monks, Stephen R. Arnold, Norbert Glatthor, Michael Kiefer, Tom J. Breider, Jeremy J. Harrison, John J. Remedios, Carsten Warneke, James M. Roberts, Glenn S. Diskin, Lewis G. Huey, Armin Wisthaler, Eric C. Apel, Peter F. Bernath, and Wuhu Feng
Atmos. Chem. Phys., 16, 13541–13559, https://doi.org/10.5194/acp-16-13541-2016, https://doi.org/10.5194/acp-16-13541-2016, 2016
Natasha MacBean, Philippe Peylin, Frédéric Chevallier, Marko Scholze, and Gregor Schürmann
Geosci. Model Dev., 9, 3569–3588, https://doi.org/10.5194/gmd-9-3569-2016, https://doi.org/10.5194/gmd-9-3569-2016, 2016
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Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model. Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context. This paper demonstrates and discusses the issues involved using toy models and examples from existing literature.
Philippe Peylin, Cédric Bacour, Natasha MacBean, Sébastien Leonard, Peter Rayner, Sylvain Kuppel, Ernest Koffi, Abdou Kane, Fabienne Maignan, Frédéric Chevallier, Philippe Ciais, and Pascal Prunet
Geosci. Model Dev., 9, 3321–3346, https://doi.org/10.5194/gmd-9-3321-2016, https://doi.org/10.5194/gmd-9-3321-2016, 2016
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The study describes a carbon cycle data assimilation system that uses satellite observations of vegetation activity, net ecosystem exchange of carbon and water at many sites and atmospheric CO2 concentrations, in order to optimize the parameters of the ORCHIDEE land surface model. The optimized model is able to fit all three data streams leading to a land carbon uptake similar to independent estimates, which opens new perspectives for better prediction of the land carbon balance.
Anna Totterdill, Tamás Kovács, Wuhu Feng, Sandip Dhomse, Christopher J. Smith, Juan Carlos Gómez-Martín, Martyn P. Chipperfield, Piers M. Forster, and John M. C. Plane
Atmos. Chem. Phys., 16, 11451–11463, https://doi.org/10.5194/acp-16-11451-2016, https://doi.org/10.5194/acp-16-11451-2016, 2016
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In this study we have experimentally determined the infrared absorption cross sections of NF3 and CFC-115, calculated the radiative forcing and efficiency using two radiative transfer models and identified the effect of clouds and stratospheric adjustment. We have also determined their atmospheric lifetimes using the Whole Atmosphere Community Climate Model.
Tamás Kovács, John M. C. Plane, Wuhu Feng, Tibor Nagy, Martyn P. Chipperfield, Pekka T. Verronen, Monika E. Andersson, David A. Newnham, Mark A. Clilverd, and Daniel R. Marsh
Geosci. Model Dev., 9, 3123–3136, https://doi.org/10.5194/gmd-9-3123-2016, https://doi.org/10.5194/gmd-9-3123-2016, 2016
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This study was completed on D-region atmospheric model development. The sophisticated 3-D Whole Atmosphere Community Climate Model (WACCM) and the 1-D Sodynkalä Ion and Neutral Chemistry Model (SIC) were combined in order to provide a detailed, accurate model (WACCM-SIC) that considers the processes taking place in solar proton events. The original SIC model was reduced by mechanism reduction, which provided an accurate sub-mechanism (rSIC, WACCM-rSIC) of the original model.
M. N. Deeter, S. Martínez-Alonso, L. V. Gatti, M. Gloor, J. B. Miller, L. G. Domingues, and C. S. C. Correia
Atmos. Meas. Tech., 9, 3999–4012, https://doi.org/10.5194/amt-9-3999-2016, https://doi.org/10.5194/amt-9-3999-2016, 2016
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Satellite methods allow biomass burning emissions to be accurately quantified with high spatial and temporal resolution. With that ultimate goal, we analyze satellite retrievals of carbon monoxide from the MOPITT instrument over the Amazon Basin. Validation results for four Amazonian sites indicate a significant negative bias in retrieved lower-tropospheric CO concentrations. The interannual variability of biomass burning emissions from 2000 to 2015 is also studied using the MOPITT record.
Jeremy J. Harrison, Martyn P. Chipperfield, Christopher D. Boone, Sandip S. Dhomse, Peter F. Bernath, Lucien Froidevaux, John Anderson, and James Russell III
Atmos. Chem. Phys., 16, 10501–10519, https://doi.org/10.5194/acp-16-10501-2016, https://doi.org/10.5194/acp-16-10501-2016, 2016
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HF, the dominant stratospheric fluorine reservoir, results from the atmospheric degradation of anthropogenic species such as CFCs, HCFCs, and HFCs. All are strong greenhouse gases, and CFCs and HCFCs deplete stratospheric ozone.
We report the comparison of HF global distributions and trends measured by the ACE-FTS and HALOE satellite instruments with the output of SLIMCAT, a chemical transport model. The global HF trends reveal a slowing down in the rate of increase of HF since the 1990s.
Anna Agustí-Panareda, Sébastien Massart, Frédéric Chevallier, Gianpaolo Balsamo, Souhail Boussetta, Emanuel Dutra, and Anton Beljaars
Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016, https://doi.org/10.5194/acp-16-10399-2016, 2016
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This paper presents a method to adjust the sinks and sources of CO2 associated with land ecosystems within a global atmospheric CO2 forecasting system in order to reduce the errors in the forecast. This is done by combining information on (1) retrospective fluxes estimated by a global flux inversion system, (2) land-use information, and (3) simulated fluxes from the model. Because the method is simple and flexible, it can easily run in real time as part of a forecasting system.
R. Hossaini, P. K. Patra, A. A. Leeson, G. Krysztofiak, N. L. Abraham, S. J. Andrews, A. T. Archibald, J. Aschmann, E. L. Atlas, D. A. Belikov, H. Bönisch, L. J. Carpenter, S. Dhomse, M. Dorf, A. Engel, W. Feng, S. Fuhlbrügge, P. T. Griffiths, N. R. P. Harris, R. Hommel, T. Keber, K. Krüger, S. T. Lennartz, S. Maksyutov, H. Mantle, G. P. Mills, B. Miller, S. A. Montzka, F. Moore, M. A. Navarro, D. E. Oram, K. Pfeilsticker, J. A. Pyle, B. Quack, A. D. Robinson, E. Saikawa, A. Saiz-Lopez, S. Sala, B.-M. Sinnhuber, S. Taguchi, S. Tegtmeier, R. T. Lidster, C. Wilson, and F. Ziska
Atmos. Chem. Phys., 16, 9163–9187, https://doi.org/10.5194/acp-16-9163-2016, https://doi.org/10.5194/acp-16-9163-2016, 2016
Cindy Cressot, Isabelle Pison, Peter J. Rayner, Philippe Bousquet, Audrey Fortems-Cheiney, and Frédéric Chevallier
Atmos. Chem. Phys., 16, 9089–9108, https://doi.org/10.5194/acp-16-9089-2016, https://doi.org/10.5194/acp-16-9089-2016, 2016
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Several hypothesis have been made to attribute current trends in atmospheric methane to particular regions. In this context, this work aims at evaluating how well anomalies in methane emissions can be detected at the regional scale with currently available observing systems: two space-borne instruments and a surface network. Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment.
Peter Rayner, Anna M. Michalak, and Frédéric Chevallier
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-148, https://doi.org/10.5194/gmd-2016-148, 2016
Revised manuscript not accepted
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Numerical models are among our most important tools for understanding and prediction. Models include quantities or equations that we cannot verify directly. We learn about these unknowns by comparing model output with observations and using some algorithm to improve the inputs. We show here that the many methods for doing this are special cases of underlying statistics. This provides a unified way of comparing and contrasting such methods.
