Articles | Volume 15, issue 11
https://doi.org/10.5194/gmd-15-4555-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-4555-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
14 Jun 2022
Development and technical paper |
| 14 Jun 2022
| 14 Jun 2022
Order of magnitude wall time improvement of variational methane inversions by physical parallelization: a demonstration using TM5-4DVAR
SRON Netherlands Institute for Space Research, Utrecht, the
Netherlands
now at: Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Sander Houweling
Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam,
the Netherlands
Arjo Segers
TNO Department of Climate, Air and Sustainability, Utrecht, the
Netherlands
Related authors
No articles found.
Simeng Li, Enrico Dammers, Beatriz Herrera, Arjo Segers, Mark W. Shephard, Martin Van Damme, Lieven Clarisse, Shelley van der Graaf, Roy Wichink Kruit, and Jan Willem Erisman
EGUsphere, https://doi.org/10.5194/egusphere-2026-4245, https://doi.org/10.5194/egusphere-2026-4245, 2026
This preprint is open for discussion and under review for Geoscientific Instrumentation, Methods and Data Systems (GI).
Short summary
Short summary
Ammonia from agriculture can harm ecosystems and air quality, but tracking emissions accurately is difficult. We developed a method combining in situ measurements and satellite observations to estimate ammonia emissions across the Netherlands. In situ measurement captures local detail while satellites provide broad coverage; combining both improves estimates. We also identified where new measurement stations would most improve emission monitoring, helping guide future network design.
Mengrong Lu, Huilin Chen, Xun Zhang, Xuguang Chi, Chong Wei, Shuangxi Fang, Fenjuan Wang, Eleftherios Ioannidis, Friedemann Reum, Xinlu Wang, Prajal Pradhan, Wouter Peters, Klaus Hubacek, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2026-3879, https://doi.org/10.5194/egusphere-2026-3879, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Effective methane mitigation requires accurate knowledge of the spatial and temporal distribution of sources and sinks. Using high-resolution atmospheric modeling and ground-based observations, we estimated methane emissions in East Asia, focusing on the Yangtze River Delta. Emissions are lower than most inventories suggest, but show a clear seasonal cycle, with summer peaks driven by rice cultivation and natural sources. This seasonality is critical for emission tracking and mitigation design.
Tyler Wizenberg, Enrico Dammers, Arjo Segers, Mark W. Shephard, Pierre Coheur, Lieven Clarisse, Martin Van Damme, Henk Eskes, Roy Wichink Kruit, Shelley van der Graaf, and Martijn Schaap
Atmos. Chem. Phys., 26, 9589–9623, https://doi.org/10.5194/acp-26-9589-2026, https://doi.org/10.5194/acp-26-9589-2026, 2026
Short summary
Short summary
We combined five years of satellite data on ammonia and nitrogen dioxide concentrations with a regional model to better estimate nitrogen emissions and deposition in the Netherlands. This improved the accuracy of pollution maps and trends, especially in agricultural regions. Our approach helps identify when and where emissions are highest, supporting better air quality management and environmental protection by showing the benefits of using multiple complimentary satellite datasets together.
Bibhasvata Dasgupta, Sudhanshu Pandey, Sander Houweling, Malika Menoud, Carina van der Veen, John Miller, Ben Riddell-Young, Sylvia Englund Michel, Peter Sperlich, Shinji Morimoto, Ryo Fujita, Stephen Platt, Christine Groot Zwaaftink, Ingeborg Levin, Cordelia Veidt, Cathrine Lund Myhre, Ceres Woolley Maisch, Rebecca Fisher, Euan G. Nisbet, James France, Rowena Moss, Nicola Warwick, and Thomas Röckmann
Atmos. Chem. Phys., 26, 8601–8616, https://doi.org/10.5194/acp-26-8601-2026, https://doi.org/10.5194/acp-26-8601-2026, 2026
Short summary
Short summary
Methane is a strong greenhouse gas, and its rise since the mid-2000s is debated in terms of sources and sinks. Using top-down and bottom-up data, along with inversion models and methane isotopes (δ13C-CH4 and δD-CH4), we find that wetlands are the primary driver of post-2006 increases, followed by agriculture and fossil fuels. Methane's lifetime has decreased by about 0.1 years. We also assess how isotope signatures and sink processes influence uncertainties.
