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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Emma Sands, Richard J. Pope, Ruth M. Doherty, Fiona M. O'Connor, Chris Wilson, and Hugh Pumphrey
Atmos. Chem. Phys., 24, 11081–11102, https://doi.org/10.5194/acp-24-11081-2024, https://doi.org/10.5194/acp-24-11081-2024, 2024
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Changes in vegetation alongside biomass burning impact regional atmospheric composition and air quality. Using satellite remote sensing, we find a clear linear relationship between forest cover and isoprene and a pronounced non-linear relationship between burned area and nitrogen dioxide in the southern Amazon, a region of substantial deforestation. These quantified relationships can be used for model evaluation and further exploration of biosphere-atmosphere interactions in Earth System Models.
Chris Wilson, Brian J. Kerridge, Richard Siddans, David P. Moore, Lucy J. Ventress, Emily Dowd, Wuhu Feng, Martyn P. Chipperfield, and John J. Remedios
Atmos. Chem. Phys., 24, 10639–10653, https://doi.org/10.5194/acp-24-10639-2024, https://doi.org/10.5194/acp-24-10639-2024, 2024
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The leaks from the Nord Stream gas pipelines in September 2022 released a large amount of methane (CH4) into the atmosphere. We provide observational data from a satellite instrument that shows a large CH4 plume over the North Sea off the coast of Scandinavia. We use this together with atmospheric models to quantify the CH4 leaked into the atmosphere from the pipelines. We find that 219–427 Gg CH4 was emitted, making this the largest individual fossil-fuel-related CH4 leak on record.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Emily Dowd, Alistair J. Manning, Bryn Orth-Lashley, Marianne Girard, James France, Rebecca E. Fisher, Dave Lowry, Mathias Lanoisellé, Joseph R. Pitt, Kieran M. Stanley, Simon O'Doherty, Dickon Young, Glen Thistlethwaite, Martyn P. Chipperfield, Emanuel Gloor, and Chris Wilson
Atmos. Meas. Tech., 17, 1599–1615, https://doi.org/10.5194/amt-17-1599-2024, https://doi.org/10.5194/amt-17-1599-2024, 2024
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We provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys of an active gas leak detected near Cheltenham, UK. GHGSat’s emission estimates broadly agree with the surface-based mobile survey and steps were taken to fix the leak, highlighting the importance of satellite data in identifying emissions and helping to reduce our human impact on climate change.
Ross Noel Bannister and Chris Wilson
EGUsphere, https://doi.org/10.5194/egusphere-2024-655, https://doi.org/10.5194/egusphere-2024-655, 2024
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Prior information is essential for the top-down estimation of CH4 surface fluxes. Errors in the prior are correlated in time/space, but accounting for correlations can be costly. We report on an efficient scheme to represent correlations in the inverse modelling system, INVICAT. The method is tested by assimilating CH4 observations using the scheme. Our findings show that accounting for spatio-temporal correlations improve CH4 flux estimates, demonstrating that the method should be further used.
Michael P. Cartwright, Richard J. Pope, Jeremy J. Harrison, Martyn P. Chipperfield, Chris Wilson, Wuhu Feng, David P. Moore, and Parvadha Suntharalingam
Atmos. Chem. Phys., 23, 10035–10056, https://doi.org/10.5194/acp-23-10035-2023, https://doi.org/10.5194/acp-23-10035-2023, 2023
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A 3-D chemical transport model, TOMCAT, is used to simulate global atmospheric carbonyl sulfide (OCS) distribution. Modelled OCS compares well with satellite observations of OCS from limb-sounding satellite observations. Model simulations also compare adequately with surface and atmospheric observations and suitably capture the seasonality of OCS and background concentrations.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
Atmos. Chem. Phys., 23, 7363–7382, https://doi.org/10.5194/acp-23-7363-2023, https://doi.org/10.5194/acp-23-7363-2023, 2023
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Surface observations of methane show that the seasonal cycle amplitude (SCA) of methane is decreasing in the northern high latitudes (NHLs) but increased globally (1995–2020). The NHL decrease is counterintuitive, as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate changes in SCA in the NHLs. We find well-mixed methane and changes in emissions from Canada, the Middle East, and Europe are the largest contributors to the SCA in NHLs.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
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.
