Articles | Volume 9, issue 12
https://doi.org/10.5194/gmd-9-4461-2016
© Author(s) 2016. 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-9-4461-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
15 Dec 2016
Development and technical paper |
| 15 Dec 2016
Daily black carbon emissions from fires in northern Eurasia for 2002–2015
Wei Min Hao
CORRESPONDING AUTHOR
Missoula Fire Sciences Laboratory, Rocky Mountain Research Station,
United States Forest Service, Missoula, Montana, USA
Alexander Petkov
Missoula Fire Sciences Laboratory, Rocky Mountain Research Station,
United States Forest Service, Missoula, Montana, USA
Bryce L. Nordgren
Missoula Fire Sciences Laboratory, Rocky Mountain Research Station,
United States Forest Service, Missoula, Montana, USA
Rachel E. Corley
Missoula Fire Sciences Laboratory, Rocky Mountain Research Station,
United States Forest Service, Missoula, Montana, USA
Robin P. Silverstein
Missoula Fire Sciences Laboratory, Rocky Mountain Research Station,
United States Forest Service, Missoula, Montana, USA
Shawn P. Urbanski
Missoula Fire Sciences Laboratory, Rocky Mountain Research Station,
United States Forest Service, Missoula, Montana, USA
Nikolaos Evangeliou
Laboratoire des Sciences du Climat et de l'Environnement (LSCE),
CEA-UVSQ-CNRS UMR 8212, Institut Pierre et Simon Laplace, L'Orme des
Merisiers, 91191 Gif-sur-Yvette, CEDEX, France
Norwegian Institute for Air Research (NILU), Department of Atmospheric
and Climate Research (ATMOS), Kjeller, Norway
Yves Balkanski
Laboratoire des Sciences du Climat et de l'Environnement (LSCE),
CEA-UVSQ-CNRS UMR 8212, Institut Pierre et Simon Laplace, L'Orme des
Merisiers, 91191 Gif-sur-Yvette, CEDEX, France
Bradley L. Kinder
International Program, United States Forest Service, Washington DC,
USA
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Y. H. Mao, Q. B. Li, D. Chen, L. Zhang, W.-M. Hao, and K.-N. Liou
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Lubna Dada, Benjamin T. Brem, Lidia-Marta Amarandi-Netedu, Martine Collaud Coen, Nikolaos Evangeliou, Christoph Hueglin, Nora Nowak, Robin Modini, Martin Steinbacher, and Martin Gysel-Beer
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Cameron McErlich, Felix Goddard, Alex Aves, Catherine Hardacre, Nikolaos Evangeliou, and Laura E. Revell
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Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
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Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
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Olga B. Popovicheva, Nikolaos Evangeliou, Vasilii O. Kobelev, Marina A. Chichaeva, Konstantinos Eleftheriadis, Asta Gregorič, and Nikolay S. Kasimov
Atmos. Chem. Phys., 22, 5983–6000, https://doi.org/10.5194/acp-22-5983-2022, https://doi.org/10.5194/acp-22-5983-2022, 2022
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Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Christine D. Groot Zwaaftink, Wenche Aas, Sabine Eckhardt, Nikolaos Evangeliou, Paul Hamer, Mona Johnsrud, Arve Kylling, Stephen M. Platt, Kerstin Stebel, Hilde Uggerud, and Karl Espen Yttri
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We investigate causes of a poor-air-quality episode in northern Europe in October 2020 during which EU health limits for air quality were vastly exceeded. Such episodes may trigger measures to improve air quality. Analysis based on satellite observations, transport simulations, and surface observations revealed two sources of pollution. Emissions of mineral dust in Central Asia and biomass burning in Ukraine arrived almost simultaneously in Norway, and transport continued into the Arctic.
Stephen M. Platt, Øystein Hov, Torunn Berg, Knut Breivik, Sabine Eckhardt, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Markus Fiebig, Rebecca Fisher, Georg Hansen, Hans-Christen Hansson, Jost Heintzenberg, Ove Hermansen, Dominic Heslin-Rees, Kim Holmén, Stephen Hudson, Roland Kallenborn, Radovan Krejci, Terje Krognes, Steinar Larssen, David Lowry, Cathrine Lund Myhre, Chris Lunder, Euan Nisbet, Pernilla B. Nizzetto, Ki-Tae Park, Christina A. Pedersen, Katrine Aspmo Pfaffhuber, Thomas Röckmann, Norbert Schmidbauer, Sverre Solberg, Andreas Stohl, Johan Ström, Tove Svendby, Peter Tunved, Kjersti Tørnkvist, Carina van der Veen, Stergios Vratolis, Young Jun Yoon, Karl Espen Yttri, Paul Zieger, Wenche Aas, and Kjetil Tørseth
Atmos. Chem. Phys., 22, 3321–3369, https://doi.org/10.5194/acp-22-3321-2022, https://doi.org/10.5194/acp-22-3321-2022, 2022
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Here we detail the history of the Zeppelin Observatory, a unique global background site and one of only a few in the high Arctic. We present long-term time series of up to 30 years of atmospheric components and atmospheric transport phenomena. Many of these time series are important to our understanding of Arctic and global atmospheric composition change. Finally, we discuss the future of the Zeppelin Observatory and emerging areas of future research on the Arctic atmosphere.