Shuai Sun, Yuzhong Zhang, Wei Chen, Shaomin Pan, Dongchuan Pu, Xin Tong, Huilin Chen, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2026-2165, https://doi.org/10.5194/egusphere-2026-2165, 2026
Short summary
Short summary
This study estimates methane emissions across Europe from 2019 to 2023 using atmospheric methane measurements from satellites and ground stations to improve understanding of emission sources. We find that total emissions are slightly higher than official reports, mainly due to livestock and waste, while emissions from fossil fuel production are lower in some regions. These results show that atmospheric measurements can improve independent verification of emissions and support climate policy.
Mengze Li, Robert B. Jackson, Marielle Saunois, Philippe Ciais, Ben Poulter, Josep G. Canadell, Prabir K. Patra, Hanqin Tian, Zhen Zhang, Etienne Fluet-Chouinard, Zutao Ouyang, Ting Zhang, David J. Beerling, Dmitry A. Belikov, Philippe Bousquet, Danilo Custodio, Naveen Chandra, Xinyu Dou, Nicola Gedney, Peter O. Hopcroft, Alison M. Hoyt, Kazuhito Ichii, Akihito Ito, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Masayuki Kondo, Fa Li, Tingting Li, Xiangyu Liu, Shamil Maksyutov, Avni Malhotra, Adrien Martinez, Kyle McDonald, Joe R. Melton, Jurek Müller, Yosuke Niwa, Shufen Pan, Shushi Peng, Changhui Peng, Zhangcai Qin, Peter Raymond, William Riley, Arjo Segers, Rona L. Thompson, Aki Tsuruta, Yi Xi, Kunxiaojia Yuan, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 18, 3507–3524, https://doi.org/10.5194/essd-18-3507-2026, https://doi.org/10.5194/essd-18-3507-2026, 2026
Short summary
Short summary
We proposed a framework that combines machine-learning and climate data to predict global natural vegetated wetland methane emissions for 2000–2025. We found that although total global emissions remained stable in the post-2020s, Northern Hemisphere emissions surged whilst tropical emissions fell. This approach allows us to rapidly monitor emissions and provides early warnings for climate impacts.
Clayton Roberts, Joannes D. Maasakkers, Tobias A. de Jong, Berend J. Schuit, Shubham Sharma, Theo Huegens, Anne-Wil van den Berg, Sander Houweling, and Ilse Aben
EGUsphere, https://doi.org/10.5194/egusphere-2026-1871, https://doi.org/10.5194/egusphere-2026-1871, 2026
Short summary
Short summary
Methane is a powerful greenhouse gas, and cutting its emissions can slow climate change in the near term. We have created a new machine-learning based method that uses satellite methane observations and weather data to better estimate emission rates for large methane plumes. It has proved more accurate than an existing physics-based method when tested on simulated satellite observations. When applied to real satellite observations, our method produces estimates that agree with other methods.
Ingrid Super, David Mathas, Bastiaan Jonkheid, Arjo Segers, and Jeroen Kuenen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-77, https://doi.org/10.5194/essd-2026-77, 2026
Revised manuscript accepted for ESSD
Short summary
Short summary
We present an emission uncertainty estimate to support atmospheric monitoring of greenhouse gas and air pollutant emissions using observations. We find significant uncertainties in country-total emissions and in the spatial distribution of emissions, largely dependent on the pollutant considered. A dataset is provided that lists emission uncertainties for a state-of-the-art European emission inventory.