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.
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.
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%.
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.
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.
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.
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).
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.
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.
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.
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
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Douwang Li, Zhe Wang, Siyi Zhao, Jiankai Zhang, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2025-955, https://doi.org/10.5194/egusphere-2025-955, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We find that wind variations at the equator (QBO) modulate the occurrence of Arctic polar stratospheric clouds (PSCs), which are key contributors to ozone depletion. During westerly QBO, the PSC occurrence is significantly greater than during easterly QBO. The QBO affects PSC mainly through temperature, while H2O and HNO3 have less effect. This suggests that future climate change may affect ozone recovery if it alters the QBO pattern. This study provides a new perspective on ozone prediction.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jamal Makkor, Mathias Palm, Matthias Buschmann, Emmanuel Mahieu, Martyn P. Chipperfield, and Justus Notholt
Atmos. Meas. Tech., 18, 1105–1114, https://doi.org/10.5194/amt-18-1105-2025, https://doi.org/10.5194/amt-18-1105-2025, 2025
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During the years 1950 and 1951, Marcel Migeotte took regular solar measurements in the form of paper rolls at the Jungfraujoch site. These historical spectra proved to be valuable for atmospheric research and needed to be saved for posterity. Therefore, a digitization method which used image-processing techniques was developed to extract them from the historical paper rolls. This allowed them to be saved in a machine-readable format that is easily accessible to the scientific community.
Diego Santaren, Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Frédéric Chevallier, Iolanda Ialongo, Hannakaisa Lindqvist, Janne Nurmela, Johanna Tamminen, Laia Amorós, Dominik Brunner, and Grégoire Broquet
Atmos. Meas. Tech., 18, 211–239, https://doi.org/10.5194/amt-18-211-2025, https://doi.org/10.5194/amt-18-211-2025, 2025
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This study evaluates data-driven inversion methods for estimating CO2 emissions from local sources, such as power plants and cities, using meteorological data and XCO2 and NO2 satellite images rather than atmospheric transport modeling. We assess and compare the performance of five different methods using simulations of 1 year of satellite images, taken from the upcoming Copernicus CO2 Monitoring Mission, covering 15 power plants and the city of Berlin, Germany.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3717, https://doi.org/10.5194/egusphere-2024-3717, 2024
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Tropospheric ozone (O3) is a harmful secondary atmospheric pollutant and an important greenhouse gas. Here, we present an in-depth analysis of lower-tropospheric sub-column O3 (LTCO3, surface – 6 km) records from three satellite products produced by the Rutherford Appleton Laboratory (RAL) over Europe between 1996 and 2017. Overall, we detect moderate negative trends in the satellite records, but corresponding model simulations and ozonesonde measurements show negligible trends.
Ryan Hossaini, David Sherry, Zihao Wang, Martyn P. Chipperfield, Wuhu Feng, David E. Oram, Karina E. Adcock, Stephen A. Montzka, Isobel J. Simpson, Andrea Mazzeo, Amber A. Leeson, Elliot Atlas, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 13457–13475, https://doi.org/10.5194/acp-24-13457-2024, https://doi.org/10.5194/acp-24-13457-2024, 2024
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DCE (1,2-dichloroethane) is an industrial chemical used to produce PVC (polyvinyl chloride). We analysed DCE production data to estimate global DCE emissions (2002–2020). The emissions were included in an atmospheric model and evaluated by comparing simulated DCE to DCE measurements in the troposphere. We show that DCE contributes ozone-depleting Cl to the stratosphere and that this has increased with increasing DCE emissions. DCE’s impact on stratospheric O3 is currently small but non-zero.
