Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-5917-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-5917-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
01 Dec 2020
Development and technical paper |
| 01 Dec 2020
| 01 Dec 2020
On the tuning of atmospheric inverse methods: comparisons with the European Tracer Experiment (ETEX) and Chernobyl datasets using the atmospheric transport model FLEXPART
Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic
Lukáš Ulrych
Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic
Václav Šmídl
Institute of Information Theory and Automation, Czech Academy of Sciences, Prague, Czech Republic
Nikolaos Evangeliou
NILU: Norwegian Institute for Air Research, Kjeller, Norway
Andreas Stohl
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Related authors
Nikolaos Evangeliou, Ondřej Tichý, Marit Svendby Otervik, Sabine Eckhardt, Yves Balkanski, and Didier A. Hauglustaine
Aerosol Research, 3, 155–174, https://doi.org/10.5194/ar-3-155-2025, https://doi.org/10.5194/ar-3-155-2025, 2025
Short summary
Short summary
The COVID-19 lockdown measures in 2020 reduced emissions of various substances, improving air quality. However, PM2.5 stayed unchanged due to NH3 and related chemical transformations. Higher humidity favoured more SO42- production, as did the accumulated NH3. Excess NH3 reacted with HNO3 to make NO3-. In high-NH3 conditions such as those in 2020, a small reduction in NOx levels drove faster oxidation of NO3- and slower deposition of total inorganic NO3-, causing high secondary PM2.5.
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023, https://doi.org/10.5194/acp-23-15235-2023, 2023
Short summary
Short summary
We show declining trends in NH3 emissions over Europe for 2013–2020 using advanced dispersion and inverse modelling and satellite measurements from CrIS. Emissions decreased by −26% since 2013, showing that the abatement strategies adopted by the European Union have been very efficient. Ammonia emissions are low in winter and peak in summer due to temperature-dependent soil volatilization. The largest decreases were observed in central and western Europe in countries with high emissions.
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
Short summary
Short summary
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.
Ondřej Tichý, Václav Šmídl, Radek Hofman, Kateřina Šindelářová, Miroslav Hýža, and Andreas Stohl
Atmos. Chem. Phys., 17, 12677–12696, https://doi.org/10.5194/acp-17-12677-2017, https://doi.org/10.5194/acp-17-12677-2017, 2017
Short summary
Short summary
In the fall of 2011, iodine-131 (131I) was detected at several radionuclide monitoring stations in central Europe. We estimate the source location and emission variation using only the available 131I measurements. Subsequently, we use the IAEA report about the source term for validation of our results. We find that our algorithm could successfully locate the actual release site. The findings are also in agreement with the values reported by the IAEA.
Ondřej Tichý, Václav Šmídl, Radek Hofman, and Andreas Stohl
Geosci. Model Dev., 9, 4297–4311, https://doi.org/10.5194/gmd-9-4297-2016, https://doi.org/10.5194/gmd-9-4297-2016, 2016
Short summary
Short summary
Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. We formulate a probabilistic model, where a full Bayesian estimation allows estimation of all tuning parameters from the measurements. The proposed algorithm is tested and compared with the state-of-the-art method on data from the European Tracer Experiment (ETEX), where advantages of the new method are demonstrated.
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
Aerosol Research, 3, 315–336, https://doi.org/10.5194/ar-3-315-2025, https://doi.org/10.5194/ar-3-315-2025, 2025
Short summary
Short summary
We investigated the sources of ultrafine particles (UFPs) in Payerne, Switzerland, highlighting the significant role of secondary processes in elevating UFP concentrations to levels comparable to urban areas. As the first study in rural midland Switzerland to analyze new particle formation events and secondary contributions, it offers key insights for air quality regulation and the role of agriculture in Switzerland and central Europe.
Cameron McErlich, Felix Goddard, Alex Aves, Catherine Hardacre, Nikolaos Evangeliou, and Laura E. Revell
EGUsphere, https://doi.org/10.5194/egusphere-2025-1575, https://doi.org/10.5194/egusphere-2025-1575, 2025
Short summary
Short summary
Airborne microplastics are a new air pollutant but are not yet included in most global models. We add them to the UK Earth System Model to show how they move, change, and are removed from air. Smaller microplastics persist for longer and can travel further, even to Antarctica. While their current role in air pollution is small, their presence is expected to grow in future. This work offers a framework to assess future impacts of microplastics on air quality and climate.