Eleftherios Ioannidis, Antoon Meesters, Michael Steiner, Dominik Brunner, Friedemann Reum, Isabelle Pison, Antoine Berchet, Rona Thompson, Espen Sollum, Frank-Thomas Koch, Christoph Gerbig, Fenjuan Wang, Shamil Maksyutov, Aki Tsuruta, Maria Tenkanen, Tuula Aalto, Guillaume Monteil, Hong Lin, Ge Ren, Marko Scholze, and Sander Houweling
Earth Syst. Sci. Data, 18, 167–198, https://doi.org/10.5194/essd-18-167-2026, https://doi.org/10.5194/essd-18-167-2026, 2026
Short summary
Short summary
This paper describes a detailed study on CH4 European emissions, using different methodologies (9 total inverse models). The study spans over 15 years and provides detailed information on European CH4 emission trends and seasonality, using in-situ data, including Integrated Carbon Observation System (ICOS) network. Our results highlight the importance of improving details in the inversion setup, such as the treatment of lateral boundary conditions to narrow the uncertainty ranges further.
Bibhasvata Dasgupta, Malika Menoud, Carina van der Veen, Ingeborg Levin, Cordelia Veidt, Heiko Moossen, Sylvia Englund Michel, Peter Sperlich, Shinji Morimoto, Ryo Fujita, Taku Umezawa, Stephen Platt, Christine Groot Zwaaftink, Cathrine Lund Myhre, Rebecca Fisher, David Lowry, Euan G. Nisbet, James France, Ceres Woolley Maisch, Gordon Brailsford, Rowena Moss, Daisuke Goto, Sudhanshu Pandey, Sander Houweling, Nicola Warwick, and Thomas Röckmann
Atmos. Meas. Tech., 18, 6591–6607, https://doi.org/10.5194/amt-18-6591-2025, https://doi.org/10.5194/amt-18-6591-2025, 2025
Short summary
Short summary
We combined long-term methane mole fraction and isotope measurements from eight laboratories that sample high-latitude stations to compare, offset correct and harmonise the datasets into a hemisphere merged timeseries. Because each laboratory uses slightly different methods, we adjusted the data to make it directly comparable. This allowed us to create a consistent record of atmospheric methane concentration and its isotopes from 1988 to 2023.
Simeng Li, Enrico Dammers, Arjo Segers, and Jan Willem Erisman
Atmos. Chem. Phys., 25, 15593–15611, https://doi.org/10.5194/acp-25-15593-2025, https://doi.org/10.5194/acp-25-15593-2025, 2025
Short summary
Short summary
Between 2019 and 2022, a notable reduction in livestock numbers has been observed on Schiermonnikoog, a small island in the north of the Netherlands. We have assessed ammonia emissions using real-world measurements on the island, demonstrated emission decrease, and proposed a network to improve emission monitoring.
Marc Guevara, Augustin Colette, Antoine Guion, Valentin Petiot, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Andrea Bolignano, Paula Camps, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilaria D'Elia, Hugo Denier van der Gon, Gaël Descombes, John Douros, Hilde Fagerli, Yalda Fatahi, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Risto Hänninen, Kaj Hansen, Oriol Jorba, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Victor Lannuque, Frédérik Meleux, Agnes Nyíri, Yuliia Palamarchuk, Carlos Pérez García-Pando, Lennard Robertson, Felicita Russo, Arjo Segers, Mikhail Sofiev, Joanna Struzewska, Renske Timmermans, Andreas Uppstu, Alvaro Valdebenito, and Zhuyun Ye
Atmos. Chem. Phys., 25, 13245–13278, https://doi.org/10.5194/acp-25-13245-2025, https://doi.org/10.5194/acp-25-13245-2025, 2025
Short summary
Short summary
Air quality models require hourly emissions to accurately represent dispersion and physico-chemical processes in the atmosphere. Since emission inventories are typically provided at the annual level, emissions are downscaled to a refined temporal resolution using temporal profiles. This study quantifies the impact of using new anthropogenic temporal profiles on the performance of an European air quality multi-model ensemble. Overall, the findings indicate an improvement of the modelling results.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frédérik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilaria D'Elia, Massimo D'Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
Geosci. Model Dev., 18, 6835–6883, https://doi.org/10.5194/gmd-18-6835-2025, https://doi.org/10.5194/gmd-18-6835-2025, 2025
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The service relies on a distributed modelling production by 11 leading European modelling teams following stringent requirements with an operational design that has no equivalent in the world. All the products are free, open, and quality-assured and disseminated with a high level of reliability.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
Short summary
Short summary
Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
Short summary
Short summary
This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
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
Short summary
Short summary
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.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, and Ilse Aben
Atmos. Chem. Phys., 25, 555–574, https://doi.org/10.5194/acp-25-555-2025, https://doi.org/10.5194/acp-25-555-2025, 2025
Short summary
Short summary