Anthony Rey-Pommier, Alexandre Héraud, Frédéric Chevallier, Philippe Ciais, Theodoros Christoudias, Jonilda Kushta, and Jean Sciare
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-410, https://doi.org/10.5194/essd-2024-410, 2024
Revised manuscript under review for ESSD
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In this study, we estimate emissions of nitrogen oxides (NOx) in 2022 at high-resolution at the global scale, using satellite observations. We provide maps of the emissions and identify several types of sources. Our results are similar to the EDGAR emission inventory. However, differences are found in countries with lower observation densities and lower emissions.
Emma Sands, Richard J. Pope, Ruth M. Doherty, Fiona M. O'Connor, Chris Wilson, and Hugh Pumphrey
Atmos. Chem. Phys., 24, 11081–11102, https://doi.org/10.5194/acp-24-11081-2024, https://doi.org/10.5194/acp-24-11081-2024, 2024
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Changes in vegetation alongside biomass burning impact regional atmospheric composition and air quality. Using satellite remote sensing, we find a clear linear relationship between forest cover and isoprene and a pronounced non-linear relationship between burned area and nitrogen dioxide in the southern Amazon, a region of substantial deforestation. These quantified relationships can be used for model evaluation and further exploration of biosphere-atmosphere interactions in Earth System Models.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
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This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Chris Wilson, Brian J. Kerridge, Richard Siddans, David P. Moore, Lucy J. Ventress, Emily Dowd, Wuhu Feng, Martyn P. Chipperfield, and John J. Remedios
Atmos. Chem. Phys., 24, 10639–10653, https://doi.org/10.5194/acp-24-10639-2024, https://doi.org/10.5194/acp-24-10639-2024, 2024
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The leaks from the Nord Stream gas pipelines in September 2022 released a large amount of methane (CH4) into the atmosphere. We provide observational data from a satellite instrument that shows a large CH4 plume over the North Sea off the coast of Scandinavia. We use this together with atmospheric models to quantify the CH4 leaked into the atmosphere from the pipelines. We find that 219–427 Gg CH4 was emitted, making this the largest individual fossil-fuel-related CH4 leak on record.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-2736, https://doi.org/10.5194/egusphere-2024-2736, 2024
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Globally, lockdowns were implemented to limit the spread of COVID-19, leading to a decrease in emissions of key air pollutants. Here, we use novel satellite data and a chemistry model to investigate the impact of the pandemic on tropospheric ozone (O3), a key pollutant, in 2020. Overall, we found substantial decreases of up to 20 %, 2/3s of which came from emission reductions while 1/3 was due to a decrease in the stratospheric ozone flux into the troposphere.
Alok K. Pandey, David S. Stevenson, Alcide Zhao, Richard J. Pope, Ryan Hossaini, Krishan Kumar, and Marytn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-2686, https://doi.org/10.5194/egusphere-2024-2686, 2024
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Nitrogen dioxide is an air pollutant largely controlled by human activity that affects ozone, methane and aerosols. Satellite instruments can quantify column NO2, and by carefully matching the time and location of measurements, enable evaluation of model simulations. NO2 over SE Asia is assessed, showing that the model captures many features of the measurements, but also important differences that suggest model deficiencies in representing several aspects of the atmospheric chemistry of NO2.
Richard J. Pope, Fiona M. O'Connor, Mohit Dalvi, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Brice Barret, Eric Le Flochmoen, Anne Boynard, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, Catherine Wespes, and Richard Rigby
Atmos. Chem. Phys., 24, 9177–9195, https://doi.org/10.5194/acp-24-9177-2024, https://doi.org/10.5194/acp-24-9177-2024, 2024
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Ozone is a potent air pollutant in the lower troposphere, with adverse impacts on human health. Satellite records of tropospheric ozone currently show large-scale inconsistencies in long-term trends. Our detailed study of the potential factors (e.g. satellite errors, where the satellite can observe ozone) potentially driving these inconsistencies found that, in North America, Europe, and East Asia, the underlying trends are typically small with large uncertainties.