Adrian Chappell, Nicholas Webb, Mark Hennen, Charles Zender, Philippe Ciais, Kerstin Schepanski, Brandon Edwards, Nancy Ziegler, Sandra Jones, Yves Balkanski, Daniel Tong, John Leys, Stephan Heidenreich, Robert Hynes, David Fuchs, Zhenzhong Zeng, Marie Ekström, Matthew Baddock, Jeffrey Lee, and Tarek Kandakji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-337, https://doi.org/10.5194/gmd-2021-337, 2021
Revised manuscript not accepted
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Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Our results indicate that tuning dust emission models to dust in the atmosphere has hidden dust emission modelling weaknesses and its poor performance. Our new approach will reduce uncertainty and driven by prognostic albedo improve Earth System Models of aerosol effects on future environmental change.
Jessica L. McCarty, Juha Aalto, Ville-Veikko Paunu, Steve R. Arnold, Sabine Eckhardt, Zbigniew Klimont, Justin J. Fain, Nikolaos Evangeliou, Ari Venäläinen, Nadezhda M. Tchebakova, Elena I. Parfenova, Kaarle Kupiainen, Amber J. Soja, Lin Huang, and Simon Wilson
Biogeosciences, 18, 5053–5083, https://doi.org/10.5194/bg-18-5053-2021, https://doi.org/10.5194/bg-18-5053-2021, 2021
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Fires, including extreme fire seasons, and fire emissions are more common in the Arctic. A review and synthesis of current scientific literature find climate change and human activity in the north are fuelling an emerging Arctic fire regime, causing more black carbon and methane emissions within the Arctic. Uncertainties persist in characterizing future fire landscapes, and thus emissions, as well as policy-relevant challenges in understanding, monitoring, and managing Arctic fire regimes.
Yves Balkanski, Rémy Bonnet, Olivier Boucher, Ramiro Checa-Garcia, and Jérôme Servonnat
Atmos. Chem. Phys., 21, 11423–11435, https://doi.org/10.5194/acp-21-11423-2021, https://doi.org/10.5194/acp-21-11423-2021, 2021
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Earth system models have persistent biases that impinge on our ability to make robust future regional predictions of precipitation. For the last 15 years, there has been little improvement in these biases. This work presents an accurate representation of dust absorption based upon observed dust mineralogical composition and size distribution. The striking result is that this more accurate representation improves tropical precipitations for climate models with too weak an African monsoon.
Ramiro Checa-Garcia, Yves Balkanski, Samuel Albani, Tommi Bergman, Ken Carslaw, Anne Cozic, Chris Dearden, Beatrice Marticorena, Martine Michou, Twan van Noije, Pierre Nabat, Fiona M. O'Connor, Dirk Olivié, Joseph M. Prospero, Philippe Le Sager, Michael Schulz, and Catherine Scott
Atmos. Chem. Phys., 21, 10295–10335, https://doi.org/10.5194/acp-21-10295-2021, https://doi.org/10.5194/acp-21-10295-2021, 2021
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Thousands of tons of dust are emitted into the atmosphere every year, producing important impacts on the Earth system. However, current global climate models are not yet able to reproduce dust emissions, transport and depositions with the desirable accuracy. Our study analyses five different Earth system models to report aspects to be improved to reproduce better available observations, increase the consistency between models and therefore decrease the current uncertainties.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Danny M. Leung, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, Jessica S. Wan, and Chloe A. Whicker
Atmos. Chem. Phys., 21, 8127–8167, https://doi.org/10.5194/acp-21-8127-2021, https://doi.org/10.5194/acp-21-8127-2021, 2021
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Desert dust interacts with virtually every component of the Earth system, including the climate system. We develop a new methodology to represent the global dust cycle that integrates observational constraints on the properties and abundance of desert dust with global atmospheric model simulations. We show that the resulting representation of the global dust cycle is more accurate than what can be obtained from a large number of current climate global atmospheric models.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, and Jessica S. Wan
Atmos. Chem. Phys., 21, 8169–8193, https://doi.org/10.5194/acp-21-8169-2021, https://doi.org/10.5194/acp-21-8169-2021, 2021
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The many impacts of dust on the Earth system depend on dust mineralogy, which varies between dust source regions. We constrain the contribution of the world’s main dust source regions by integrating dust observations with global model simulations. We find that Asian dust contributes more and that North African dust contributes less than models account for. We obtain a dataset of each source region’s contribution to the dust cycle that can be used to constrain dust impacts on the Earth system.
Pascale Braconnot, Samuel Albani, Yves Balkanski, Anne Cozic, Masa Kageyama, Adriana Sima, Olivier Marti, and Jean-Yves Peterschmitt
Clim. Past, 17, 1091–1117, https://doi.org/10.5194/cp-17-1091-2021, https://doi.org/10.5194/cp-17-1091-2021, 2021
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We investigate how mid-Holocene dust reduction affects the Earth’s energetics from a suite of climate simulations. Our analyses confirm the peculiar role of the dust radiative effect over bright surfaces such as African deserts. We highlight a strong dependence on the dust pattern. The relative dust forcing between West Africa and the Middle East impacts the relative response of Indian and African monsoons and between the western tropical Atlantic and the Atlantic meridional circulation.