The production of steel coincides with large emissions of greenhouse gases and air pollutants including carbon monoxide. European facilities are required to report their emissions, which are estimated using a variety of methods. We evaluate these estimates using carbon monoxide concentrations measured via satellite. We find generally good agreement between our values and those reported but also identify some uncertainties, showing that satellites can provide insights into these emissions.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
Short summary
Short summary
Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Li Fang, Jianbing Jin, Arjo Segers, Hong Liao, Ke Li, Bufan Xu, Wei Han, Mijie Pang, and Hai Xiang Lin
Geosci. Model Dev., 16, 4867–4882, https://doi.org/10.5194/gmd-16-4867-2023, https://doi.org/10.5194/gmd-16-4867-2023, 2023
Short summary
Short summary
Machine learning models have gained great popularity in air quality prediction. However, they are only available at air quality monitoring stations. In contrast, chemical transport models (CTM) provide predictions that are continuous in the 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional feature selection machine learning prediction (RFSML v1.0) and a CTM prediction.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 23, 8899–8919, https://doi.org/10.5194/acp-23-8899-2023, https://doi.org/10.5194/acp-23-8899-2023, 2023
Short summary
Short summary
We present a fast method to evaluate carbon monoxide emissions from cities in Africa. Carbon monoxide is important for climate change in an indirect way, as it is linked to ozone, methane, and carbon dioxide. Our measurements are made with a satellite that sees the entire globe every single day. This means that we can check from space whether the current knowledge of emission rates is up to date. We make the comparison and show that the emission rates in northern Africa are underestimated.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
Short summary
Short summary
This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Jianbing Jin, Bas Henzing, and Arjo Segers
Atmos. Chem. Phys., 23, 1641–1660, https://doi.org/10.5194/acp-23-1641-2023, https://doi.org/10.5194/acp-23-1641-2023, 2023
Short summary
Short summary
Aerosol models and satellite retrieval algorithms rely on different aerosol size assumptions. In practice, differences between simulations and observations do not always reflect the difference in aerosol amount. To avoid inconsistencies, we designed a hybrid assimilation approach. Different from a standard aerosol optical depth (AOD) assimilation that directly assimilates AODs, the hybrid one estimates aerosol size parameters by assimilating Ängström observations before assimilating the AODs.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Ilse Aben, Hugo A. C. Denier van der Gon, and Maarten C. Krol
Atmos. Chem. Phys., 22, 16053–16071, https://doi.org/10.5194/acp-22-16053-2022, https://doi.org/10.5194/acp-22-16053-2022, 2022
Short summary
Short summary
Hydroxyl radical (OH) is the important chemical species that determines the lifetime of some greenhouse gases and trace gases. OH plays a vital role in air pollution chemistry. OH has a short lifetime and is extremely difficult to measure directly. OH concentrations derived from the chemistry transport model (CTM) have uncertainties of >50 %. Therefore, in this study, OH is derived indirectly using satellite date in urban plumes.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev., 15, 7791–7807, https://doi.org/10.5194/gmd-15-7791-2022, https://doi.org/10.5194/gmd-15-7791-2022, 2022
Short summary
Short summary
This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, fewer training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
Short summary
Short summary
We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Jianbing Jin, Mijie Pang, Arjo Segers, Wei Han, Li Fang, Baojie Li, Haochuan Feng, Hai Xiang Lin, and Hong Liao
Atmos. Chem. Phys., 22, 6393–6410, https://doi.org/10.5194/acp-22-6393-2022, https://doi.org/10.5194/acp-22-6393-2022, 2022
Short summary
Short summary
Super dust storms reappeared in East Asia last spring after being absent for one and a half decades. Accurate simulation of such super sandstorms is valuable, but challenging due to imperfect emissions. In this study, the emissions of these dust storms are estimated by assimilating multiple observations. The results reveal that emissions originated from both China and Mongolia. However, for northern China, long-distance transport from Mongolia contributes much more dust than Chinese deserts.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
Short summary
Short summary
Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Yousef Albuhaisi, Ype van der Velde, and Sander Houweling
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-55, https://doi.org/10.5194/bg-2022-55, 2022
Manuscript not accepted for further review
Short summary
Short summary
An important uncertainty in the modelling of methane emissions from natural wetlands is the wetland area. It is important to get the spatiotemporal covariance between the variables that drive methane emissions right for accurate quantification. Using high-resolution wetland and soil carbon maps, in combination with a simplified methane emission model that is coarsened in six steps from 0.005° to 1°, we find a strong relation between wetland emissions and the model resolution.