Joe McNorton, Martyn P. Chipperfield, Manuel Gloor, Chris Wilson, Wuhu Feng, Garry D. Hayman, Matt Rigby, Paul B. Krummel, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, Ed Dlugokencky, and Steve A. Montzka
Atmos. Chem. Phys., 16, 7943–7956, https://doi.org/10.5194/acp-16-7943-2016, https://doi.org/10.5194/acp-16-7943-2016, 2016
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Methane (CH4) is an important greenhouse gas. The growth of atmospheric CH4 stalled from 1999 to 2006, with current explanations focussed mainly on changing surface fluxes. We combine models with observations and meteorological data to assess the atmospheric contribution to CH4 changes. We find that variations in mean atmospheric hydroxyl concentration can explain part of the stall in growth. Our study highlights the role of multi-annual variability in atmospheric chemistry in global CH4 trends.
Christian Frankenberg, Susan S. Kulawik, Steven C. Wofsy, Frédéric Chevallier, Bruce Daube, Eric A. Kort, Christopher O'Dell, Edward T. Olsen, and Gregory Osterman
Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, https://doi.org/10.5194/acp-16-7867-2016, 2016
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We use observations from the HIAPER Pole-to-Pole Observations (HIPPO) flights from January 2009 through September 2011 to validate CO2 measurements from satellites (GOSAT, TES, AIRS) and atmospheric inversion models (CarbonTracker CT2013B, MACC v13r1).
Lin Wu, Grégoire Broquet, Philippe Ciais, Valentin Bellassen, Felix Vogel, Frédéric Chevallier, Irène Xueref-Remy, and Yilong Wang
Atmos. Chem. Phys., 16, 7743–7771, https://doi.org/10.5194/acp-16-7743-2016, https://doi.org/10.5194/acp-16-7743-2016, 2016
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This paper advances atmospheric inversion of city CO2 emissions as follows: (1) illustrate how inversion methodology can be tailored to deal with very large urban networks of sensors measuring CO2 concentrations; (2) demonstrate that atmospheric inversion could be a relevant tool of Monitoring, Reporting and Verification (MRV) of city CO2 emissions; (3) clarify the theoretical potential of inversion for reducing uncertainties in the estimates of citywide total and sectoral CO2 emissions.
Alex Boon, Grégoire Broquet, Deborah J. Clifford, Frédéric Chevallier, David M. Butterfield, Isabelle Pison, Michel Ramonet, Jean-Daniel Paris, and Philippe Ciais
Atmos. Chem. Phys., 16, 6735–6756, https://doi.org/10.5194/acp-16-6735-2016, https://doi.org/10.5194/acp-16-6735-2016, 2016
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We measured carbon dioxide and methane concentrations at four near-ground sites located in London, 2012. We investigated the potential for using these measurements, alongside numerical modelling, to help us to understand urban greenhouse gas emissions. Low-level sites were highly sensitive to local emissions, which questions our ability to use measurements from near-ground sites in cities in some modelling applications. A gradient approach was found to be beneficial to reduce model–data errors.
Sudhanshu Pandey, Sander Houweling, Maarten Krol, Ilse Aben, Frédéric Chevallier, Edward J. Dlugokencky, Luciana V. Gatti, Emanuel Gloor, John B. Miller, Rob Detmers, Toshinobu Machida, and Thomas Röckmann
Atmos. Chem. Phys., 16, 5043–5062, https://doi.org/10.5194/acp-16-5043-2016, https://doi.org/10.5194/acp-16-5043-2016, 2016
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This study investigates the constraint provided by measurements of Xratio (XCH4/XCO2) from space on surface fluxes of CH4 and CO2. We apply the ratio inversion method described in Pandey et al. (2015) to Xratio retrievals from the GOSAT with the TM5-4DVAR inverse modeling system, to constrain the surface fluxes of CH4 and CO2 for 2009 and 2010. The results are compared to proxy CH4 inversions using model-derived-XCO2 mixing ratios from CarbonTracker and MACC.
Antoine Berchet, Philippe Bousquet, Isabelle Pison, Robin Locatelli, Frédéric Chevallier, Jean-Daniel Paris, Ed J. Dlugokencky, Tuomas Laurila, Juha Hatakka, Yrjo Viisanen, Doug E. J. Worthy, Euan Nisbet, Rebecca Fisher, James France, David Lowry, Viktor Ivakhov, and Ove Hermansen
Atmos. Chem. Phys., 16, 4147–4157, https://doi.org/10.5194/acp-16-4147-2016, https://doi.org/10.5194/acp-16-4147-2016, 2016
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We propose insights based on atmospheric observations around the Arctic circle to evaluate estimates of methane emissions to the atmosphere from the East Siberian Arctic Shelf. Based on a comprehensive statistical analysis of the observations and of high-resolution transport simulations, annual methane emissions from ESAS are estimated to range from 0.0 to 4.5 TgCH4 yr−1, with a maximum in summer and very low emissions in winter.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
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To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
Sébastien Massart, Anna Agustí-Panareda, Jens Heymann, Michael Buchwitz, Frédéric Chevallier, Maximilian Reuter, Michael Hilker, John P. Burrows, Nicholas M. Deutscher, Dietrich G. Feist, Frank Hase, Ralf Sussmann, Filip Desmet, Manvendra K. Dubey, David W. T. Griffith, Rigel Kivi, Christof Petri, Matthias Schneider, and Voltaire A. Velazco
Atmos. Chem. Phys., 16, 1653–1671, https://doi.org/10.5194/acp-16-1653-2016, https://doi.org/10.5194/acp-16-1653-2016, 2016
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This study presents the European Centre for Medium-Range Weather Forecasts (ECMWF) monitoring of atmospheric CO2 using measurements from the Greenhouse gases Observing Satellite (GOSAT). We show that the modelled CO2 has a better precision than standard CO2 satellite products compared to ground-based measurements. We also present the CO2 forecast based on our best knowledge of the atmospheric CO2 distribution. We show that it has skill to forecast the largest scale CO2 patterns up to day 5.
Y. Yin, F. Chevallier, P. Ciais, G. Broquet, A. Fortems-Cheiney, I. Pison, and M. Saunois
Atmos. Chem. Phys., 15, 13433–13451, https://doi.org/10.5194/acp-15-13433-2015, https://doi.org/10.5194/acp-15-13433-2015, 2015
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We studied the global CO concentration decline over the recent decade with a sophisticated atmospheric inversion system assimilating MOPITT CO retrievals, surface methane and surface methyl chloroform in situ measurements. The inversion interprets the CO concentration decline as a 23% decrease in the CO emissions from 2002 to 2011, twice the negative trend estimated by emission inventories. In contrast to bottom-up inventories, we find negative trends over China and South-east Asia.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
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Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
H. Lindqvist, C. W. O'Dell, S. Basu, H. Boesch, F. Chevallier, N. Deutscher, L. Feng, B. Fisher, F. Hase, M. Inoue, R. Kivi, I. Morino, P. I. Palmer, R. Parker, M. Schneider, R. Sussmann, and Y. Yoshida
Atmos. Chem. Phys., 15, 13023–13040, https://doi.org/10.5194/acp-15-13023-2015, https://doi.org/10.5194/acp-15-13023-2015, 2015
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Atmospheric carbon dioxide concentration varies seasonally mainly due to plant photosynthesis in the Northern Hemisphere. We found that the satellite GOSAT can capture this variability from space to within 1ppm. We also found that models can differ by more than 1ppm. This implies that the satellite measurements could be useful in evaluating models and their prior estimates of carbon dioxide sources and sinks.
N. Kadygrov, G. Broquet, F. Chevallier, L. Rivier, C. Gerbig, and P. Ciais
Atmos. Chem. Phys., 15, 12765–12787, https://doi.org/10.5194/acp-15-12765-2015, https://doi.org/10.5194/acp-15-12765-2015, 2015
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We study the potential of the European Integrated Carbon Observing System (ICOS) atmospheric network for estimating European CO2 ecosystem fluxes. Regional atmospheric inversions with synthetic data are used to derive it in terms of statistical uncertainty. This potential is high in western Europe and future extensions of the network will increase it in eastern Europe. Future improvements of the models underlying the inversion should also significantly decrease uncertainties at high resolution.