Karl Espen Yttri, Francesco Canonaco, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Hans Gundersen, Anne-Gunn Hjellbrekke, Cathrine Lund Myhre, Stephen Matthew Platt, André S. H. Prévôt, David Simpson, Sverre Solberg, Jason Surratt, Kjetil Tørseth, Hilde Uggerud, Marit Vadset, Xin Wan, and Wenche Aas
Atmos. Chem. Phys., 21, 7149–7170, https://doi.org/10.5194/acp-21-7149-2021, https://doi.org/10.5194/acp-21-7149-2021, 2021
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Carbonaceous aerosol sources and trends were studied at the Birkenes Observatory. A large decrease in elemental carbon (EC; 2001–2018) and a smaller decline in levoglucosan (2008–2018) suggest that organic carbon (OC)/EC from traffic/industry is decreasing, whereas the abatement of OC/EC from biomass burning has been less successful. Positive matrix factorization apportioned 72 % of EC to fossil fuel sources and 53 % (PM2.5) and 78 % (PM10–2.5) of OC to biogenic sources.
Wei Min Hao, Matthew C. Reeves, L. Scott Baggett, Yves Balkanski, Philippe Ciais, Bryce L. Nordgren, Alexander Petkov, Rachel E. Corley, Florent Mouillot, Shawn P. Urbanski, and Chao Yue
Biogeosciences, 18, 2559–2572, https://doi.org/10.5194/bg-18-2559-2021, https://doi.org/10.5194/bg-18-2559-2021, 2021
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We examined the trends in the spatial and temporal distribution of the area burned in northern Eurasia from 2002 to 2016. The annual area burned in this region declined by 53 % during the 15-year period under analysis. Grassland fires in Kazakhstan dominated the fire activity, comprising 47 % of the area burned but accounting for 84 % of the decline. A wetter climate and the increase in grazing livestock in Kazakhstan are the major factors contributing to the decline in the area burned.
Nikolaos Evangeliou, Yves Balkanski, Sabine Eckhardt, Anne Cozic, Martin Van Damme, Pierre-François Coheur, Lieven Clarisse, Mark W. Shephard, Karen E. Cady-Pereira, and Didier Hauglustaine
Atmos. Chem. Phys., 21, 4431–4451, https://doi.org/10.5194/acp-21-4431-2021, https://doi.org/10.5194/acp-21-4431-2021, 2021
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Ammonia, a substance that has played a key role in sustaining life, has been increasing in the atmosphere, affecting climate and humans. Understanding the reasons for this increase is important for the beneficial use of ammonia. The evolution of satellite products gives us the opportunity to calculate ammonia emissions easier. We calculated global ammonia emissions over the last 10 years, incorporated them into a chemistry model and recorded notable improvement in reproducing observations.
Longlei Li, Natalie M. Mahowald, Ron L. Miller, Carlos Pérez García-Pando, Martina Klose, Douglas S. Hamilton, Maria Gonçalves Ageitos, Paul Ginoux, Yves Balkanski, Robert O. Green, Olga Kalashnikova, Jasper F. Kok, Vincenzo Obiso, David Paynter, and David R. Thompson
Atmos. Chem. Phys., 21, 3973–4005, https://doi.org/10.5194/acp-21-3973-2021, https://doi.org/10.5194/acp-21-3973-2021, 2021
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For the first time, this study quantifies the range of the dust direct radiative effect due to uncertainty in the soil mineral abundance using all currently available information. We show that the majority of the estimated direct radiative effect range is due to uncertainty in the simulated mass fractions of iron oxides and thus their soil abundance, which is independent of the model employed. We therefore prove the necessity of considering mineralogy for understanding dust–climate interactions.
Nikolaos Evangeliou, Stephen M. Platt, Sabine Eckhardt, Cathrine Lund Myhre, Paolo Laj, Lucas Alados-Arboledas, John Backman, Benjamin T. Brem, Markus Fiebig, Harald Flentje, Angela Marinoni, Marco Pandolfi, Jesus Yus-Dìez, Natalia Prats, Jean P. Putaud, Karine Sellegri, Mar Sorribas, Konstantinos Eleftheriadis, Stergios Vratolis, Alfred Wiedensohler, and Andreas Stohl
Atmos. Chem. Phys., 21, 2675–2692, https://doi.org/10.5194/acp-21-2675-2021, https://doi.org/10.5194/acp-21-2675-2021, 2021
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Following the transmission of SARS-CoV-2 to Europe, social distancing rules were introduced to prevent further spread. We investigate the impacts of the European lockdowns on black carbon (BC) emissions by means of in situ observations and inverse modelling. BC emissions declined by 23 kt in Europe during the lockdowns as compared with previous years and by 11 % as compared to the period prior to lockdowns. Residential combustion prevailed in Eastern Europe, as confirmed by remote sensing data.
Ondřej Tichý, Miroslav Hýža, Nikolaos Evangeliou, and Václav Šmídl
Atmos. Meas. Tech., 14, 803–818, https://doi.org/10.5194/amt-14-803-2021, https://doi.org/10.5194/amt-14-803-2021, 2021
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We present an investigation of the usability of newly developed real-time concentration monitoring systems, which are based on the gamma-ray counting of aerosol filters. These high-resolution data were used for inverse modeling of the 106Ru release in 2017. Our inverse modeling results agree with previously published estimates and provide better temporal resolution of the estimates.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
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Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Ondřej Tichý, Lukáš Ulrych, Václav Šmídl, Nikolaos Evangeliou, and Andreas Stohl
Geosci. Model Dev., 13, 5917–5934, https://doi.org/10.5194/gmd-13-5917-2020, https://doi.org/10.5194/gmd-13-5917-2020, 2020
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We study the estimation of the temporal profile of an atmospheric release using formalization as a linear inverse problem. The problem is typically ill-posed, so all state-of-the-art methods need some form of regularization using additional information. We provide a sensitivity study on the prior source term and regularization parameters for the shape of the source term with a demonstration on the ETEX experimental release and the Cs-134 and Cs-137 dataset from the Chernobyl accident.