Shelley van der Graaf, Enrico Dammers, Arjo Segers, Richard Kranenburg, Martijn Schaap, Mark W. Shephard, and Jan Willem Erisman
Atmos. Chem. Phys., 22, 951–972, https://doi.org/10.5194/acp-22-951-2022, https://doi.org/10.5194/acp-22-951-2022, 2022
Short summary
Short summary
CrIS NH3 satellite observations are assimilated into the LOTOS-EUROS model using two different methods. In the first method the data are used to fit spatially varying NH3 emission time factors. In the second method a local ensemble transform Kalman filter is used. Compared to in situ observations, combining both methods led to the most significant improvements in the modeled concentrations and deposition, illustrating the usefulness of CrIS NH3 to improve the spatiotemporal distribution of NH3.
Vilma Kangasaho, Aki Tsuruta, Leif Backman, Pyry Mäkinen, Sander Houweling, Arjo Segers, Maarten Krol, Ed Dlugokencky, Sylvia Michel, James White, and Tuula Aalto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-843, https://doi.org/10.5194/acp-2021-843, 2021
Revised manuscript not accepted
Short summary
Short summary
Understanding the composition of carbon isotopes can help to better understand the changes in methane budgets. This study investigates how methane sources affect the seasonal cycle of the methane carbon-13 isotope during 2000–2012 using an atmospheric transport model. We found that emissions from both anthropogenic and natural sources contribute. The findings raise a need to revise the magnitudes, proportion, and seasonal cycles of anthropogenic sources and northern wetland emissions.
Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao
Geosci. Model Dev., 14, 5607–5622, https://doi.org/10.5194/gmd-14-5607-2021, https://doi.org/10.5194/gmd-14-5607-2021, 2021
Short summary
Short summary
When discussing the accuracy of a dust forecast, the shape and position of the plume as well as the intensity are key elements. The position forecast determines which locations will be affected, while the intensity only describes the actual dust level. A dust forecast with position misfit directly results in incorrect timing profiles of dust loads. In this paper, an image-morphing-based data assimilation is designed for realigning a simulated dust plume to correct for the position error.
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
Short summary
Short summary
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.
Cited articles
Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I., Krummel, P., Steele, P., Langenfelds, R., Torn, M., Biraud, S., Stephens, B., Andrews, A., and Worthy, D.: Global CO2 fluxes estimated from GOSAT retrievals of total column CO2, Atmos. Chem. Phys., 13, 8695–8717, https://doi.org/10.5194/acp-13-8695-2013, 2013.
Bergamaschi, P., Krol, M., Meirink, J. F., Dentener, F., Segers, A., van
Aardenne, J., Monni, S., Vermeulen, A. T., Schmidt, M., Ramonet, M., Yver,
C., Meinhardt, F., Nisbet, E. G., Fisher, R. E., O'Doherty, S., and
Dlugokencky, E. J.: Inverse modeling of European CH4 emissions 2001–2006,
J. Geophys. Res., 115, D22309, https://doi.org/10.1029/2010JD014180, 2010.
Chevallier, F.: On the parallelization of atmospheric inversions of CO2 surface fluxes within a variational framework, Geosci. Model Dev., 6, 783–790, https://doi.org/10.5194/gmd-6-783-2013, 2013.