R. J. Parker, H. Boesch, K. Byckling, A. J. Webb, P. I. Palmer, L. Feng, P. Bergamaschi, F. Chevallier, J. Notholt, N. Deutscher, T. Warneke, F. Hase, R. Sussmann, S. Kawakami, R. Kivi, D. W. T. Griffith, and V. Velazco
Atmos. Meas. Tech., 8, 4785–4801, https://doi.org/10.5194/amt-8-4785-2015, https://doi.org/10.5194/amt-8-4785-2015, 2015
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Atmospheric CH4 is an important greenhouse gas. Long-term global observations are necessary to understand its behaviour, with satellite observations playing a key role. The "proxy" retrieval method is one of the most successful but relies on the contribution from atmospheric CO2 models. This work assesses the significance of the uncertainty from the model CO2 within the retrieval and determines that despite this uncertainty the data are still valuable for determining sources and sinks of CH4.
R. J. Pope, N. H. Savage, M. P. Chipperfield, C. Ordóñez, and L. S. Neal
Atmos. Chem. Phys., 15, 11201–11215, https://doi.org/10.5194/acp-15-11201-2015, https://doi.org/10.5194/acp-15-11201-2015, 2015
F. Chevallier
Atmos. Chem. Phys., 15, 11133–11145, https://doi.org/10.5194/acp-15-11133-2015, https://doi.org/10.5194/acp-15-11133-2015, 2015
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We demonstrate that the current two-step approach to infer the CO2 surface fluxes from satellite measured radiances, with CO2 retrievals as an intermediate product, is not optimal. This suboptimality corrupts the 4D information flow from the radiance measurements to the surface flux estimates. It is amplified by current retrieval strategies where prior errors are much larger than the performance of prior CO2 simulations used in atmospheric inversions.
A. Berchet, I. Pison, F. Chevallier, J.-D. Paris, P. Bousquet, J.-L. Bonne, M. Y. Arshinov, B. D. Belan, C. Cressot, D. K. Davydov, E. J. Dlugokencky, A. V. Fofonov, A. Galanin, J. Lavrič, T. Machida, R. Parker, M. Sasakawa, R. Spahni, B. D. Stocker, and J. Winderlich
Biogeosciences, 12, 5393–5414, https://doi.org/10.5194/bg-12-5393-2015, https://doi.org/10.5194/bg-12-5393-2015, 2015
R. Locatelli, P. Bousquet, M. Saunois, F. Chevallier, and C. Cressot
Atmos. Chem. Phys., 15, 9765–9780, https://doi.org/10.5194/acp-15-9765-2015, https://doi.org/10.5194/acp-15-9765-2015, 2015
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
R. J. Pope, M. P. Chipperfield, N. H. Savage, C. Ordóñez, L. S. Neal, L. A. Lee, S. S. Dhomse, N. A. D. Richards, and T. D. Keslake
Atmos. Chem. Phys., 15, 5611–5626, https://doi.org/10.5194/acp-15-5611-2015, https://doi.org/10.5194/acp-15-5611-2015, 2015
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
S. A. Monks, S. R. Arnold, L. K. Emmons, K. S. Law, S. Turquety, B. N. Duncan, J. Flemming, V. Huijnen, S. Tilmes, J. Langner, J. Mao, Y. Long, J. L. Thomas, S. D. Steenrod, J. C. Raut, C. Wilson, M. P. Chipperfield, G. S. Diskin, A. Weinheimer, H. Schlager, and G. Ancellet
Atmos. Chem. Phys., 15, 3575–3603, https://doi.org/10.5194/acp-15-3575-2015, https://doi.org/10.5194/acp-15-3575-2015, 2015
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Multi-model simulations of Arctic CO, O3 and OH are evaluated using observations. Models show highly variable concentrations but the relative importance of emission regions and types is robust across the models, demonstrating the importance of biomass burning as a source. Idealised tracer experiments suggest that some of the model spread is due to variations in simulated transport from Europe in winter and from Asia throughout the year.
F. M. Bréon, G. Broquet, V. Puygrenier, F. Chevallier, I. Xueref-Remy, M. Ramonet, E. Dieudonné, M. Lopez, M. Schmidt, O. Perrussel, and P. Ciais
Atmos. Chem. Phys., 15, 1707–1724, https://doi.org/10.5194/acp-15-1707-2015, https://doi.org/10.5194/acp-15-1707-2015, 2015
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
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Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
M. O. Johnson, M. Gloor, M. J. Kirkby, and J. Lloyd
Biogeosciences, 11, 6873–6894, https://doi.org/10.5194/bg-11-6873-2014, https://doi.org/10.5194/bg-11-6873-2014, 2014
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We present a soil evolution model which incorporates the major processes of pedogenesis: mineral weathering, leaching, erosion, bioturbation, nutrient cycling and organic carbon inputs. We compare the modelled soil properties with soil chronosequences from Hawaii and demonstrate that the model captures well the key components of soil development. The model also highlights the important role that vegetation plays in accelerating the weathering and the release of globally important nutrients.
L. Ammoura, I. Xueref-Remy, V. Gros, A. Baudic, B. Bonsang, J.-E. Petit, O. Perrussel, N. Bonnaire, J. Sciare, and F. Chevallier
Atmos. Chem. Phys., 14, 12871–12882, https://doi.org/10.5194/acp-14-12871-2014, https://doi.org/10.5194/acp-14-12871-2014, 2014
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We present the first study of CO2, VOCs and NOx measured all together in a road tunnel around the Paris megacity with the aim to quantify the ratios of these species co-emitted within traffic emissions. It allows us to independently assess some of the ratios provided in the latest Paris emission inventory. It also reveals a large variability of the ratios to CO2, implying that traffic does not have a unique imprint in the urban plume, but rather leaves various signatures.
A. Agustí-Panareda, S. Massart, F. Chevallier, S. Boussetta, G. Balsamo, A. Beljaars, P. Ciais, N. M. Deutscher, R. Engelen, L. Jones, R. Kivi, J.-D. Paris, V.-H. Peuch, V. Sherlock, A. T. Vermeulen, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, https://doi.org/10.5194/acp-14-11959-2014, 2014
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This paper presents a new operational CO2 forecast product as part of the Copernicus Atmospheric Services suite of atmospheric composition products, using the state-of-the-art numerical weather prediction model from the European Centre of Medium-Range Weather Forecasts.
The evaluation with independent observations shows that the forecast has skill in predicting the synoptic variability of CO2. The online simulation of CO2 fluxes from vegetation contributes to this skill.
J. J. Harrison, M. P. Chipperfield, A. Dudhia, S. Cai, S. Dhomse, C. D. Boone, and P. F. Bernath
Atmos. Chem. Phys., 14, 11915–11933, https://doi.org/10.5194/acp-14-11915-2014, https://doi.org/10.5194/acp-14-11915-2014, 2014
S. Kuppel, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti
Geosci. Model Dev., 7, 2581–2597, https://doi.org/10.5194/gmd-7-2581-2014, https://doi.org/10.5194/gmd-7-2581-2014, 2014
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A consistent calibration of an advanced land surface model was performed by grouping in situ information on land-atmosphere exchanges of carbon and water using broad ecosystem and climate classes. Signatures of improved carbon cycle simulations were found across spatial and temporal scales, along with insights into current model limitations. These results hold promising perspectives within the ongoing efforts towards building robust model-data fusion frameworks for earth system models.