Gunnar Myhre, Bjørn H. Samset, Christian W. Mohr, Kari Alterskjær, Yves Balkanski, Nicolas Bellouin, Mian Chin, James Haywood, Øivind Hodnebrog, Stefan Kinne, Guangxing Lin, Marianne T. Lund, Joyce E. Penner, Michael Schulz, Nick Schutgens, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, and Kai Zhang
Atmos. Chem. Phys., 20, 8855–8865, https://doi.org/10.5194/acp-20-8855-2020, https://doi.org/10.5194/acp-20-8855-2020, 2020
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The radiative forcing of the direct aerosol effects can be decomposed into clear-sky and cloudy-sky portions. In this study we use observational methods and two sets of multi-model global aerosol simulations over the industrial era to show that the contribution from cloudy-sky regions is likely weak.
Laurent Menut, Guillaume Siour, Bertrand Bessagnet, Florian Couvidat, Emilie Journet, Yves Balkanski, and Karine Desboeufs
Geosci. Model Dev., 13, 2051–2071, https://doi.org/10.5194/gmd-13-2051-2020, https://doi.org/10.5194/gmd-13-2051-2020, 2020
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Modelling of mineral dust is often done using one single mean species. In this study, differentiated mineral species with their chemical composition are implemented in the CHIMERE regional chemistry-transport model by using global databases. Simulations are carried out to quantify the realism and gain of such mineralogy.
Claudia Di Biagio, Paola Formenti, Yves Balkanski, Lorenzo Caponi, Mathieu Cazaunau, Edouard Pangui, Emilie Journet, Sophie Nowak, Meinrat O. Andreae, Konrad Kandler, Thuraya Saeed, Stuart Piketh, David Seibert, Earle Williams, and Jean-François Doussin
Atmos. Chem. Phys., 19, 15503–15531, https://doi.org/10.5194/acp-19-15503-2019, https://doi.org/10.5194/acp-19-15503-2019, 2019
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This paper presents a new dataset of laboratory measurements of the shortwave (SW) spectral complex refractive index and single-scattering albedo (SSA) for global mineral dust aerosols of varying origin and composition. Our results show that the dust refractive index and SSA vary strongly from source to source, mostly due to particle iron content changes. We recommend that source-dependent values of the SW spectral refractive index and SSA be used in models and remote sensing applications.
Ignacio Pisso, Espen Sollum, Henrik Grythe, Nina I. Kristiansen, Massimo Cassiani, Sabine Eckhardt, Delia Arnold, Don Morton, Rona L. Thompson, Christine D. Groot Zwaaftink, Nikolaos Evangeliou, Harald Sodemann, Leopold Haimberger, Stephan Henne, Dominik Brunner, John F. Burkhart, Anne Fouilloux, Jerome Brioude, Anne Philipp, Petra Seibert, and Andreas Stohl
Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, https://doi.org/10.5194/gmd-12-4955-2019, 2019
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We present the latest release of the Lagrangian transport model FLEXPART, which simulates the transport, diffusion, dry and wet deposition, radioactive decay, and 1st-order chemical reactions of atmospheric tracers. The model has been recently updated both technically and in the representation of physicochemical processes. We describe the changes, document the most recent input and output files, provide working examples, and introduce testing capabilities.
Jens Mühle, Cathy M. Trudinger, Luke M. Western, Matthew Rigby, Martin K. Vollmer, Sunyoung Park, Alistair J. Manning, Daniel Say, Anita Ganesan, L. Paul Steele, Diane J. Ivy, Tim Arnold, Shanlan Li, Andreas Stohl, Christina M. Harth, Peter K. Salameh, Archie McCulloch, Simon O'Doherty, Mi-Kyung Park, Chun Ok Jo, Dickon Young, Kieran M. Stanley, Paul B. Krummel, Blagoj Mitrevski, Ove Hermansen, Chris Lunder, Nikolaos Evangeliou, Bo Yao, Jooil Kim, Benjamin Hmiel, Christo Buizert, Vasilii V. Petrenko, Jgor Arduini, Michela Maione, David M. Etheridge, Eleni Michalopoulou, Mike Czerniak, Jeffrey P. Severinghaus, Stefan Reimann, Peter G. Simmonds, Paul J. Fraser, Ronald G. Prinn, and Ray F. Weiss
Atmos. Chem. Phys., 19, 10335–10359, https://doi.org/10.5194/acp-19-10335-2019, https://doi.org/10.5194/acp-19-10335-2019, 2019
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We discuss atmospheric concentrations and emissions of the strong greenhouse gas perfluorocyclobutane. A large fraction of recent emissions stem from China, India, and Russia, probably as a by-product from the production of fluoropolymers and fluorochemicals. Most historic emissions likely stem from developed countries. Total emissions are higher than what is being reported. Clearly, more measurements and better reporting are needed to understand emissions of this and other greenhouse gases.