Chevallier, F., Fisher, M., Peylin, P., Serrar, S., Bousquet, P.,
Bréon, F. M., Chédin, A., and Ciais, P.: Inferring CO2 sources and
sinks from satellite observations: Method and application to TOVS data,
J. Geophys. Res.-Atmos., 110, 1–13, https://doi.org/10.1029/2005JD006390, 2005.
Chevallier, F., Breon, F.-M., and Rayner, P. J.: Contribution of the
Orbiting Carbon Observatory to the estimation of CO2 sources and sinks:
Theoretical study in a variational data assimilation framework, J. Geophys.
Res.-Atmos., 112, D09307, https://doi.org/10.1029/2006JD007375, 2007.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy,
S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P.,
Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M.,
Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C.,
Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis:
Configuration and performance of the data assimilation system, Q. J. Roy.
Meteor. Soc., 137, 553–597, 2011.
Dlugokencky, E. J., Nisbet, E. G., Fisher, R. and Lowry, D.: Global
atmospheric methane: Budget, changes and dangers,
Philos. T. Roy. Soc. A, 369, 2058–2072, https://doi.org/10.1098/rsta.2010.0341,
2011.
Dlugokencky, E. J., Crotwell, A. M., Mund, J. W., Crotwell, M. J., and
Thoning, K. W.: Atmospheric Methane Dry Air Mole Fractions from the NOAA GML
Carbon Cycle Cooperative Global Air Sampling Network, Version: 2020-07, NOAA Global Monitoring Laboratory Data Repository [data set],
https://doi.org/10.15138/VNCZ-M766, 2020.
Fisher, M. and Courtier, P.: Estimating the covariance matrices of analysis
and forecast error in variational data assimilation, in: ECMWF Technical
Memorandum 220, ECMWF, Reading, UK, https://doi.org/10.21957/1dxrasjit, 1995.
Gurney, K., Law, R., Denning, A., Rayner, P., Baker, D., Bousquet, P.,
Bruhwiler, L., Chen, H., Ciais, P., Fan, S., Fung, I., Gloor, M., Heimann,
M., Higuchi, K., John, J., Maki, T., Maksyutov, S., Ken, M., Peylin, P.,
Prather, M., Pak, B. C., Randerson, J., Sarmiento, J., Taguchi, S.,
Takahashi, T., and Yuen, C.-W.: Towards robust regional estimates of CO2
sources and sinks using atmospheric transport models, Nature, 415, 626–630,
https://doi.org/10.1038/415626a, 2002.
Houweling, S., Krol, M., Bergamaschi, P., Frankenberg, C., Dlugokencky, E. J., Morino, I., Notholt, J., Sherlock, V., Wunch, D., Beck, V., Gerbig, C., Chen, H., Kort, E. A., Röckmann, T., and Aben, I.: A multi-year methane inversion using SCIAMACHY, accounting for systematic errors using TCCON measurements, Atmos. Chem. Phys., 14, 3991–4012, https://doi.org/10.5194/acp-14-3991-2014, 2014.
Krol, M., Houweling, S., Bregman, B., van den Broek, M., Segers, A., van Velthoven, P., Peters, W., Dentener, F., and Bergamaschi, P.: The two-way nested global chemistry-transport zoom model TM5: algorithm and applications, Atmos. Chem. Phys., 5, 417–432, https://doi.org/10.5194/acp-5-417-2005, 2005.
Krol, M., Sager, P., and Segers, A.: 4DVAR data assimilation system using TM5, https://sourceforge.net/projects/tm5/ (last access: 1 June 2022), 2013.
Maasakkers, J. D., Jacob, D. J., Sulprizio, M. P., Scarpelli, T. R., Nesser, H., Sheng, J.-X., Zhang, Y., Hersher, M., Bloom, A. A., Bowman, K. W., Worden, J. R., Janssens-Maenhout, G., and Parker, R. J.: Global distribution of methane emissions, emission trends, and OH concentrations and trends inferred from an inversion of GOSAT satellite data for 2010–2015, Atmos. Chem. Phys., 19, 7859–7881, https://doi.org/10.5194/acp-19-7859-2019, 2019.