S. S. Dhomse, K. M. Emmerson, G. W. Mann, N. Bellouin, K. S. Carslaw, M. P. Chipperfield, R. Hommel, N. L. Abraham, P. Telford, P. Braesicke, M. Dalvi, C. E. Johnson, F. O'Connor, O. Morgenstern, J. A. Pyle, T. Deshler, J. M. Zawodny, and L. W. Thomason
Atmos. Chem. Phys., 14, 11221–11246, https://doi.org/10.5194/acp-14-11221-2014, https://doi.org/10.5194/acp-14-11221-2014, 2014
L. Kritten, A. Butz, M. P. Chipperfield, M. Dorf, S. Dhomse, R. Hossaini, H. Oelhaf, C. Prados-Roman, G. Wetzel, and K. Pfeilsticker
Atmos. Chem. Phys., 14, 9555–9566, https://doi.org/10.5194/acp-14-9555-2014, https://doi.org/10.5194/acp-14-9555-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
N. M. Fyllas, E. Gloor, L. M. Mercado, S. Sitch, C. A. Quesada, T. F. Domingues, D. R. Galbraith, A. Torre-Lezama, E. Vilanova, H. Ramírez-Angulo, N. Higuchi, D. A. Neill, M. Silveira, L. Ferreira, G. A. Aymard C., Y. Malhi, O. L. Phillips, and J. Lloyd
Geosci. Model Dev., 7, 1251–1269, https://doi.org/10.5194/gmd-7-1251-2014, https://doi.org/10.5194/gmd-7-1251-2014, 2014
M. R. Raupach, M. Gloor, J. L. Sarmiento, J. G. Canadell, T. L. Frölicher, T. Gasser, R. A. Houghton, C. Le Quéré, and C. M. Trudinger
Biogeosciences, 11, 3453–3475, https://doi.org/10.5194/bg-11-3453-2014, https://doi.org/10.5194/bg-11-3453-2014, 2014
R. L. Thompson, K. Ishijima, E. Saikawa, M. Corazza, U. Karstens, P. K. Patra, P. Bergamaschi, F. Chevallier, E. Dlugokencky, R. G. Prinn, R. F. Weiss, S. O'Doherty, P. J. Fraser, L. P. Steele, P. B. Krummel, A. Vermeulen, Y. Tohjima, A. Jordan, L. Haszpra, M. Steinbacher, S. Van der Laan, T. Aalto, F. Meinhardt, M. E. Popa, J. Moncrieff, and P. Bousquet
Atmos. Chem. Phys., 14, 6177–6194, https://doi.org/10.5194/acp-14-6177-2014, https://doi.org/10.5194/acp-14-6177-2014, 2014
S. Massart, A. Agusti-Panareda, I. Aben, A. Butz, F. Chevallier, C. Crevoisier, R. Engelen, C. Frankenberg, and O. Hasekamp
Atmos. Chem. Phys., 14, 6139–6158, https://doi.org/10.5194/acp-14-6139-2014, https://doi.org/10.5194/acp-14-6139-2014, 2014
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
R. L. Thompson, P. K. Patra, K. Ishijima, E. Saikawa, M. Corazza, U. Karstens, C. Wilson, P. Bergamaschi, E. Dlugokencky, C. Sweeney, R. G. Prinn, R. F. Weiss, S. O'Doherty, P. J. Fraser, L. P. Steele, P. B. Krummel, M. Saunois, M. Chipperfield, and P. Bousquet
Atmos. Chem. Phys., 14, 4349–4368, https://doi.org/10.5194/acp-14-4349-2014, https://doi.org/10.5194/acp-14-4349-2014, 2014
R. L. Thompson, F. Chevallier, A. M. Crotwell, G. Dutton, R. L. Langenfelds, R. G. Prinn, R. F. Weiss, Y. Tohjima, T. Nakazawa, P. B. Krummel, L. P. Steele, P. Fraser, S. O'Doherty, K. Ishijima, and S. Aoki
Atmos. Chem. Phys., 14, 1801–1817, https://doi.org/10.5194/acp-14-1801-2014, https://doi.org/10.5194/acp-14-1801-2014, 2014
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
C. Cressot, F. Chevallier, P. Bousquet, C. Crevoisier, E. J. Dlugokencky, A. Fortems-Cheiney, C. Frankenberg, R. Parker, I. Pison, R. A. Scheepmaker, S. A. Montzka, P. B. Krummel, L. P. Steele, and R. L. Langenfelds
Atmos. Chem. Phys., 14, 577–592, https://doi.org/10.5194/acp-14-577-2014, https://doi.org/10.5194/acp-14-577-2014, 2014
A. T. Brown, M. P. Chipperfield, N. A. D. Richards, C. Boone, and P. F. Bernath
Atmos. Chem. Phys., 14, 267–282, https://doi.org/10.5194/acp-14-267-2014, https://doi.org/10.5194/acp-14-267-2014, 2014
R. Hossaini, H. Mantle, M. P. Chipperfield, S. A. Montzka, P. Hamer, F. Ziska, B. Quack, K. Krüger, S. Tegtmeier, E. Atlas, S. Sala, A. Engel, H. Bönisch, T. Keber, D. Oram, G. Mills, C. Ordóñez, A. Saiz-Lopez, N. Warwick, Q. Liang, W. Feng, F. Moore, B. R. Miller, V. Marécal, N. A. D. Richards, M. Dorf, and K. Pfeilsticker
Atmos. Chem. Phys., 13, 11819–11838, https://doi.org/10.5194/acp-13-11819-2013, https://doi.org/10.5194/acp-13-11819-2013, 2013
P. Peylin, R. M. Law, K. R. Gurney, F. Chevallier, A. R. Jacobson, T. Maki, Y. Niwa, P. K. Patra, W. Peters, P. J. Rayner, C. Rödenbeck, I. T. van der Laan-Luijkx, and X. Zhang
Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, https://doi.org/10.5194/bg-10-6699-2013, 2013
S. S. Dhomse, M. P. Chipperfield, W. Feng, W. T. Ball, Y. C. Unruh, J. D. Haigh, N. A. Krivova, S. K. Solanki, and A. K. Smith
Atmos. Chem. Phys., 13, 10113–10123, https://doi.org/10.5194/acp-13-10113-2013, https://doi.org/10.5194/acp-13-10113-2013, 2013
R. Locatelli, P. Bousquet, F. Chevallier, A. Fortems-Cheney, S. Szopa, M. Saunois, A. Agusti-Panareda, D. Bergmann, H. Bian, P. Cameron-Smith, M. P. Chipperfield, E. Gloor, S. Houweling, S. R. Kawa, M. Krol, P. K. Patra, R. G. Prinn, M. Rigby, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 9917–9937, https://doi.org/10.5194/acp-13-9917-2013, https://doi.org/10.5194/acp-13-9917-2013, 2013
G. Broquet, F. Chevallier, F.-M. Bréon, N. Kadygrov, M. Alemanno, F. Apadula, S. Hammer, L. Haszpra, F. Meinhardt, J. A. Morguí, J. Necki, S. Piacentino, M. Ramonet, M. Schmidt, R. L. Thompson, A. T. Vermeulen, C. Yver, and P. Ciais
Atmos. Chem. Phys., 13, 9039–9056, https://doi.org/10.5194/acp-13-9039-2013, https://doi.org/10.5194/acp-13-9039-2013, 2013
A. T. Brown, M. P. Chipperfield, S. Dhomse, C. Boone, and P. F. Bernath
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-23491-2013, https://doi.org/10.5194/acpd-13-23491-2013, 2013
Revised manuscript has not been submitted
D. S. Moreira, S. R. Freitas, J. P. Bonatti, L. M. Mercado, N. M. É. Rosário, K. M. Longo, J. B. Miller, M. Gloor, and L. V. Gatti
Geosci. Model Dev., 6, 1243–1259, https://doi.org/10.5194/gmd-6-1243-2013, https://doi.org/10.5194/gmd-6-1243-2013, 2013
P. D. Hamer, V. Marécal, R. Hossaini, M. Pirre, N. Warwick, M. Chipperfield, A. A. Samah, N. Harris, A. Robinson, B. Quack, A. Engel, K. Krüger, E. Atlas, K. Subramaniam, D. Oram, Emma C. Leedham Elvidge, G. Mills, K. Pfeilsticker, S. Sala, T. Keber, H. Bönisch, L. K. Peng, M. S. M. Nadzir, P. T. Lim, A. Mujahid, A. Anton, H. Schlager, V. Catoire, G. Krysztofiak, S. Fühlbrügge, M. Dorf, and W. T. Sturges
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-20611-2013, https://doi.org/10.5194/acpd-13-20611-2013, 2013
Revised manuscript not accepted
A. Berchet, I. Pison, F. Chevallier, P. Bousquet, S. Conil, M. Geever, T. Laurila, J. Lavrič, M. Lopez, J. Moncrieff, J. Necki, M. Ramonet, M. Schmidt, M. Steinbacher, and J. Tarniewicz
Atmos. Chem. Phys., 13, 7115–7132, https://doi.org/10.5194/acp-13-7115-2013, https://doi.org/10.5194/acp-13-7115-2013, 2013
N. Huneeus, O. Boucher, and F. Chevallier
Atmos. Chem. Phys., 13, 6555–6573, https://doi.org/10.5194/acp-13-6555-2013, https://doi.org/10.5194/acp-13-6555-2013, 2013
S. Kreycy, C. Camy-Peyret, M. P. Chipperfield, M. Dorf, W. Feng, R. Hossaini, L. Kritten, B. Werner, and K. Pfeilsticker
Atmos. Chem. Phys., 13, 6263–6274, https://doi.org/10.5194/acp-13-6263-2013, https://doi.org/10.5194/acp-13-6263-2013, 2013
F. Chevallier
Geosci. Model Dev., 6, 783–790, https://doi.org/10.5194/gmd-6-783-2013, https://doi.org/10.5194/gmd-6-783-2013, 2013