Nishit J. Shetty, Apoorva Pandey, Stephen Baker, Wei Min Hao, and Rajan K. Chakrabarty
Atmos. Chem. Phys., 19, 8817–8830, https://doi.org/10.5194/acp-19-8817-2019, https://doi.org/10.5194/acp-19-8817-2019, 2019
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We investigated biases in particle-phase absorption coefficients for organic aerosol from bulk-phase absorbance measurements of solvent extracts in the visible spectrum. These biases were systematically studied as a function of organic-to-total carbon mass ratios and aerosol single scattering albedo. A linear correlation between SSA and OC / TC ratios was observed. Differences in the absorption Ångström exponents from bulk- and particle-phase measurements were also investigated.
Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
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Earth system models for producing climate projections under given forcings include additional processes and feedbacks that traditional physical climate models do not consider. We present an overview of climate feedbacks for key Earth system components and discuss the evaluation of these feedbacks. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research.
Nikolaos Evangeliou, Arve Kylling, Sabine Eckhardt, Viktor Myroniuk, Kerstin Stebel, Ronan Paugam, Sergiy Zibtsev, and Andreas Stohl
Atmos. Chem. Phys., 19, 1393–1411, https://doi.org/10.5194/acp-19-1393-2019, https://doi.org/10.5194/acp-19-1393-2019, 2019
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We simulated the peatland fires that burned in Greenland in summer 2017. Using satellite data, we estimated that the total burned area was 2345 ha, the fuel amount consumed 117 kt C and the emissions of BC, OC and BrC 23.5, 731 and 141 t, respectively. About 30 % of the emissions were deposited on snow or ice surfaces. This caused a maximum albedo change of 0.007 and a surface radiative forcing of 0.03–0.04 W m−2, with local maxima of up to 0.63–0.77 W m−2. Overall, the fires had a small impact.
Shawn P. Urbanski, Matt C. Reeves, Rachel E. Corley, Robin P. Silverstein, and Wei Min Hao
Earth Syst. Sci. Data, 10, 2241–2274, https://doi.org/10.5194/essd-10-2241-2018, https://doi.org/10.5194/essd-10-2241-2018, 2018
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Wildfires are a major source of air pollutants in the US that trigger pollution episodes and challenge air regulators’ efforts to meet air quality standards. Improved wildfire emission estimates are needed to quantify air pollution from fires to guide decision-making activities related to the control of anthropogenic sources. To address the need of air regulators for improved wildfire emission estimates, we developed an inventory of daily US wildfire pollutant emissions for 2003–2015.
Nikolaos Evangeliou, Rona L. Thompson, Sabine Eckhardt, and Andreas Stohl
Atmos. Chem. Phys., 18, 15307–15327, https://doi.org/10.5194/acp-18-15307-2018, https://doi.org/10.5194/acp-18-15307-2018, 2018
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We present BC inversions at high northern latitudes in 2013–2015. The emissions were high close to the gas flaring regions in Russia and in western Canada. The posterior emissions of BC at latitudes > 50° N were estimated as 560 ± 171 kt yr-1, smaller than in bottom-up inventories. Posterior concentrations over the Arctic compared with independent observations from flight and ship campaigns showed small biases. Seasonal maxima were estimated in summer months due to biomass burning, mainly in Europe.
Xin Lin, Philippe Ciais, Philippe Bousquet, Michel Ramonet, Yi Yin, Yves Balkanski, Anne Cozic, Marc Delmotte, Nikolaos Evangeliou, Nuggehalli K. Indira, Robin Locatelli, Shushi Peng, Shilong Piao, Marielle Saunois, Panangady S. Swathi, Rong Wang, Camille Yver-Kwok, Yogesh K. Tiwari, and Lingxi Zhou
Atmos. Chem. Phys., 18, 9475–9497, https://doi.org/10.5194/acp-18-9475-2018, https://doi.org/10.5194/acp-18-9475-2018, 2018
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We simulate CH4 and CO2 using a zoomed global transport model with a horizontal resolution of ~50 km over South and East Asia, as well as a standard model version for comparison. Model performance is evaluated for both gases and versions at multiple timescales against a new collection of surface stations over this key GHG-emitting region. The evaluation at different timescales and comparisons between gases and model versions have implications for possible model improvements and inversions.
Camille Richon, Jean-Claude Dutay, François Dulac, Rong Wang, and Yves Balkanski
Biogeosciences, 15, 2499–2524, https://doi.org/10.5194/bg-15-2499-2018, https://doi.org/10.5194/bg-15-2499-2018, 2018
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This work is part of the Mermex and ChArMEx projects of the MISTRALS program. It aims at studying the impacts of phosphorus deposition from contrasted sources on the biogeochemical cycles of the Mediterranean Sea.
The results show that combustion-related phosphorus deposition effects dominate P deposition over the northern Mediterranean, whereas dust-derived phosphorus deposition effects dominate in the southern part.