Nikolaos Evangeliou, Ondřej Tichý, Marit Svendby Otervik, Sabine Eckhardt, Yves Balkanski, and Didier A. Hauglustaine
Aerosol Research, 3, 155–174, https://doi.org/10.5194/ar-3-155-2025, https://doi.org/10.5194/ar-3-155-2025, 2025
Short summary
Short summary
The COVID-19 lockdown measures in 2020 reduced emissions of various substances, improving air quality. However, PM2.5 stayed unchanged due to NH3 and related chemical transformations. Higher humidity favoured more SO42- production, as did the accumulated NH3. Excess NH3 reacted with HNO3 to make NO3-. In high-NH3 conditions such as those in 2020, a small reduction in NOx levels drove faster oxidation of NO3- and slower deposition of total inorganic NO3-, causing high secondary PM2.5.
Lucie Bakels, Michael Blaschek, Marina Dütsch, Andreas Plach, Vincent Lechner, Georg Brack, Leopold Haimberger, and Andreas Stohl
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-26, https://doi.org/10.5194/essd-2025-26, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Meteorological reanalyses are crucial datasets. Most reanalyses are Eulerian, providing data at specific, fixed points in space and time. When studying how air moves, it is more convenient to follow air masses through space and time, requiring a Lagrangian reanalysis (LARA). We explain how the LARA dataset is organized, and provide four examples of applications. These include studying the evolution of wind patterns, understanding weather systems, and measuring air mass travel time over land.
Martin Vojta, Andreas Plach, Rona L. Thompson, Pallav Purohit, Kieran Stanley, Simon O’Doherty, Dickon Young, Joe Pitt, Xin Lan, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2025-1095, https://doi.org/10.5194/egusphere-2025-1095, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We determine European emissions of the highly potent greenhouse gas sulfur hexafluoride from 2005 to 2021 – focusing on high-emitting countries and the aggregated EU-27 emissions. Emissions declined in most regions, likely due to EU F-gas regulations. However, our results reveal that most studied countries underestimate their emissions in their national reports. Our sensitivity tests highlight the importance of dense observational networks for reliable inversion-based emission estimates.
Rona Louise Thompson, Nalini Krishnankutty, Ignacio Pisso, Philipp Schneider, Kerstin Stebel, Motoki Sasakawa, Andreas Stohl, and Stephen Platt
EGUsphere, https://doi.org/10.5194/egusphere-2025-147, https://doi.org/10.5194/egusphere-2025-147, 2025
Short summary
Short summary
Satellite remote sensing of atmospheric mixing ratios of greenhouse gases (GHGs) can provide information on the emissions of these GHGs. This study presents a novel method to use atmospheric column mixing ratios with a Lagrangian model of atmospheric transport to estimate GHG emissions. This method can reduce model errors resulting from how an observation is represented by an atmospheric model potentially reducing the errors in the GHG emissions derived.
Alina Sylvia Waltraud Reininger, Daria Tatsii, Taraprasad Bhowmick, Gholamhossein Bagheri, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2025-605, https://doi.org/10.5194/egusphere-2025-605, 2025
Short summary
Short summary
Microplastics are transported over large distances in the atmosphere, but the shape-dependence of their atmospheric transport lacks investigation. We conducted laboratory experiments and atmospheric transport simulations to study the settling of commercially sold microplastics. We found that films settle up to 74 % slower and travel up to ~ 4x further than volume-equivalent spheres. Our work emphasizes the role of the atmosphere as a transport medium for commercial microplastics such as glitter.
Michel Legrand, Mstislav Vorobyev, Daria Bokuchava, Stanislav Kutuzov, Andreas Plach, Andreas Stohl, Alexandra Khairedinova, Vladimir Mikhalenko, Maria Vinogradova, Sabine Eckhardt, and Susanne Preunkert
Atmos. Chem. Phys., 25, 1385–1399, https://doi.org/10.5194/acp-25-1385-2025, https://doi.org/10.5194/acp-25-1385-2025, 2025
Short summary
Short summary
Past atmospheric NH3 pollution in south-eastern Europe was reconstructed by analysing ammonium in an ice core drilled at the Mount Elbrus (Caucasus, Russia). The observed 3.5-fold increase in ice concentrations between 1750 and 1990 CE is in good agreement with estimated past dominant ammonia emissions from agriculture, mainly from south European Russia and Türkiye. In contrast to present-day conditions, the ammonium level observed in 1750 CE indicates significant natural emissions at that time.