N. A. D. Richards, S. R. Arnold, M. P. Chipperfield, G. Miles, A. Rap, R. Siddans, S. A. Monks, and M. J. Hollaway
Atmos. Chem. Phys., 13, 2331–2345, https://doi.org/10.5194/acp-13-2331-2013, https://doi.org/10.5194/acp-13-2331-2013, 2013
D. A. Belikov, S. Maksyutov, M. Krol, A. Fraser, M. Rigby, H. Bian, A. Agusti-Panareda, D. Bergmann, P. Bousquet, P. Cameron-Smith, M. P. Chipperfield, A. Fortems-Cheiney, E. Gloor, K. Haynes, P. Hess, S. Houweling, S. R. Kawa, R. M. Law, Z. Loh, L. Meng, P. I. Palmer, P. K. Patra, R. G. Prinn, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013, https://doi.org/10.5194/acp-13-1093-2013, 2013
U. Schuster, G. A. McKinley, N. Bates, F. Chevallier, S. C. Doney, A. R. Fay, M. González-Dávila, N. Gruber, S. Jones, J. Krijnen, P. Landschützer, N. Lefèvre, M. Manizza, J. Mathis, N. Metzl, A. Olsen, A. F. Rios, C. Rödenbeck, J. M. Santana-Casiano, T. Takahashi, R. Wanninkhof, and A. J. Watson
Biogeosciences, 10, 607–627, https://doi.org/10.5194/bg-10-607-2013, https://doi.org/10.5194/bg-10-607-2013, 2013
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Halogen chemistry in volcanic plumes: a 1D framework based on MOCAGE 1D (version R1.18.1) preparing 3D global chemistry modelling
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CLGAN: a generative adversarial network (GAN)-based video prediction model for precipitation nowcasting
Long-term evaluation of surface air pollution in CAMSRA and MERRA-2 global reanalyses over Europe (2003–2020)
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Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere–atmosphere fluxes relevant for ozone air quality
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Improving trajectory calculations by FLEXPART 10.4+ using single-image super-resolution
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James Weber, James A. King, Katerina Sindelarova, and Maria Val Martin
Geosci. Model Dev., 16, 3083–3101, https://doi.org/10.5194/gmd-16-3083-2023, https://doi.org/10.5194/gmd-16-3083-2023, 2023
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The emissions of volatile organic compounds from vegetation (BVOCs) influence atmospheric composition and contribute to certain gases and aerosols (tiny airborne particles) which play a role in climate change. BVOC emissions are likely to change in the future due to changes in climate and land use. Therefore, accurate simulation of BVOC emission is important, and this study describes an update to the simulation of BVOC emissions in the United Kingdom Earth System Model (UKESM).
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
Xiaohan Li, Yi Zhang, Xindong Peng, Baiquan Zhou, Jian Li, and Yiming Wang
Geosci. Model Dev., 16, 2975–2993, https://doi.org/10.5194/gmd-16-2975-2023, https://doi.org/10.5194/gmd-16-2975-2023, 2023
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The weather and climate physics suites used in GRIST-A22.7.28 are compared using single-column modeling. The source of their discrepancies in terms of modeling cloud and precipitation is explored. Convective parameterization is found to be a key factor responsible for the differences. The two suites also have intrinsic differences in the interaction between microphysics and other processes, resulting in different cloud features and time step sensitivities.
Virginie Marécal, Ronan Voisin-Plessis, Tjarda Jane Roberts, Alessandro Aiuppa, Herizo Narivelo, Paul David Hamer, Béatrice Josse, Jonathan Guth, Luke Surl, and Lisa Grellier
Geosci. Model Dev., 16, 2873–2898, https://doi.org/10.5194/gmd-16-2873-2023, https://doi.org/10.5194/gmd-16-2873-2023, 2023
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We implemented a halogen volcanic chemistry scheme in a one-dimensional modelling framework preparing for further use in a three-dimensional global chemistry-transport model. The results of the simulations for an eruption of Mt Etna in 2008, including various sensitivity tests, show a good consistency with previous modelling studies.
Zhe Feng, Joseph Hardin, Hannah C. Barnes, Jianfeng Li, L. Ruby Leung, Adam Varble, and Zhixiao Zhang
Geosci. Model Dev., 16, 2753–2776, https://doi.org/10.5194/gmd-16-2753-2023, https://doi.org/10.5194/gmd-16-2753-2023, 2023
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PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to track convective clouds from a variety of observations and model simulations. The package has a collection of multi-object identification algorithms and has been optimized for large datasets. This paper describes the algorithms and demonstrates applications for tracking deep convective cells and mesoscale convective systems from observations and model simulations at a wide range of scales.
Yan Ji, Bing Gong, Michael Langguth, Amirpasha Mozaffari, and Xiefei Zhi
Geosci. Model Dev., 16, 2737–2752, https://doi.org/10.5194/gmd-16-2737-2023, https://doi.org/10.5194/gmd-16-2737-2023, 2023
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Formulating short-term precipitation forecasting as a video prediction task, a novel deep learning architecture (convolutional long short-term memory generative adversarial network, CLGAN) is proposed. A benchmark dataset is built on minute-level precipitation measurements. Results show that with the GAN component the model generates predictions sharing statistical properties with observations, resulting in it outperforming the baseline in dichotomous and spatial scores for heavy precipitation.
Aleksander Lacima, Hervé Petetin, Albert Soret, Dene Bowdalo, Oriol Jorba, Zhaoyue Chen, Raúl F. Méndez Turrubiates, Hicham Achebak, Joan Ballester, and Carlos Pérez García-Pando
Geosci. Model Dev., 16, 2689–2718, https://doi.org/10.5194/gmd-16-2689-2023, https://doi.org/10.5194/gmd-16-2689-2023, 2023
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Understanding how air pollution varies across space and time is of key importance for the safeguarding of human health. This work arose in the context of the project EARLY-ADAPT, for which the Barcelona Supercomputing Center developed an air pollution database covering all of Europe. Through different statistical methods, we compared two global pollution models against measurements from ground stations and found significant discrepancies between the observed and the modeled surface pollution.
Andrew Geiss, Po-Lun Ma, Balwinder Singh, and Joseph C. Hardin
Geosci. Model Dev., 16, 2355–2370, https://doi.org/10.5194/gmd-16-2355-2023, https://doi.org/10.5194/gmd-16-2355-2023, 2023
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Atmospheric aerosols play a critical role in Earth's climate, but it is too computationally expensive to directly model their interaction with radiation in climate simulations. This work develops a new neural-network-based parameterization of aerosol optical properties for use in the Energy Exascale Earth System Model that is much more accurate than the current one; it also introduces a unique model optimization method that involves randomly generating neural network architectures.