Yang Li, Wuhu Feng, Xin Zhou, Yajuan Li, and Martyn P. Chipperfield
Atmos. Chem. Phys., 24, 8277–8293, https://doi.org/10.5194/acp-24-8277-2024, https://doi.org/10.5194/acp-24-8277-2024, 2024
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The Tibetan Plateau (TP), the highest and largest plateau, experiences strong surface solar UV radiation, whose excess can cause harmful influences on local biota. Hence, it is critical to study TP ozone. We find ENSO, the strongest interannual phenomenon, tends to induce tropospheric temperature change and thus modulate tropopause variability, which in turn favours ozone change over the TP. Our results have implications for a better understanding of the interannual variability of TP ozone.
Santiago Botía, Saqr Munassar, Thomas Koch, Danilo Custodio, Luana S. Basso, Shujiro Komiya, Jost V. Lavric, David Walter, Manuel Gloor, Giordane Martins, Stijn Naus, Gerbrand Koren, Ingrid Luijkx, Stijn Hantson, John B. Miller, Wouter Peters, Christian Rödenbeck, and Christoph Gerbig
EGUsphere, https://doi.org/10.5194/egusphere-2024-1735, https://doi.org/10.5194/egusphere-2024-1735, 2024
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This study uses CO2 data from the Amazon Tall Tower Observatory and airborne profiles to estimate net carbon exchange. We found that the biogeographic Amazon is a net carbon sink, while the Cerrado and Caatinga biomes are net carbon sources, resulting in an overall neutral balance. To further reduce the uncertainty in our estimates we call for an expansion of the monitoring capacity, especially in the Amazon-Andes foothills.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Nicolas Metzl, Claire Lo Monaco, Coraline Leseurre, Céline Ridame, Gilles Reverdin, Thi Tuyet Trang Chau, Frédéric Chevallier, and Marion Gehlen
Ocean Sci., 20, 725–758, https://doi.org/10.5194/os-20-725-2024, https://doi.org/10.5194/os-20-725-2024, 2024
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In the southern Indian Ocean, south of the polar front, an observed increase of sea surface fCO2 and a decrease of pH over 1985–2021 are mainly driven by anthropogenic CO2 uptake, but in the last decade (2010–2020) fCO2 and pH were stable in summer, highlighting the competitive balance between anthropogenic CO2 and primary production. In the water column the increase of anthropogenic CO2 concentrations leads to migration of the aragonite saturation state from 600 m in 1985 up to 400 m in 2021.
Richard J. Pope, Alexandru Rap, Matilda A. Pimlott, Brice Barret, Eric Le Flochmoen, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Anne Boynard, Christian Retscher, Wuhu Feng, Richard Rigby, Sandip S. Dhomse, Catherine Wespes, and Martyn P. Chipperfield
Atmos. Chem. Phys., 24, 3613–3626, https://doi.org/10.5194/acp-24-3613-2024, https://doi.org/10.5194/acp-24-3613-2024, 2024
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Tropospheric ozone is an important short-lived climate forcer which influences the incoming solar short-wave radiation and the outgoing long-wave radiation in the atmosphere (8–15 km) where the balance between the two yields a net positive (i.e. warming) effect at the surface. Overall, we find that the tropospheric ozone radiative effect ranges between 1.21 and 1.26 W m−2 with a negligible trend (2008–2017), suggesting that tropospheric ozone influences on climate have remained stable with time.
Emily Dowd, Alistair J. Manning, Bryn Orth-Lashley, Marianne Girard, James France, Rebecca E. Fisher, Dave Lowry, Mathias Lanoisellé, Joseph R. Pitt, Kieran M. Stanley, Simon O'Doherty, Dickon Young, Glen Thistlethwaite, Martyn P. Chipperfield, Emanuel Gloor, and Chris Wilson
Atmos. Meas. Tech., 17, 1599–1615, https://doi.org/10.5194/amt-17-1599-2024, https://doi.org/10.5194/amt-17-1599-2024, 2024
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We provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys of an active gas leak detected near Cheltenham, UK. GHGSat’s emission estimates broadly agree with the surface-based mobile survey and steps were taken to fix the leak, highlighting the importance of satellite data in identifying emissions and helping to reduce our human impact on climate change.