Matthew Boyer, Diego Aliaga, Lauriane L. J. Quéléver, Silvia Bucci, Hélène Angot, Lubna Dada, Benjamin Heutte, Lisa Beck, Marina Duetsch, Andreas Stohl, Ivo Beck, Tiia Laurila, Nina Sarnela, Roseline C. Thakur, Branka Miljevic, Markku Kulmala, Tuukka Petäjä, Mikko Sipilä, Julia Schmale, and Tuija Jokinen
Atmos. Chem. Phys., 24, 12595–12621, https://doi.org/10.5194/acp-24-12595-2024, https://doi.org/10.5194/acp-24-12595-2024, 2024
Short summary
Short summary
We analyze the seasonal cycle and sources of gases that are relevant for the formation of aerosol particles in the central Arctic. Since theses gases can form new particles, they can influence Arctic climate. We show that the sources of these gases are associated with changes in the Arctic environment during the year, especially with respect to sea ice. Therefore, the concentration of these gases will likely change in the future as the Arctic continues to warm.
Martin Vojta, Andreas Plach, Saurabh Annadate, Sunyoung Park, Gawon Lee, Pallav Purohit, Florian Lindl, Xin Lan, Jens Mühle, Rona L. Thompson, and Andreas Stohl
Atmos. Chem. Phys., 24, 12465–12493, https://doi.org/10.5194/acp-24-12465-2024, https://doi.org/10.5194/acp-24-12465-2024, 2024
Short summary
Short summary
We constrain the global emissions of the very potent greenhouse gas sulfur hexafluoride (SF6) between 2005 and 2021. We show that SF6 emissions are decreasing in the USA and in the EU, while they are substantially growing in China, leading overall to an increasing global emission trend. The national reports for the USA, EU, and China all underestimated their SF6 emissions. However, stringent mitigation measures can successfully reduce SF6 emissions, as can be seen in the EU emission trend.
Olga B. Popovicheva, Marina A. Chichaeva, Nikolaos Evangeliou, Sabine Eckhardt, Evangelia Diapouli, and Nikolay S. Kasimov
EGUsphere, https://doi.org/10.5194/egusphere-2024-3124, https://doi.org/10.5194/egusphere-2024-3124, 2024
Short summary
Short summary
High-quality measurements of light-absorbing carbon were performed at the polar aerosol station "Island Bely” (Western Siberian Arctic) from 2019 to 2022. The maximum light absorption coefficients were seen in summer due to gas flaring contribution, which is the most significant source in the region. However, the increasing Siberian wildfires had a special share in carbon contribution to this high Arctic station with a persistent smoke layer extending over the whole troposphere in summer.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Katharina Baier, Lucie Bakels, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2024-2801, https://doi.org/10.5194/egusphere-2024-2801, 2024
Short summary
Short summary
As extremely dry and warm conditions over the Amazon basin can cause huge damages, we study the role of atmospheric transport into the western Amazon for such events. We show that the physical processes depend on the climate variability El Niño Southern Oscillation (ENSO). While warm and dry air from the Atlantic Ocean is transported to the western Amazon for extreme events during the warm ENSO phase, we expect continental regions to have a stronger impact for the other extreme events we found.
Karl Espen Yttri, Are Bäcklund, Franz Conen, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Anne Kasper-Giebl, Avram Gold, Hans Gundersen, Cathrine Lund Myhre, Stephen Matthew Platt, David Simpson, Jason D. Surratt, Sönke Szidat, Martin Rauber, Kjetil Tørseth, Martin Album Ytre-Eide, Zhenfa Zhang, and Wenche Aas
Atmos. Chem. Phys., 24, 2731–2758, https://doi.org/10.5194/acp-24-2731-2024, https://doi.org/10.5194/acp-24-2731-2024, 2024
Short summary
Short summary
We discuss carbonaceous aerosol (CA) observed at the high Arctic Zeppelin Observatory (2017 to 2020). We find that organic aerosol is a significant fraction of the Arctic aerosol, though less than sea salt aerosol and mineral dust, as well as non-sea-salt sulfate, originating mainly from anthropogenic sources in winter and from natural sources in summer, emphasizing the importance of wildfires for biogenic secondary organic aerosol and primary biological aerosol particles observed in the Arctic.
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023, https://doi.org/10.5194/acp-23-15235-2023, 2023
Short summary
Short summary
We show declining trends in NH3 emissions over Europe for 2013–2020 using advanced dispersion and inverse modelling and satellite measurements from CrIS. Emissions decreased by −26% since 2013, showing that the abatement strategies adopted by the European Union have been very efficient. Ammonia emissions are low in winter and peak in summer due to temperature-dependent soil volatilization. The largest decreases were observed in central and western Europe in countries with high emissions.