Joey C. Y. Lam, Amos P. K. Tai, Jason A. Ducker, and Christopher D. Holmes
Geosci. Model Dev., 16, 2323–2342, https://doi.org/10.5194/gmd-16-2323-2023, https://doi.org/10.5194/gmd-16-2323-2023, 2023
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We developed a new component within an atmospheric chemistry model to better simulate plant ecophysiological processes relevant for ozone air quality. We showed that it reduces simulated biases in plant uptake of ozone in prior models. The new model enables us to explore how future climatic changes affect air quality via affecting plants, examine ozone–vegetation interactions and feedbacks, and evaluate the impacts of changing atmospheric chemistry and climate on vegetation productivity.
Qian Shu, Sergey L. Napelenok, William T. Hutzell, Kirk R. Baker, Barron H. Henderson, Benjamin N. Murphy, and Christian Hogrefe
Geosci. Model Dev., 16, 2303–2322, https://doi.org/10.5194/gmd-16-2303-2023, https://doi.org/10.5194/gmd-16-2303-2023, 2023
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Source attribution methods are generally used to determine culpability of precursor emission sources to ambient pollutant concentrations. However, source attribution of secondarily formed pollutants such as ozone and its precursors cannot be explicitly measured, making evaluation of source apportionment methods challenging. In this study, multiple apportionment approach comparisons show common features but still reveal wide variations in predicted sector contribution and species dependency.
Rüdiger Brecht, Lucie Bakels, Alex Bihlo, and Andreas Stohl
Geosci. Model Dev., 16, 2181–2192, https://doi.org/10.5194/gmd-16-2181-2023, https://doi.org/10.5194/gmd-16-2181-2023, 2023
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We use neural-network-based single-image super-resolution to improve the upscaling of meteorological wind fields to be used for particle dispersion models. This deep-learning-based methodology improves the standard linear interpolation typically used in particle dispersion models. The improvement of wind fields leads to substantial improvement in the computed trajectories of the particles.
Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodriguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
Geosci. Model Dev., 16, 2193–2213, https://doi.org/10.5194/gmd-16-2193-2023, https://doi.org/10.5194/gmd-16-2193-2023, 2023
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This work aims to derive and evaluate a general statistical post-processing tool specifically designed for the street scale that can be applied to any urban air quality system. Our data fusion methodology corrects NO2 fields based on continuous hourly observations and experimental campaigns. This study enables us to obtain exceedance probability maps of air quality standards. In 2019, 13 % of the Barcelona area had a 70 % or higher probability of exceeding the annual legal NO2 limit of 40 µg/m3.
Liang Wang, Bingcheng Wan, Shaohui Zhou, Haofei Sun, and Zhiqiu Gao
Geosci. Model Dev., 16, 2167–2179, https://doi.org/10.5194/gmd-16-2167-2023, https://doi.org/10.5194/gmd-16-2167-2023, 2023
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The past 24 h TC trajectories and meteorological field data were used to forecast TC tracks in the northwestern Pacific from hours 6–72 based on GRU_CNN, which we proposed in this paper and which has better prediction results than traditional single deep-learning methods. The historical steering flow of cyclones has a significant effect on improving the accuracy of short-term forecasting, while, in long-term forecasting, the SST and geopotential height will have a particular impact.
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
Geosci. Model Dev., 16, 2037–2054, https://doi.org/10.5194/gmd-16-2037-2023, https://doi.org/10.5194/gmd-16-2037-2023, 2023
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Kinetic multi-layer models (KMs) successfully describe heterogeneous and multiphase atmospheric chemistry. In applications requiring repeated execution, however, these models can be too expensive. We trained machine learning surrogate models on output of the model KM-SUB and achieved high correlations. The surrogate models run orders of magnitude faster, which suggests potential applicability in global optimization tasks and as sub-modules in large-scale atmospheric models.
Elena Fillola, Raul Santos-Rodriguez, Alistair Manning, Simon O'Doherty, and Matt Rigby
Geosci. Model Dev., 16, 1997–2009, https://doi.org/10.5194/gmd-16-1997-2023, https://doi.org/10.5194/gmd-16-1997-2023, 2023
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Lagrangian particle dispersion models are used extensively for the estimation of greenhouse gas (GHG) fluxes using atmospheric observations. However, these models do not scale well as data volumes increase. Here, we develop a proof-of-concept machine learning emulator that can produce outputs similar to those of the dispersion model, but 50 000 times faster, using only meteorological inputs. This works demonstrates the potential of machine learning to accelerate GHG estimations across the globe.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
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Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Kun Wang, Chao Gao, Kai Wu, Kaiyun Liu, Haofan Wang, Mo Dan, Xiaohui Ji, and Qingqing Tong
Geosci. Model Dev., 16, 1961–1973, https://doi.org/10.5194/gmd-16-1961-2023, https://doi.org/10.5194/gmd-16-1961-2023, 2023
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This study establishes an easy-to-use and integrated framework for a model-ready emission inventory for the Weather Research and Forecasting (WRF)–Air Quality Numerical Model (AQM). A free tool called the ISAT (Inventory Spatial Allocation Tool) was developed based on this framework. ISAT helps users complete the workflow from the WRF nested-domain configuration to a model-ready emission inventory for AQM with a regional emission inventory and a shapefile for the target region.
Jagat S. H. Bisht, Prabir K. Patra, Masayuki Takigawa, Takashi Sekiya, Yugo Kanaya, Naoko Saitoh, and Kazuyuki Miyazaki
Geosci. Model Dev., 16, 1823–1838, https://doi.org/10.5194/gmd-16-1823-2023, https://doi.org/10.5194/gmd-16-1823-2023, 2023
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In this study, we estimated CH4 fluxes using an advanced 4D-LETKF method. The system was tested and optimized using observation system simulation experiments (OSSEs), where a known surface emission distribution is retrieved from synthetic observations. The availability of satellite measurements has increased, and there are still many missions focused on greenhouse gas observations that have not yet launched. The technique being referred to has the potential to improve estimates of CH4 fluxes.
Ruizi Shi and Fanghua Xu
Geosci. Model Dev., 16, 1839–1856, https://doi.org/10.5194/gmd-16-1839-2023, https://doi.org/10.5194/gmd-16-1839-2023, 2023
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Based on the Gaussian quadrature method, a fast algorithm of sea-spray-mediated heat flux is developed. Compared with the widely used single-radius algorithm, the new fast algorithm shows a better agreement with the full spectrum integral of spray flux. The new fast algorithm is evaluated in a coupled modeling system, and the simulations of sea surface temperature, wind speed and wave height are improved. Thereby, the new fast algorithm has great potential to be used in coupled modeling systems.
Forwood Wiser, Bryan K. Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
Geosci. Model Dev., 16, 1801–1821, https://doi.org/10.5194/gmd-16-1801-2023, https://doi.org/10.5194/gmd-16-1801-2023, 2023
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We developed a reduced model of atmospheric isoprene oxidation, AMORE-Isoprene 1.0. It was created using a new Automated Model Reduction (AMORE) method designed to simplify complex chemical mechanisms with minimal manual adjustments to the output. AMORE-Isoprene 1.0 has improved accuracy and similar size to other reduced isoprene mechanisms. When included in the CRACMM mechanism, it improved the accuracy of EPA’s CMAQ model predictions for the northeastern USA compared to observations.
Jonathan D. Labriola, Jeremy A. Gibbs, and Louis J. Wicker
Geosci. Model Dev., 16, 1779–1799, https://doi.org/10.5194/gmd-16-1779-2023, https://doi.org/10.5194/gmd-16-1779-2023, 2023
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Observing system simulation experiments (OSSEs) are simulated case studies used to understand how different assimilated weather observations impact forecast skill. This study introduces the methods used to create an OSSE for a tornadic quasi-linear convective system event. These steps provide an opportunity to simulate a realistic high-impact weather event and can be used to encourage a more diverse set of OSSEs.