Nikolaos Evangeliou, Vladimir P. Shevchenko, Karl Espen Yttri, Sabine Eckhardt, Espen Sollum, Oleg S. Pokrovsky, Vasily O. Kobelev, Vladimir B. Korobov, Andrey A. Lobanov, Dina P. Starodymova, Sergey N. Vorobiev, Rona L. Thompson, and Andreas Stohl
Atmos. Chem. Phys., 18, 963–977, https://doi.org/10.5194/acp-18-963-2018, https://doi.org/10.5194/acp-18-963-2018, 2018
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We present EC measurements from an uncertain region in terms of emissions (Russia). Its origin is quantified with a Lagrangian model that uses a recently developed feature that allows backward estimation of the specific source locations that contribute to the deposited mass. In NW European Russia transportation and domestic combustion from Finland was important. A systematic underestimation was found in W Siberia at places where gas flaring was important, implying miscalculation or sources.
Sabine Eckhardt, Massimo Cassiani, Nikolaos Evangeliou, Espen Sollum, Ignacio Pisso, and Andreas Stohl
Geosci. Model Dev., 10, 4605–4618, https://doi.org/10.5194/gmd-10-4605-2017, https://doi.org/10.5194/gmd-10-4605-2017, 2017
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We extend the backward modelling technique in the existing model FLEXPART to substances deposited at the Earth’s surface by wet scavenging and dry deposition. This means that for existing measurements of a substance in snow, ice cores or rain samples the source regions can be determined. This will help the interpretation of the measurement as well as gaining information of emission strength at the source of the deposited substance.
Maria Sand, Bjørn H. Samset, Yves Balkanski, Susanne Bauer, Nicolas Bellouin, Terje K. Berntsen, Huisheng Bian, Mian Chin, Thomas Diehl, Richard Easter, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Jean-François Lamarque, Guangxing Lin, Xiaohong Liu, Gan Luo, Gunnar Myhre, Twan van Noije, Joyce E. Penner, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Fangqun Yu, Kai Zhang, and Hua Zhang
Atmos. Chem. Phys., 17, 12197–12218, https://doi.org/10.5194/acp-17-12197-2017, https://doi.org/10.5194/acp-17-12197-2017, 2017
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The role of aerosols in the changing polar climate is not well understood and the aerosols are poorly constrained in the models. In this study we have compared output from 16 different aerosol models with available observations at both poles. We show that the model median is representative of the observations, but the model spread is large. The Arctic direct aerosol radiative effect over the industrial area is positive during spring due to black carbon and negative during summer due to sulfate.
Nikolaos Evangeliou, Thomas Hamburger, Anne Cozic, Yves Balkanski, and Andreas Stohl
Atmos. Chem. Phys., 17, 8805–8824, https://doi.org/10.5194/acp-17-8805-2017, https://doi.org/10.5194/acp-17-8805-2017, 2017
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This is the first paper that attempts to assess the source term of the Chernobyl accident using not only activity concentrations but also deposition measurements. This is done by using the FLEXPART model combined with a Bayesian inversion algorithm. Our results show that the altitude of the injection during the first days of the accident might have reached up to 3 km, in contrast to what has been already reported (2.2 km maximum), in order the model to better match observations.
Lorenzo Caponi, Paola Formenti, Dario Massabó, Claudia Di Biagio, Mathieu Cazaunau, Edouard Pangui, Servanne Chevaillier, Gautier Landrot, Meinrat O. Andreae, Konrad Kandler, Stuart Piketh, Thuraya Saeed, Dave Seibert, Earle Williams, Yves Balkanski, Paolo Prati, and Jean-François Doussin
Atmos. Chem. Phys., 17, 7175–7191, https://doi.org/10.5194/acp-17-7175-2017, https://doi.org/10.5194/acp-17-7175-2017, 2017
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This paper presents new laboratory measurements of the shortwave mass absorption efficiency (MAE) used by climate models for mineral dust of different origin and at different sizes. We found that small particles are more efficient, by given mass, in absorbing radiation, particularly at shorter wavelength. Because dust has high concentrations in the atmosphere, light absorption by mineral dust can be competitive to other absorbing atmospheric aerosols such as black and brown carbon.
Claudia Di Biagio, Paola Formenti, Yves Balkanski, Lorenzo Caponi, Mathieu Cazaunau, Edouard Pangui, Emilie Journet, Sophie Nowak, Sandrine Caquineau, Meinrat O. Andreae, Konrad Kandler, Thuraya Saeed, Stuart Piketh, David Seibert, Earle Williams, and Jean-François Doussin
Atmos. Chem. Phys., 17, 1901–1929, https://doi.org/10.5194/acp-17-1901-2017, https://doi.org/10.5194/acp-17-1901-2017, 2017
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Modeling the interaction of dust with long-wave (LW) radiation is still a challenge due to the scarcity of information on their refractive index. In this paper, we present a unique dataset of dust refractive indices obtained from in situ measurements in a large smog chamber. Our results show that the dust LW refractive index varies strongly from source to source due to particle composition changes. We recommend taking this variability into account in climate and remote sensing applications.