Rimal Abeed, Camille Viatte, William C. Porter, Nikolaos Evangeliou, Cathy Clerbaux, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, and Sarah Safieddine
Atmos. Chem. Phys., 23, 12505–12523, https://doi.org/10.5194/acp-23-12505-2023, https://doi.org/10.5194/acp-23-12505-2023, 2023
Short summary
Short summary
Ammonia emissions from agricultural activities will inevitably increase with the rise in population. We use a variety of datasets (satellite, reanalysis, and model simulation) to calculate the first regional map of ammonia emission potential during the start of the growing season in Europe. We then apply our developed method using a climate model to show the effect of the temperature increase on future ammonia columns under two possible climate scenarios.
Rüdiger Brecht, Lucie Bakels, Alex Bihlo, and Andreas Stohl
Geosci. Model Dev., 16, 2181–2192, https://doi.org/10.5194/gmd-16-2181-2023, https://doi.org/10.5194/gmd-16-2181-2023, 2023
Short summary
Short summary
We use neural-network-based single-image super-resolution to improve the upscaling of meteorological wind fields to be used for particle dispersion models. This deep-learning-based methodology improves the standard linear interpolation typically used in particle dispersion models. The improvement of wind fields leads to substantial improvement in the computed trajectories of the particles.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
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
Short summary
Short summary
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.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Matthew Boyer, Diego Aliaga, Jakob Boyd Pernov, Hélène Angot, Lauriane L. J. Quéléver, Lubna Dada, Benjamin Heutte, Manuel Dall'Osto, David C. S. Beddows, Zoé Brasseur, Ivo Beck, Silvia Bucci, Marina Duetsch, Andreas Stohl, Tiia Laurila, Eija Asmi, Andreas Massling, Daniel Charles Thomas, Jakob Klenø Nøjgaard, Tak Chan, Sangeeta Sharma, Peter Tunved, Radovan Krejci, Hans Christen Hansson, Federico Bianchi, Katrianne Lehtipalo, Alfred Wiedensohler, Kay Weinhold, Markku Kulmala, Tuukka Petäjä, Mikko Sipilä, Julia Schmale, and Tuija Jokinen
Atmos. Chem. Phys., 23, 389–415, https://doi.org/10.5194/acp-23-389-2023, https://doi.org/10.5194/acp-23-389-2023, 2023
Short summary
Short summary
The Arctic is a unique environment that is warming faster than other locations on Earth. We evaluate measurements of aerosol particles, which can influence climate, over the central Arctic Ocean for a full year and compare the data to land-based measurement stations across the Arctic. Our measurements show that the central Arctic has similarities to but also distinct differences from the stations further south. We note that this may change as the Arctic warms and sea ice continues to decline.
Martin Vojta, Andreas Plach, Rona L. Thompson, and Andreas Stohl
Geosci. Model Dev., 15, 8295–8323, https://doi.org/10.5194/gmd-15-8295-2022, https://doi.org/10.5194/gmd-15-8295-2022, 2022
Short summary
Short summary
In light of recent global warming, we aim to improve methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.
Lauren M. Zamora, Ralph A. Kahn, Nikolaos Evangeliou, Christine D. Groot Zwaaftink, and Klaus B. Huebert
Atmos. Chem. Phys., 22, 12269–12285, https://doi.org/10.5194/acp-22-12269-2022, https://doi.org/10.5194/acp-22-12269-2022, 2022
Short summary
Short summary
Arctic dust, smoke, and pollution particles can affect clouds and Arctic warming. The distributions of these particles were estimated in three different satellite, reanalysis, and model products. These products showed good agreement overall but indicate that it is important to include local dust in models. We hypothesize that mineral dust effects on ice processes in the Arctic atmosphere might be highest over Siberia, where it is cold, moist, and subject to relatively high dust levels.
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
Short summary
Short summary
Measurements of black carbon (BC) combined with atmospheric transport modeling reveal that gas flaring from oil and gas extraction in Kazakhstan, Volga-Ural, Komi, Nenets and western Siberia contributes the largest share of surface BC in the Russian Arctic dominating over domestic, industrial and traffic sectors. Pollution episodes show an increasing trend in concentration levels and frequency as the station is in the Siberian gateway of the highest anthropogenic pollution to the Russian Arctic.