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023, https://doi.org/10.5194/gmd-16-1713-2023, 2023
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Building on the baseline of RAL1, the RAL2 science configuration is used for regional modelling around the UM partnership and in operations at the Met Office. RAL2 has been tested in different parts of the world including Australia, India and the UK. RAL2 increases medium and low cloud amounts in the mid-latitudes compared to RAL1, leading to improved cloud forecasts and a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates.
Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
Geosci. Model Dev., 16, 1641–1659, https://doi.org/10.5194/gmd-16-1641-2023, https://doi.org/10.5194/gmd-16-1641-2023, 2023
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Ammonia in the atmosphere has wide impacts on the ecological environment and air quality, and its emission from soil volatilization is highly sensitive to meteorology, making it challenging to be well captured in models. We developed a dynamic emission model capable of calculating ammonia emission interactively with meteorological and soil conditions. Such a coupling of soil emission with meteorology provides a better understanding of ammonia emission and its contribution to atmospheric aerosol.
Linlu Mei, Vladimir Rozanov, Alexei Rozanov, and John P. Burrows
Geosci. Model Dev., 16, 1511–1536, https://doi.org/10.5194/gmd-16-1511-2023, https://doi.org/10.5194/gmd-16-1511-2023, 2023
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This paper summarizes recent developments of aerosol, cloud and surface reflectance databases and models in the framework of the software package SCIATRAN. These updates and developments extend the capabilities of the radiative transfer modeling, especially by accounting for different kinds of vertical inhomogeneties. Vertically inhomogeneous clouds and different aerosol types can be easily accounted for within SCIATRAN (V4.6). The widely used surface models and databases are now available.
Adrian Rojas-Campos, Michael Langguth, Martin Wittenbrink, and Gordon Pipa
Geosci. Model Dev., 16, 1467–1480, https://doi.org/10.5194/gmd-16-1467-2023, https://doi.org/10.5194/gmd-16-1467-2023, 2023
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Our paper presents an alternative approach for generating high-resolution precipitation maps based on the nonlinear combination of the complete set of variables of the numerical weather predictions. This process combines the super-resolution task with the bias correction in a single step, generating high-resolution corrected precipitation maps with a lead time of 3 h. We used using deep learning algorithms to combine the input information and increase the accuracy of the precipitation maps.
Robin N. Thor, Mariano Mertens, Sigrun Matthes, Mattia Righi, Johannes Hendricks, Sabine Brinkop, Phoebe Graf, Volker Grewe, Patrick Jöckel, and Steven Smith
Geosci. Model Dev., 16, 1459–1466, https://doi.org/10.5194/gmd-16-1459-2023, https://doi.org/10.5194/gmd-16-1459-2023, 2023
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We report on an inconsistency in the latitudinal distribution of aviation emissions between two versions of a data product which is widely used by researchers. From the available documentation, we do not expect such an inconsistency. We run a chemistry–climate model to compute the effect of the inconsistency in emissions on atmospheric chemistry and radiation and find that the radiative forcing associated with aviation ozone is 7.6 % higher when using the less recent version of the data.
Stefano Della Fera, Federico Fabiano, Piera Raspollini, Marco Ridolfi, Ugo Cortesi, Flavio Barbara, and Jost von Hardenberg
Geosci. Model Dev., 16, 1379–1394, https://doi.org/10.5194/gmd-16-1379-2023, https://doi.org/10.5194/gmd-16-1379-2023, 2023
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The long-term comparison between observed and simulated outgoing longwave radiances represents a strict test to evaluate climate model performance. In this work, 9 years of synthetic spectrally resolved radiances, simulated online on the basis of the atmospheric fields predicted by the EC-Earth global climate model (v3.3.3) in clear-sky conditions, are compared to IASI spectral radiance climatology in order to detect model biases in temperature and humidity at different atmospheric levels.
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
Geosci. Model Dev., 16, 1359–1377, https://doi.org/10.5194/gmd-16-1359-2023, https://doi.org/10.5194/gmd-16-1359-2023, 2023
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Aerosol has a large impact on climate. Using a lidar aerosol simulator ensures consistent comparisons between modeled and observed aerosol. We present a lidar aerosol simulator that applies a cloud masking and an aerosol detection threshold. We estimate the lidar signals that would be observed at 532 nm by the Cloud-Aerosol Lidar with Orthogonal Polarization overflying the atmosphere predicted by a climate model. Our comparison at the seasonal timescale shows a discrepancy in the Southern Ocean.
Christine Wiedinmyer, Yosuke Kimura, Elena C. McDonald-Buller, Louisa K. Emmons, Rebecca R. Buchholz, Wenfu Tang, Keenan Seto, Maxwell B. Joseph, Kelley C. Barsanti, Annmarie G. Carlton, and Robert Yokelson
EGUsphere, https://doi.org/10.5194/egusphere-2023-124, https://doi.org/10.5194/egusphere-2023-124, 2023
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The Fire INventory from NCAR (FINN) provides daily, global estimates of emissions from open fires based on satellite detections of hot spots. This version has been updated to apply MODIS and VIIRS satellite fire detections, and better represents both large and small fires.. FINNv2.5 generates more emissions than FINNv1, in general agreement with other fire emissions inventories. The new estimates are consistent with satellite observations, but uncertainties remain regionally and by pollutant.
Lichao Yang, Wansuo Duan, and Zifa Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-10, https://doi.org/10.5194/gmd-2023-10, 2023
Revised manuscript accepted for GMD
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We refine the ground meteorological stations by a nonlinear approach for improving the regional PM2.5 forecasts. The refined observation network (about 60 % of the current stations) can achieve almost the same improvements in PM2.5 forecasts as all the current station observations. The study will provide a scientific guidance to optimize the ground meteorological stations relative to PM2.5 forecasts and suggests an idea of cost-effective data assimilation for enhancing the PM2.5 forecast skills.
Michael S. Walters and David C. Wong
Geosci. Model Dev., 16, 1179–1190, https://doi.org/10.5194/gmd-16-1179-2023, https://doi.org/10.5194/gmd-16-1179-2023, 2023
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A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.
Sylvain Mailler, Laurent Menut, Arineh Cholakian, and Romain Pennel
Geosci. Model Dev., 16, 1119–1127, https://doi.org/10.5194/gmd-16-1119-2023, https://doi.org/10.5194/gmd-16-1119-2023, 2023
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Large or even
giantparticles of mineral dust exist in the atmosphere but, so far, solving an non-linear equation was needed to calculate the speed at which they fall in the atmosphere. The model we present, AerSett v1.0 (AERosol SETTling version 1.0), provides a new and simple way of calculating their free-fall velocity in the atmosphere, which will be useful to anyone trying to understand and represent adequately the transport of giant dust particles by the wind.
Sylvia Sullivan, Behrooz Keshtgar, Nicole Albern, Elzina Bala, Christoph Braun, Anubhav Choudhary, Johannes Hörner, Hilke Lentink, Georgios Papavasileiou, and Aiko Voigt
EGUsphere, https://doi.org/10.5194/egusphere-2023-109, https://doi.org/10.5194/egusphere-2023-109, 2023
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Clouds absorb and reemit infrared radiation from Earth's surface and absorb and reflect incoming solar radiation. As a result, they change atmospheric temperature gradients that drive large-scale circulation. To better simulate this circulation, we study how the radiative heating and cooling from clouds depends on model settings like grid spacing, whether we describe convection approximately or exactly, and the level of detail used to describe small-scale processes, or microphysics, in clouds.
Yen-Sen Lu, Garrett H. Good, and Hendrik Elbern
Geosci. Model Dev., 16, 1083–1104, https://doi.org/10.5194/gmd-16-1083-2023, https://doi.org/10.5194/gmd-16-1083-2023, 2023
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The Weather Forecasting and Research (WRF) model consists of many parameters and options that can be adapted to different conditions. This expansive sensitivity study uses a large-scale simulation system to determine the most suitable options for predicting cloud cover in Europe for deterministic and probabilistic weather predictions for day-ahead forecasting simulations.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
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When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi.
Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Phuc Thi Minh Ha, Yugo Kanaya, Fumikazu Taketani, Maria Dolores Andrés Hernández, Benjamin Schreiner, Klaus Pfeilsticker, and Kengo Sudo
Geosci. Model Dev., 16, 927–960, https://doi.org/10.5194/gmd-16-927-2023, https://doi.org/10.5194/gmd-16-927-2023, 2023
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HONO affects tropospheric oxidizing capacity; thus, it is implemented into the chemistry–climate model CHASER. The model substantially underpredicts daytime HONO, while nitrate photolysis on surfaces can supplement the daytime HONO budget. Current HONO chemistry predicts reductions of 20.4 % for global tropospheric NOx, 40–67 % for OH, and 30–45 % for O3 in the summer North Pacific. In contrast, OH and O3 winter levels in China are greatly enhanced.
Ryan Vella, Matthew Forrest, Jos Lelieveld, and Holger Tost
Geosci. Model Dev., 16, 885–906, https://doi.org/10.5194/gmd-16-885-2023, https://doi.org/10.5194/gmd-16-885-2023, 2023
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Biogenic volatile organic compounds (BVOCs) are released by vegetation and have a major impact on atmospheric chemistry and aerosol formation. Non-interacting vegetation constrains the majority of numerical models used to estimate global BVOC emissions, and thus, the effects of changing vegetation on emissions are not addressed. In this work, we replace the offline vegetation with dynamic vegetation states by linking a chemistry–climate model with a global dynamic vegetation model.
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
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We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Sam-Erik Walker, Sverre Solberg, Philipp Schneider, and Cristina Guerreiro
Geosci. Model Dev., 16, 573–595, https://doi.org/10.5194/gmd-16-573-2023, https://doi.org/10.5194/gmd-16-573-2023, 2023
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We have developed a statistical model for estimating trends in the daily air quality observations of NO2, O3, PM10 and PM2.5, adjusting for trends and short-term variations in meteorology. The model is general and may also be used for prediction purposes, including forecasting. It has been applied in a recent comprehensive study in Europe. Significant declines are shown for the pollutants from 2005 to 2019, mainly due to reductions in emissions not attributable to changes in meteorology.
Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner
Geosci. Model Dev., 16, 597–619, https://doi.org/10.5194/gmd-16-597-2023, https://doi.org/10.5194/gmd-16-597-2023, 2023
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Rapid changes in wind speed make the integration of wind energy produced during persistent orographic cold-air pools difficult to integrate into the electrical grid. By evaluating three versions of NOAA’s High-Resolution Rapid Refresh model, we demonstrate how model developments targeted during the second Wind Forecast Improvement Project improve the forecast of a persistent cold-air pool event.
Abhishekh Kumar Srivastava, Paul Aaron Ullrich, Deeksha Rastogi, Pouya Vahmani, Andrew Jones, and Richard Grotjahn
EGUsphere, https://doi.org/10.5194/egusphere-2022-1382, https://doi.org/10.5194/egusphere-2022-1382, 2023
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Stakeholders need high-resolution regional climate data for applications such as assessing water availability, mountain snowpack, etc. This study examines 3- and 24-hr historical precipitation over the contiguous United States in the 12-km WRF version 4.2.1-based dynamical downscaling of the ERA5 reanalysis. WRF improves precipitation characteristics such as the annual cycle and distribution of the precipitation maxima, but it also displays regionally and seasonally varying precipitation biases.
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023, https://doi.org/10.5194/gmd-16-509-2023, 2023
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We focus on the challenges associated with comparing atmospheric composition models with satellite products such as tropospheric NO2 columns. The aim is to highlight the methodological difficulties and propose sound ways of doing such comparisons. Building on the comparisons, a new satellite product is proposed and made available, which takes advantage of higher-resolution, regional atmospheric modelling to improve estimates of troposheric NO2 columns over Europe.
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Dominique Fonteyn, Frederik Tack, Felix Deutsch, Quentin Laffineur, Roeland Van Malderen, and Nele Veldeman
Geosci. Model Dev., 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023, https://doi.org/10.5194/gmd-16-479-2023, 2023
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High-resolution WRF-Chem simulations are conducted over Antwerp, Belgium, in June 2019 and evaluated using meteorological data and in situ, airborne, and spaceborne NO2 measurements. An intercomparison of model, aircraft, and TROPOMI NO2 columns is conducted to characterize biases in versions 1.3.1 and 2.3.1 of the satellite product. A mass balance method is implemented to provide improved emissions for simulating NO2 distribution over the study area.
Daan R. Scheepens, Irene Schicker, Kateřina Hlaváčková-Schindler, and Claudia Plant
Geosci. Model Dev., 16, 251–270, https://doi.org/10.5194/gmd-16-251-2023, https://doi.org/10.5194/gmd-16-251-2023, 2023
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The production of wind energy is increasing rapidly and relies heavily on atmospheric conditions. To ensure power grid stability, accurate predictions of wind speed are needed, especially in the short range and for extreme wind speed ranges. In this work, we demonstrate the forecasting skills of a data-driven deep learning model with model adaptations to suit higher wind speed ranges. The resulting model can be applied to other data and parameters, too, to improve nowcasting predictions.
Haixia Xiao, Yaqiang Wang, Yu Zheng, Yuanyuan Zheng, Xiaoran Zhuang, Hongyan Wang, and Mei Gao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-272, https://doi.org/10.5194/gmd-2022-272, 2023
Revised manuscript accepted for GMD
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Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CGs nowcasting has remained unattainable. Here, we developed a deep learning model – namely CGsNet – for 0–2 hours of quantitative CGs nowcasting, first achieving minute-kilometer-level forecasts. Based on CGsNet model, the average surface wind speed (ASWS) and peak wind gust speed (PWGS) predictions are obtained. Experiments indicate that CGsNet exhibits higher accuracy than the traditional method.
Peter J. M. Bosman and Maarten C. Krol
Geosci. Model Dev., 16, 47–74, https://doi.org/10.5194/gmd-16-47-2023, https://doi.org/10.5194/gmd-16-47-2023, 2023
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We describe an inverse modelling framework constructed around a simple model for the atmospheric boundary layer. This framework can be fed with various observation types to study the boundary layer and land–atmosphere exchange. With this framework, it is possible to estimate model parameters and the associated uncertainties. Some of these parameters are difficult to obtain directly by observations. An example application for a grassland in the Netherlands is included.
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023, https://doi.org/10.5194/gmd-16-1-2023, 2023
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Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Walter Hannah and Kyle Pressel
Geosci. Model Dev., 15, 8999–9013, https://doi.org/10.5194/gmd-15-8999-2022, https://doi.org/10.5194/gmd-15-8999-2022, 2022
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A multiscale modeling framework couples two models of the atmosphere that each cover different scale ranges. Traditionally, fluctuations in the small-scale model are not transported by the flow on the large-scale model grid, but this is hypothesized to be responsible for a persistent, unphysical checkerboard pattern. A method is presented to facilitate the transport of these small-scale fluctuations, analogous to how small-scale clouds and turbulence are transported in the real atmosphere.
Reimar Bauer, Jens-Uwe Grooß, Jörn Ungermann, May Bär, Markus Geldenhuys, and Lars Hoffmann
Geosci. Model Dev., 15, 8983–8997, https://doi.org/10.5194/gmd-15-8983-2022, https://doi.org/10.5194/gmd-15-8983-2022, 2022
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The Mission Support System (MSS) is an open source software package that has been used for planning flight tracks of scientific aircraft in multiple measurement campaigns during the last decade. Here, we describe the MSS software and its use during the SouthTRAC measurement campaign in 2019. As an example for how the MSS software is used in conjunction with many datasets, we describe the planning of a single flight probing orographic gravity waves propagating up into the lower mesosphere.
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