N. Evangeliou, Y. Balkanski, W. M. Hao, A. Petkov, R. P. Silverstein, R. Corley, B. L. Nordgren, S. P. Urbanski, S. Eckhardt, A. Stohl, P. Tunved, S. Crepinsek, A. Jefferson, S. Sharma, J. K. Nøjgaard, and H. Skov
Atmos. Chem. Phys., 16, 7587–7604, https://doi.org/10.5194/acp-16-7587-2016, https://doi.org/10.5194/acp-16-7587-2016, 2016
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In this study, we focused on how vegetation fires that occurred in northern Eurasia during the period 2002–2013 influenced the budget of BC in the Arctic. An average area of 250 000 km2 yr−1 was burned in northern Eurasia and the global emissions of BC ranged between 8.0 and 9.5 Tg yr−1, while 102 ± 29 kt yr−1 BC from biomass burning was deposited on the Arctic. About 46 % of the Arctic BC from vegetation fires originated from Siberia, 6 % from Kazakhstan, 5 % from Europe, and about 1 % from Mon
N. I. Kristiansen, A. Stohl, D. J. L. Olivié, B. Croft, O. A. Søvde, H. Klein, T. Christoudias, D. Kunkel, S. J. Leadbetter, Y. H. Lee, K. Zhang, K. Tsigaridis, T. Bergman, N. Evangeliou, H. Wang, P.-L. Ma, R. C. Easter, P. J. Rasch, X. Liu, G. Pitari, G. Di Genova, S. Y. Zhao, Y. Balkanski, S. E. Bauer, G. S. Faluvegi, H. Kokkola, R. V. Martin, J. R. Pierce, M. Schulz, D. Shindell, H. Tost, and H. Zhang
Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, https://doi.org/10.5194/acp-16-3525-2016, 2016
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Processes affecting aerosol removal from the atmosphere are not fully understood. In this study we investigate to what extent atmospheric transport models can reproduce observed loss of aerosols. We compare measurements of radioactive isotopes, that attached to ambient sulfate aerosols during the 2011 Fukushima nuclear accident, to 19 models using identical emissions. Results indicate aerosol removal that is too fast in most models, and apply to aerosols that have undergone long-range transport.
Y. H. Mao, Q. B. Li, D. K. Henze, Z. Jiang, D. B. A. Jones, M. Kopacz, C. He, L. Qi, M. Gao, W.-M. Hao, and K.-N. Liou
Atmos. Chem. Phys., 15, 7685–7702, https://doi.org/10.5194/acp-15-7685-2015, https://doi.org/10.5194/acp-15-7685-2015, 2015
A. A. May, T. Lee, G. R. McMeeking, S. Akagi, A. P. Sullivan, S. Urbanski, R. J. Yokelson, and S. M. Kreidenweis
Atmos. Chem. Phys., 15, 6323–6335, https://doi.org/10.5194/acp-15-6323-2015, https://doi.org/10.5194/acp-15-6323-2015, 2015
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Smoke plumes from some prescribed fires in the southeastern United States were sampled via aircraft to observe changes in organic aerosol (OA) with atmospheric transport. These plumes underwent rapid mixing, and, hence, substantial dilution with background air occurred. Dilution-driven evaporation appears to be the primary driver of OA transformations within the sampled plumes rather than photochemistry.
R. Wang, Y. Balkanski, O. Boucher, L. Bopp, A. Chappell, P. Ciais, D. Hauglustaine, J. Peñuelas, and S. Tao
Atmos. Chem. Phys., 15, 6247–6270, https://doi.org/10.5194/acp-15-6247-2015, https://doi.org/10.5194/acp-15-6247-2015, 2015
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This study makes a first attempt to estimate the temporal trend of Fe emissions from anthropogenic and natural combustion sources from 1960 to 2007 and the emissions of Fe from mineral dust based on a recent mineralogical database. The new emission inventory is introduced into a global aerosol model. The simulated total Fe and soluble Fe concentrations in surface air as well as the deposition of total Fe are evaluated by observations over major continental and oceanic regions globally.
B. H. Samset, G. Myhre, A. Herber, Y. Kondo, S.-M. Li, N. Moteki, M. Koike, N. Oshima, J. P. Schwarz, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, M. Chin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, M. Schulz, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 14, 12465–12477, https://doi.org/10.5194/acp-14-12465-2014, https://doi.org/10.5194/acp-14-12465-2014, 2014
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Far from black carbon (BC) emission sources, present climate models are unable to reproduce flight measurements. By comparing recent models with data, we find that the atmospheric lifetime of BC may be overestimated in models. By adjusting modeled BC concentrations to measurements in remote regions - over oceans and at high altitudes - we arrive at a reduced estimate for BC radiative forcing over the industrial era.
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
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ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
D. A. Hauglustaine, Y. Balkanski, and M. Schulz
Atmos. Chem. Phys., 14, 11031–11063, https://doi.org/10.5194/acp-14-11031-2014, https://doi.org/10.5194/acp-14-11031-2014, 2014
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
A. P. Sullivan, A. A. May, T. Lee, G. R. McMeeking, S. M. Kreidenweis, S. K. Akagi, R. J. Yokelson, S. P. Urbanski, and J. L. Collett Jr.