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
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
Short summary
Short summary
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.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
Short summary
Short summary
We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
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
Atmos. Chem. Phys., 22, 3789–3810, https://doi.org/10.5194/acp-22-3789-2022, https://doi.org/10.5194/acp-22-3789-2022, 2022
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Arve Kylling, Hamidreza Ardeshiri, Massimo Cassiani, Anna Solvejg Dinger, Soon-Young Park, Ignacio Pisso, Norbert Schmidbauer, Kerstin Stebel, and Andreas Stohl
Atmos. Meas. Tech., 13, 3303–3318, https://doi.org/10.5194/amt-13-3303-2020, https://doi.org/10.5194/amt-13-3303-2020, 2020
Short summary
Short summary
Atmospheric turbulence and its effect on tracer dispersion in particular may be measured by cameras sensitive to the absorption of ultraviolet (UV) sunlight by sulfur dioxide (SO2). Using large eddy simulation and 3D Monte Carlo radiative transfer modelling of a SO2 plume, we demonstrate that UV camera images of SO2 plumes may be used to derive plume statistics of relevance for the study of atmospheric turbulent dispersion.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Stephen M. Platt, Sabine Eckhardt, Benedicte Ferré, Rebecca E. Fisher, Ove Hermansen, Pär Jansson, David Lowry, Euan G. Nisbet, Ignacio Pisso, Norbert Schmidbauer, Anna Silyakova, Andreas Stohl, Tove M. Svendby, Sunil Vadakkepuliyambatta, Jürgen Mienert, and Cathrine Lund Myhre
Atmos. Chem. Phys., 18, 17207–17224, https://doi.org/10.5194/acp-18-17207-2018, https://doi.org/10.5194/acp-18-17207-2018, 2018
Short summary
Short summary
We measured atmospheric mixing ratios of methane over the Arctic Ocean around Svalbard and compared observed variations to inventories for anthropogenic, wetland, and biomass burning methane emissions and an atmospheric transport model. With knowledge of where variations were expected due to the aforementioned land-based emissions, we were able to identify and quantify a methane source from the ocean north of Svalbard, likely from sub-sea hydrocarbon seeps and/or gas hydrate decomposition.
Anna Solvejg Dinger, Kerstin Stebel, Massimo Cassiani, Hamidreza Ardeshiri, Cirilo Bernardo, Arve Kylling, Soon-Young Park, Ignacio Pisso, Norbert Schmidbauer, Jan Wasseng, and Andreas Stohl
Atmos. Meas. Tech., 11, 6169–6188, https://doi.org/10.5194/amt-11-6169-2018, https://doi.org/10.5194/amt-11-6169-2018, 2018
Short summary
Short summary
This study presents an artificial release experiment aimed to improve the understanding of turbulence in the atmospheric boundary layer. A new set of image processing methods was developed to analyse the turbulent dispersion of sulfur dioxide (SO2) puffs. For this a tomographic setup of six SO2 cameras was used to image artificially released SO2 gas.
Christine D. Groot Zwaaftink, Stephan Henne, Rona L. Thompson, Edward J. Dlugokencky, Toshinobu Machida, Jean-Daniel Paris, Motoki Sasakawa, Arjo Segers, Colm Sweeney, and Andreas Stohl
Geosci. Model Dev., 11, 4469–4487, https://doi.org/10.5194/gmd-11-4469-2018, https://doi.org/10.5194/gmd-11-4469-2018, 2018
Short summary
Short summary
A Lagrangian particle dispersion model is used to simulate global fields of methane, constrained by observations through nudging. We show that this rather simple and computationally inexpensive method can give results similar to or as good as a computationally expensive Eulerian chemistry transport model with a data assimilation scheme. The three-dimensional methane fields are of interest to applications such as inverse modelling and satellite retrievals.
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
Short summary
Short summary
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.