Ross Noel Bannister and Chris Wilson
EGUsphere, https://doi.org/10.5194/egusphere-2024-655, https://doi.org/10.5194/egusphere-2024-655, 2024
Preprint archived
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Prior information is essential for the top-down estimation of CH4 surface fluxes. Errors in the prior are correlated in time/space, but accounting for correlations can be costly. We report on an efficient scheme to represent correlations in the inverse modelling system, INVICAT. The method is tested by assimilating CH4 observations using the scheme. Our findings show that accounting for spatio-temporal correlations improve CH4 flux estimates, demonstrating that the method should be further used.
Martyn P. Chipperfield and Slimane Bekki
Atmos. Chem. Phys., 24, 2783–2802, https://doi.org/10.5194/acp-24-2783-2024, https://doi.org/10.5194/acp-24-2783-2024, 2024
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We give a personal perspective on recent issues related to the depletion of stratospheric ozone and some newly emerging challenges. We first provide a brief review of historic work on understanding the ozone layer and review ozone recovery from the effects of halogenated source gases and the Montreal Protocol. We then discuss the recent observations of ozone depletion from Australian fires in early 2020 and the Hunga Tonga–Hunga Ha'apai volcano in January 2022.
Ailish M. Graham, Richard J. Pope, Martyn P. Chipperfield, Sandip S. Dhomse, Matilda Pimlott, Wuhu Feng, Vikas Singh, Ying Chen, Oliver Wild, Ranjeet Sokhi, and Gufran Beig
Atmos. Chem. Phys., 24, 789–806, https://doi.org/10.5194/acp-24-789-2024, https://doi.org/10.5194/acp-24-789-2024, 2024
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Our paper uses novel satellite datasets and high-resolution emissions datasets alongside a back-trajectory model to investigate the balance of local and external sources influencing NOx air pollution changes in Delhi. We find in the post-monsoon season that NOx from local and non-local transport emissions contributes most to poor air quality in Delhi. Therefore, air quality mitigation strategies in Delhi and surrounding regions are used to control this issue.
Thi-Tuyet-Trang Chau, Marion Gehlen, Nicolas Metzl, and Frédéric Chevallier
Earth Syst. Sci. Data, 16, 121–160, https://doi.org/10.5194/essd-16-121-2024, https://doi.org/10.5194/essd-16-121-2024, 2024
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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° resolutions. The high-resolution reconstructions outperform their 1° 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 monitoring changes in ocean carbon uptake and ocean acidification.
Andrea Pazmiño, Florence Goutail, Sophie Godin-Beekmann, Alain Hauchecorne, Jean-Pierre Pommereau, Martyn P. Chipperfield, Wuhu Feng, Franck Lefèvre, Audrey Lecouffe, Michel Van Roozendael, Nis Jepsen, Georg Hansen, Rigel Kivi, Kimberly Strong, and Kaley A. Walker
Atmos. Chem. Phys., 23, 15655–15670, https://doi.org/10.5194/acp-23-15655-2023, https://doi.org/10.5194/acp-23-15655-2023, 2023
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The vortex-averaged ozone loss over the last 3 decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from the SAOZ network and MSR2 reanalysis. Three metrics were developed to compute ozone trends since 2000. The study confirms the ozone recovery in the Antarctic and shows a potential sign of quantitative detection of ozone recovery in the Arctic that needs to be robustly confirmed in the future.
Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, and Richard Rigby
Atmos. Chem. Phys., 23, 14933–14947, https://doi.org/10.5194/acp-23-14933-2023, https://doi.org/10.5194/acp-23-14933-2023, 2023
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Ozone is a potent air pollutant, and we present the first study to investigate long-term changes in lower tropospheric column ozone (LTCO3) from space. We have constructed a merged LTCO3 dataset from GOME-1, SCIAMACHY and OMI between 1996 and 2017. Comparing LTCO3 between the 1996–2000 and 2013–2017 5-year averages, we find significant positive increases in the tropics/sub-tropics, while in the northern mid-latitudes, we find small-scale differences.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Sandip S. Dhomse and Martyn P. Chipperfield
Earth Syst. Sci. Data, 15, 5105–5120, https://doi.org/10.5194/essd-15-5105-2023, https://doi.org/10.5194/essd-15-5105-2023, 2023
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There are no long-term stratospheric profile data sets for two very important greenhouse gases: methane (CH4) and nitrous oxide (N2O). Along with radiative feedback, these species play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite measurements with a chemical model to construct long-term gap-free profile data sets for CH4 and N2O. We aim to construct similar data sets for other important trace gases (e.g. O3, Cly, NOy species).
Ioannis Cheliotis, Thomas Lauvaux, Jinghui Lian, Theodoros Christoudias, George Georgiou, Alba Badia, Frédéric Chevallier, Pramod Kumar, Yathin Kudupaje, Ruixue Lei, and Philippe Ciais
EGUsphere, https://doi.org/10.5194/egusphere-2023-2487, https://doi.org/10.5194/egusphere-2023-2487, 2023
Preprint withdrawn
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A consistent estimation of CO2 emissions is complicated due to the scarcity of CO2 observations. In this study, we showcase the potential to improve the CO2 emissions estimations from the NO2 concentrations based on the NO2-to-CO2 ratio, which should be constant for a source co-emitting NO2 and CO2, by comparing satellite observations with atmospheric chemistry and transport model simulations for NO2 and CO2. Furthermore, we demonstrate the significance of the chemistry in NO2 simulations.
Ewa M. Bednarz, Ryan Hossaini, and Martyn P. Chipperfield
Atmos. Chem. Phys., 23, 13701–13711, https://doi.org/10.5194/acp-23-13701-2023, https://doi.org/10.5194/acp-23-13701-2023, 2023
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We quantify, for the first time, the time-varying impact of uncontrolled emissions of chlorinated very short-lived substances (Cl-VSLSs) on stratospheric ozone using a state-of-the-art chemistry-climate model. We demonstrate that Cl-VSLSs already have a non-negligible impact on stratospheric ozone, including a local reduction of up to ~7 DU in Arctic ozone in the cold winter of 2019/20, and any so future growth in emissions will continue to offset some of the benefits of the Montreal Protocol.
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev., 16, 6187–6209, https://doi.org/10.5194/gmd-16-6187-2023, https://doi.org/10.5194/gmd-16-6187-2023, 2023
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Development and performance of the new DEST chemistry scheme of UM–UKCA is described. The scheme extends the standard StratTrop scheme by including important updates to the halogen chemistry, thus allowing process-oriented studies of stratospheric ozone depletion and recovery, including impacts from both controlled long-lived ozone-depleting substances and emerging issues around uncontrolled, very short-lived substances. It will thus aid studies in support of future ozone assessment reports.
Zoé Lloret, Frédéric Chevallier, Anne Cozic, Marine Remaud, and Yann Meurdesoif
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-140, https://doi.org/10.5194/gmd-2023-140, 2023
Revised manuscript not accepted
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In this study, we evaluate the performance of a new model coupling, ICO, for simulating atmospheric carbon dioxide (CO2) transport. Using an unstructured grid, our model accurately captures seasonal CO2 variations at surface stations. The model exhibits comparable accuracy to a reference configuration and offers advantages in computational speed and storage. This highlights the importance of advanced modeling approaches and high-resolution grids in refining climate models.