Atmos. Chem. Phys., 14, 10535–10545, https://doi.org/10.5194/acp-14-10535-2014, https://doi.org/10.5194/acp-14-10535-2014, 2014
Y. H. Mao, Q. B. Li, D. Chen, L. Zhang, W.-M. Hao, and K.-N. Liou
Atmos. Chem. Phys., 14, 7195–7211, https://doi.org/10.5194/acp-14-7195-2014, https://doi.org/10.5194/acp-14-7195-2014, 2014
M. Ménégoz, G. Krinner, Y. Balkanski, O. Boucher, A. Cozic, S. Lim, P. Ginot, P. Laj, H. Gallée, P. Wagnon, A. Marinoni, and H. W. Jacobi
Atmos. Chem. Phys., 14, 4237–4249, https://doi.org/10.5194/acp-14-4237-2014, https://doi.org/10.5194/acp-14-4237-2014, 2014
E. Journet, Y. Balkanski, and S. P. Harrison
Atmos. Chem. Phys., 14, 3801–3816, https://doi.org/10.5194/acp-14-3801-2014, https://doi.org/10.5194/acp-14-3801-2014, 2014
C. Jiao, M. G. Flanner, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, K. S. Carslaw, M. Chin, N. De Luca, T. Diehl, S. J. Ghan, T. Iversen, A. Kirkevåg, D. Koch, X. Liu, G. W. Mann, J. E. Penner, G. Pitari, M. Schulz, Ø. Seland, R. B. Skeie, S. D. Steenrod, P. Stier, T. Takemura, K. Tsigaridis, T. van Noije, Y. Yun, and K. Zhang
Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, https://doi.org/10.5194/acp-14-2399-2014, 2014
M. R. Vuolo, M. Schulz, Y. Balkanski, and T. Takemura
Atmos. Chem. Phys., 14, 877–897, https://doi.org/10.5194/acp-14-877-2014, https://doi.org/10.5194/acp-14-877-2014, 2014
S. P. Urbanski
Atmos. Chem. Phys., 13, 7241–7262, https://doi.org/10.5194/acp-13-7241-2013, https://doi.org/10.5194/acp-13-7241-2013, 2013
N. Evangeliou, Y. Balkanski, A. Cozic, and A. P. Møller
Atmos. Chem. Phys., 13, 7183–7198, https://doi.org/10.5194/acp-13-7183-2013, https://doi.org/10.5194/acp-13-7183-2013, 2013
A. Sima, M. Kageyama, D.-D. Rousseau, G. Ramstein, Y. Balkanski, P. Antoine, and C. Hatté
Clim. Past, 9, 1385–1402, https://doi.org/10.5194/cp-9-1385-2013, https://doi.org/10.5194/cp-9-1385-2013, 2013
M. Ménégoz, G. Krinner, Y. Balkanski, A. Cozic, O. Boucher, and P. Ciais
The Cryosphere, 7, 537–554, https://doi.org/10.5194/tc-7-537-2013, https://doi.org/10.5194/tc-7-537-2013, 2013
D. T. Shindell, J.-F. Lamarque, M. Schulz, M. Flanner, C. Jiao, M. Chin, P. J. Young, Y. H. Lee, L. Rotstayn, N. Mahowald, G. Milly, G. Faluvegi, Y. Balkanski, W. J. Collins, A. J. Conley, S. Dalsoren, R. Easter, S. Ghan, L. Horowitz, X. Liu, G. Myhre, T. Nagashima, V. Naik, S. T. Rumbold, R. Skeie, K. Sudo, S. Szopa, T. Takemura, A. Voulgarakis, J.-H. Yoon, and F. Lo
Atmos. Chem. Phys., 13, 2939–2974, https://doi.org/10.5194/acp-13-2939-2013, https://doi.org/10.5194/acp-13-2939-2013, 2013
B. H. Samset, G. Myhre, M. Schulz, Y. Balkanski, S. Bauer, T. K. Berntsen, H. Bian, N. Bellouin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, S. Kinne, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 13, 2423–2434, https://doi.org/10.5194/acp-13-2423-2013, https://doi.org/10.5194/acp-13-2423-2013, 2013
S. K. Akagi, R. J. Yokelson, I. R. Burling, S. Meinardi, I. Simpson, D. R. Blake, G. R. McMeeking, A. Sullivan, T. Lee, S. Kreidenweis, S. Urbanski, J. Reardon, D. W. T. Griffith, T. J. Johnson, and D. R. Weise
Atmos. Chem. Phys., 13, 1141–1165, https://doi.org/10.5194/acp-13-1141-2013, https://doi.org/10.5194/acp-13-1141-2013, 2013
R. J. Yokelson, I. R. Burling, J. B. Gilman, C. Warneke, C. E. Stockwell, J. de Gouw, S. K. Akagi, S. P. Urbanski, P. Veres, J. M. Roberts, W. C. Kuster, J. Reardon, D. W. T. Griffith, T. J. Johnson, S. Hosseini, J. W. Miller, D. R. Cocker III, H. Jung, and D. R. Weise
Atmos. Chem. Phys., 13, 89–116, https://doi.org/10.5194/acp-13-89-2013, https://doi.org/10.5194/acp-13-89-2013, 2013
Related subject area
Atmospheric sciences
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
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
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
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)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
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
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
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., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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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.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently 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 has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
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.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
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.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
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.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
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.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
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This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
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.
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Short summary
We developed the most comprehensive dataset of daily BC emissions from forest, grassland, shrubland, and savanna fires over northern Eurasia at a 500 m × 500 m resolution from 2002 to 2015. We examined the daily, seasonal, and interannual variability of BC emissions from fires in different ecosystems in the geopolitical regions of Russia, eastern Asia, central and western Asia, and Europe. The results are essential for modeling the transport and deposition of fire-emitted BC to the Arctic.
We developed the most comprehensive dataset of daily BC emissions from forest, grassland,...