Lauren M. Zamora, Ralph A. Kahn, Klaus B. Huebert, Andreas Stohl, and Sabine Eckhardt
Atmos. Chem. Phys., 18, 14949–14964, https://doi.org/10.5194/acp-18-14949-2018, https://doi.org/10.5194/acp-18-14949-2018, 2018
Short summary
Short summary
We use satellite data and model output to estimate how airborne particles (aerosols) affect cloud ice particles and droplets over the Arctic Ocean. Aerosols from sources like smoke and pollution can change cloud cover, precipitation frequency, and the portion of liquid- vs. ice-containing clouds, which in turn can impact the surface energy budget. By improving our understanding these aerosol–cloud interactions, this work can help climate predictions for the rapidly changing Arctic.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Bastien Sauvage, Alain Fontaine, Sabine Eckhardt, Antoine Auby, Damien Boulanger, Hervé Petetin, Ronan Paugam, Gilles Athier, Jean-Marc Cousin, Sabine Darras, Philippe Nédélec, Andreas Stohl, Solène Turquety, Jean-Pierre Cammas, and Valérie Thouret
Atmos. Chem. Phys., 17, 15271–15292, https://doi.org/10.5194/acp-17-15271-2017, https://doi.org/10.5194/acp-17-15271-2017, 2017
Short summary
Short summary
We provide the scientific community with a SOFT-IO tool based on the coupling of Lagrangian modeling with emission inventories and aircraft CO measurements, which is able to calculate the contribution of the sources and geographical origins of CO measurements, with good performances. Calculated CO added-value products will help scientists in interpreting large IAGOS CO data set. SOFT-IO could further be applied to other CO data sets or used to help validate emission inventories.
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
Short summary
Short summary
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.
Ondřej Tichý, Václav Šmídl, Radek Hofman, Kateřina Šindelářová, Miroslav Hýža, and Andreas Stohl
Atmos. Chem. Phys., 17, 12677–12696, https://doi.org/10.5194/acp-17-12677-2017, https://doi.org/10.5194/acp-17-12677-2017, 2017
Short summary
Short summary
In the fall of 2011, iodine-131 (131I) was detected at several radionuclide monitoring stations in central Europe. We estimate the source location and emission variation using only the available 131I measurements. Subsequently, we use the IAEA report about the source term for validation of our results. We find that our algorithm could successfully locate the actual release site. The findings are also in agreement with the values reported by the IAEA.
Franz Conen, Sabine Eckhardt, Hans Gundersen, Andreas Stohl, and Karl Espen Yttri
Atmos. Chem. Phys., 17, 11065–11073, https://doi.org/10.5194/acp-17-11065-2017, https://doi.org/10.5194/acp-17-11065-2017, 2017
Short summary
Short summary
Observation of ice nuclei active at −8 °C show that rainfall drives their abundance throughout all seasons and that they are equally distributed amongst coarse and fine fraction of PM10. Concurrent measurements of fungal spore markers suggest that some fraction of INP-8 may consist of fungal spores during the warm part of the year. Snow cover suppresses the aerosolisation of ice nuclei. Changes in snow cover and rainfall may affect atmospheric concentrations of ice nuclei in future.
Christine D. Groot Zwaaftink, Ólafur Arnalds, Pavla Dagsson-Waldhauserova, Sabine Eckhardt, Joseph M. Prospero, and Andreas Stohl
Atmos. Chem. Phys., 17, 10865–10878, https://doi.org/10.5194/acp-17-10865-2017, https://doi.org/10.5194/acp-17-10865-2017, 2017
Short summary
Short summary
How much dust do Icelandic sources emit and where is this dust deposited? We modelled dust emission and transport from Icelandic sources over 27 years with FLEXPART. Results show that Icelandic dust sources can have emission rates similar to parts of the Sahara and considerable amounts of dust are deposited in the ocean and on glaciers.
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
Short summary
Short summary
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.
Lauren M. Zamora, Ralph A. Kahn, Sabine Eckhardt, Allison McComiskey, Patricia Sawamura, Richard Moore, and Andreas Stohl
Atmos. Chem. Phys., 17, 7311–7332, https://doi.org/10.5194/acp-17-7311-2017, https://doi.org/10.5194/acp-17-7311-2017, 2017
Short summary
Short summary
Clouds have a major but uncertain effect on Arctic surface temperatures. Here, we used remote sensing observations to better understand aerosol effects on one type of Arctic cloud. By modifying a variety of cloud properties, aerosols in this type of cloud indirectly reduced the net warming effect of these clouds on the surface by ~ 10 % of the clean-background cloud effect, not including changes in cloud fraction. This work will improve our ability to predict future Arctic surface temperatures.