Anthony Rey-Pommier, Frédéric Chevallier, Philippe Ciais, Jonilda Kushta, Theodoros Christoudias, I. Safak Bayram, and Jean Sciare
Atmos. Chem. Phys., 23, 13565–13583, https://doi.org/10.5194/acp-23-13565-2023, https://doi.org/10.5194/acp-23-13565-2023, 2023
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We use four years (2019–2022) of TROPOMI NO2 data to map NOx emissions in Qatar. We estimate average monthly emissions for the country and industrial facilities and derive an emission factor for the power sector. Monthly emissions have a weekly cycle reflecting the social norms in Qatar and an annual cycle consistent with the electricity production by gas-fired power plants. Their mean value is lower than the NOx emissions in global inventories but similar to the emissions reported for 2007.
Richard J. Pope, Brian J. Kerridge, Martyn P. Chipperfield, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Matilda A. Pimlott, Wuhu Feng, Edward Comyn-Platt, Garry D. Hayman, Stephen R. Arnold, and Ailish M. Graham
Atmos. Chem. Phys., 23, 13235–13253, https://doi.org/10.5194/acp-23-13235-2023, https://doi.org/10.5194/acp-23-13235-2023, 2023
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In the summer of 2018, Europe experienced several persistent large-scale ozone (O3) pollution episodes. Satellite tropospheric O3 and surface O3 data recorded substantial enhancements in 2018 relative to other years. Targeted model simulations showed that meteorological processes and emissions controlled the elevated surface O3, while mid-tropospheric O3 enhancements were dominated by stratospheric O3 intrusion and advection of North Atlantic O3-rich air masses into Europe.
Yajuan Li, Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Jianchun Bian, Yuan Xia, and Dong Guo
Atmos. Chem. Phys., 23, 13029–13047, https://doi.org/10.5194/acp-23-13029-2023, https://doi.org/10.5194/acp-23-13029-2023, 2023
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For the first time a regularized multivariate regression model is used to estimate stratospheric ozone trends. Regularized regression avoids the over-fitting issue due to correlation among explanatory variables. We demonstrate that there are considerable differences in satellite-based and chemical-model-based ozone trends, highlighting large uncertainties in our understanding about ozone variability. We argue that caution is needed when interpreting results with different methods and datasets.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Michael P. Cartwright, Richard J. Pope, Jeremy J. Harrison, Martyn P. Chipperfield, Chris Wilson, Wuhu Feng, David P. Moore, and Parvadha Suntharalingam
Atmos. Chem. Phys., 23, 10035–10056, https://doi.org/10.5194/acp-23-10035-2023, https://doi.org/10.5194/acp-23-10035-2023, 2023
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A 3-D chemical transport model, TOMCAT, is used to simulate global atmospheric carbonyl sulfide (OCS) distribution. Modelled OCS compares well with satellite observations of OCS from limb-sounding satellite observations. Model simulations also compare adequately with surface and atmospheric observations and suitably capture the seasonality of OCS and background concentrations.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
Atmos. Chem. Phys., 23, 7363–7382, https://doi.org/10.5194/acp-23-7363-2023, https://doi.org/10.5194/acp-23-7363-2023, 2023
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Surface observations of methane show that the seasonal cycle amplitude (SCA) of methane is decreasing in the northern high latitudes (NHLs) but increased globally (1995–2020). The NHL decrease is counterintuitive, as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate changes in SCA in the NHLs. We find well-mixed methane and changes in emissions from Canada, the Middle East, and Europe are the largest contributors to the SCA in NHLs.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
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
Atmos. Chem. Phys., 23, 6599–6611, https://doi.org/10.5194/acp-23-6599-2023, https://doi.org/10.5194/acp-23-6599-2023, 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.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
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.
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.
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.
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%.
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
Preprint withdrawn
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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
Short summary
Short summary
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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Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
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AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
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Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
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Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-157, https://doi.org/10.5194/gmd-2024-157, 2024
Revised manuscript accepted for GMD
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This study combines Machine Learning with Concentration-Weighted Trajectory Analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
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Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
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