Meirink, J. F., Bergamaschi, P., and Krol, M. C.: Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion, Atmos. Chem. Phys., 8, 6341–6353, https://doi.org/10.5194/acp-8-6341-2008, 2008.
Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J.,
Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T.,
Robock, A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and
Natural Radiative Forcing, in: Climate Change 2013: The Physical Science
Basis, Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, Cambridge University Press,
Cambridge, UK and New York, NY, USA, https://www.ipcc.ch/report/ar5/wg1/ last access: 1 June 2022), 2013.
Naus, S., Montzka, S. A., Pandey, S., Basu, S., Dlugokencky, E. J., and Krol, M.: Constraints and biases in a tropospheric two-box model of OH, Atmos. Chem. Phys., 19, 407–424, https://doi.org/10.5194/acp-19-407-2019, 2019.
Naus, S., Montzka, S. A., Patra, P. K., and Krol, M. C.: A three-dimensional-model inversion of methyl chloroform to constrain the atmospheric oxidative capacity, Atmos. Chem. Phys., 21, 4809–4824, https://doi.org/10.5194/acp-21-4809-2021, 2021.
Pandey, S., Houweling, S., Krol, M., Aben, I., Chevallier, F., Dlugokencky, E. J., Gatti, L. V., Gloor, E., Miller, J. B., Detmers, R., Machida, T., and Röckmann, T.: Inverse modeling of GOSAT-retrieved ratios of total column CH4 and CO2 for 2009 and 2010, Atmos. Chem. Phys., 16, 5043–5062, https://doi.org/10.5194/acp-16-5043-2016, 2016.
Pandey, S., Houweling, S., Krol, M., and Aben, I.: Influence of Atmospheric
Transport on Estimates of Variability in the Global Methane Burden
Geophysical Research Letters, Geophys. Res. Lett., 46, 2302–2311, https://doi.org/10.1029/2018GL081092,
2019.
Pandey, S., Houweling, S., and Segers, A.: TM5-4DVAR-PP Version
1.0-beta.1, Zenodo [code], https://doi.org/10.5281/zenodo.6326373,
2022.
Peters, W., Miller, J. B., Whitaker, J., Denning, A. S., Hirsch, A., Krol,
M. C., Zupanski, D., Bruhwiler, L., and Tans, P. P.: An ensemble data
assimilation system to estimate CO2 surface fluxes from atmospheric trace
gas observations, J. Geophys. Res., 110, D24304, https://doi.org/10.1029/2005JD006157,
2005.
Segers, A. and Houweling, S.: Validation of the CH4 surface flux inversion
– reanalysis 1990–2017, 1–40, https://atmosphere.copernicus.eu/sites/default/files/2021-02/CAMS73_2018SC2_D73.2.4.1-2020_202012_validation_CH4_1990-2019_v2.pdf (last access: 27 March 2021), 2020.
Williams, J. E., Boersma, K. F., Le Sager, P., and Verstraeten, W. W.: The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation, Geosci. Model Dev., 10, 721–750, https://doi.org/10.5194/gmd-10-721-2017, 2017.
Zhang, Y., Jacob, D. J., Maasakkers, J. D., Sulprizio, M. P., Sheng, J.-X., Gautam, R., and Worden, J.: Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane, Atmos. Chem. Phys., 18, 15959–15973, https://doi.org/10.5194/acp-18-15959-2018, 2018.
Zhang, Y., Jacob, D. J., Lu, X., Maasakkers, J. D., Scarpelli, T. R., Sheng, J.-X., Shen, L., Qu, Z., Sulprizio, M. P., Chang, J., Bloom, A. A., Ma, S., Worden, J., Parker, R. J., and Boesch, H.: Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations, Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, 2021.
Short summary
Inversions are used to calculate methane emissions using atmospheric mole-fraction measurements. Multidecadal inversions are needed to extract information from the long measurement records of methane. However, multidecadal inversion computations can take months to finish. Here, we demonstrate an order of magnitude improvement in wall clock time for an iterative multidecadal inversion by physical parallelization of chemical transport model.
Inversions are used to calculate methane emissions using atmospheric mole-fraction measurements....