Henrik Grythe, Nina I. Kristiansen, Christine D. Groot Zwaaftink, Sabine Eckhardt, Johan Ström, Peter Tunved, Radovan Krejci, and Andreas Stohl
Geosci. Model Dev., 10, 1447–1466, https://doi.org/10.5194/gmd-10-1447-2017, https://doi.org/10.5194/gmd-10-1447-2017, 2017
Short summary
Short summary
A new and more physically based treatment of how removal by precipitation is calculated by FLEXPART is introduced to take into account more aspects of aerosol diversity. Also new is the definition of clouds and cloud properties. Results from simulations show good agreement with observed atmospheric concentrations for distinctly different aerosols. Atmospheric lifetimes were found to vary from a few hours (large aerosol particles) up to a month (small non-soluble particles)
Monika Wittmann, Christine Dorothea Groot Zwaaftink, Louise Steffensen Schmidt, Sverrir Guðmundsson, Finnur Pálsson, Olafur Arnalds, Helgi Björnsson, Throstur Thorsteinsson, and Andreas Stohl
The Cryosphere, 11, 741–754, https://doi.org/10.5194/tc-11-741-2017, https://doi.org/10.5194/tc-11-741-2017, 2017
Short summary
Short summary
This work includes a study on the effects of dust deposition on the mass balance of Brúarjökull, an outlet glacier of Vatnajökull, Iceland's largest ice cap. A model was used to simulate dust deposition on the glacier, and these periods of dust were compared to albedo measurements at two weather stations on Brúarjökull to evaluate the dust impact. We determine the influence of dust events on the snow albedo and the surface energy balance.
Rona L. Thompson, Motoki Sasakawa, Toshinobu Machida, Tuula Aalto, Doug Worthy, Jost V. Lavric, Cathrine Lund Myhre, and Andreas Stohl
Atmos. Chem. Phys., 17, 3553–3572, https://doi.org/10.5194/acp-17-3553-2017, https://doi.org/10.5194/acp-17-3553-2017, 2017
Short summary
Short summary
Methane (CH4) fluxes were estimated for the high northern latitudes for 2005–2013 based on observations of atmospheric CH4 mixing ratios. Methane fluxes were found to be higher than prior estimates in northern Eurasia and Canada, especially in the Western Siberian Lowlands and the Canadian province Alberta. Significant inter-annual variations in the fluxes were found as well as a small positive trend. In Canada, the trend may be related to an increase in soil temperature over the study period.
Wei Min Hao, Alexander Petkov, Bryce L. Nordgren, Rachel E. Corley, Robin P. Silverstein, Shawn P. Urbanski, Nikolaos Evangeliou, Yves Balkanski, and Bradley L. Kinder
Geosci. Model Dev., 9, 4461–4474, https://doi.org/10.5194/gmd-9-4461-2016, https://doi.org/10.5194/gmd-9-4461-2016, 2016
Short summary
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.
Ondřej Tichý, Václav Šmídl, Radek Hofman, and Andreas Stohl
Geosci. Model Dev., 9, 4297–4311, https://doi.org/10.5194/gmd-9-4297-2016, https://doi.org/10.5194/gmd-9-4297-2016, 2016
Short summary
Short summary
Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. We formulate a probabilistic model, where a full Bayesian estimation allows estimation of all tuning parameters from the measurements. The proposed algorithm is tested and compared with the state-of-the-art method on data from the European Tracer Experiment (ETEX), where advantages of the new method are demonstrated.
Xiao Lu, Lin Zhang, Xu Yue, Jiachen Zhang, Daniel A. Jaffe, Andreas Stohl, Yuanhong Zhao, and Jingyuan Shao
Atmos. Chem. Phys., 16, 14687–14702, https://doi.org/10.5194/acp-16-14687-2016, https://doi.org/10.5194/acp-16-14687-2016, 2016
Short summary
Short summary
Increasing wildfire activities in the mountainous western US may present a challenge for the region to attain a recently revised ozone air quality standard in summer. We quantify the wildfire influence on the ozone variability, trends, and number of high ozone days over this region in summers 1989–2010 using a Lagrangian dispersion model and statistical regression models.
Massimo Cassiani, Andreas Stohl, Dirk Olivié, Øyvind Seland, Ingo Bethke, Ignacio Pisso, and Trond Iversen
Geosci. Model Dev., 9, 4029–4048, https://doi.org/10.5194/gmd-9-4029-2016, https://doi.org/10.5194/gmd-9-4029-2016, 2016
Short summary
Short summary
FLEXPART is a community model used by many scientists. Here, an alternative FLEXPART model version has been developed, tailored to use with the output data generated by the Norwegian Earth System Model (NorESM1-M). The model provides an advanced tool to analyse and diagnose atmospheric transport properties of the climate model NorESM. To validate the model, several tests were performed that offered the possibility to investigate some aspects of offline global dispersion modelling.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Xuekun Fang, Min Shao, Andreas Stohl, Qiang Zhang, Junyu Zheng, Hai Guo, Chen Wang, Ming Wang, Jiamin Ou, Rona L. Thompson, and Ronald G. Prinn
Atmos. Chem. Phys., 16, 3369–3382, https://doi.org/10.5194/acp-16-3369-2016, https://doi.org/10.5194/acp-16-3369-2016, 2016
Short summary
Short summary
This is the first study reporting top-down estimates of benzene and toluene emissions in southern China using atmospheric measurement data from a rural site in the area, an atmospheric transport model and an inverse modeling method. This study shows in detail the temporal and spatial differences between the inversion estimate and four different bottom-up emission inventories (RCP, REAS, MEIC; Yin et al., 2015). We propose that more observations are urgently needed in future.
A. Stohl, B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. Olivié, J. Quaas, B. Quennehen, J.-C. Raut, S. T. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu
Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, https://doi.org/10.5194/acp-15-10529-2015, 2015
Short summary
Short summary
This paper presents a summary of the findings of the ECLIPSE EU project. The project has investigated the climate and air quality impacts of short-lived climate pollutants (especially methane, ozone, aerosols) and has designed a global mitigation strategy that maximizes co-benefits between air quality and climate policy. Transient climate model simulations allowed quantifying the impacts on temperature (e.g., reduction in global warming by 0.22K for the decade 2041-2050) and precipitation.
M. Beekmann, A. S. H. Prévôt, F. Drewnick, J. Sciare, S. N. Pandis, H. A. C. Denier van der Gon, M. Crippa, F. Freutel, L. Poulain, V. Ghersi, E. Rodriguez, S. Beirle, P. Zotter, S.-L. von der Weiden-Reinmüller, M. Bressi, C. Fountoukis, H. Petetin, S. Szidat, J. Schneider, A. Rosso, I. El Haddad, A. Megaritis, Q. J. Zhang, V. Michoud, J. G. Slowik, S. Moukhtar, P. Kolmonen, A. Stohl, S. Eckhardt, A. Borbon, V. Gros, N. Marchand, J. L. Jaffrezo, A. Schwarzenboeck, A. Colomb, A. Wiedensohler, S. Borrmann, M. Lawrence, A. Baklanov, and U. Baltensperger
Atmos. Chem. Phys., 15, 9577–9591, https://doi.org/10.5194/acp-15-9577-2015, https://doi.org/10.5194/acp-15-9577-2015, 2015
Short summary
Short summary
A detailed characterization of air quality in the Paris (France) agglomeration, a megacity, during two summer and winter intensive campaigns and from additional 1-year observations, revealed that about 70% of the fine particulate matter (PM) at urban background is transported into the megacity from upwind regions. Unexpectedly, a major part of organic PM is of modern origin (woodburning and cooking activities, secondary formation from biogenic VOC).
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
Short summary
Short summary
The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
L. J. Kramer, D. Helmig, J. F. Burkhart, A. Stohl, S. Oltmans, and R. E. Honrath
Atmos. Chem. Phys., 15, 6827–6849, https://doi.org/10.5194/acp-15-6827-2015, https://doi.org/10.5194/acp-15-6827-2015, 2015
M. Martinez-Camara, B. Béjar Haro, A. Stohl, and M. Vetterli
Geosci. Model Dev., 7, 2303–2311, https://doi.org/10.5194/gmd-7-2303-2014, https://doi.org/10.5194/gmd-7-2303-2014, 2014
T. Trickl, H. Vogelmann, H. Giehl, H.-E. Scheel, M. Sprenger, and A. Stohl
Atmos. Chem. Phys., 14, 9941–9961, https://doi.org/10.5194/acp-14-9941-2014, https://doi.org/10.5194/acp-14-9941-2014, 2014
M. Maione, F. Graziosi, J. Arduini, F. Furlani, U. Giostra, D. R. Blake, P. Bonasoni, X. Fang, S. A. Montzka, S. J. O'Doherty, S. Reimann, A. Stohl, and M. K. Vollmer
Atmos. Chem. Phys., 14, 9755–9770, https://doi.org/10.5194/acp-14-9755-2014, https://doi.org/10.5194/acp-14-9755-2014, 2014
K. E. Yttri, C. Lund Myhre, S. Eckhardt, M. Fiebig, C. Dye, D. Hirdman, J. Ström, Z. Klimont, and A. Stohl
Atmos. Chem. Phys., 14, 6427–6442, https://doi.org/10.5194/acp-14-6427-2014, https://doi.org/10.5194/acp-14-6427-2014, 2014
H. Grythe, J. Ström, R. Krejci, P. Quinn, and A. Stohl
Atmos. Chem. Phys., 14, 1277–1297, https://doi.org/10.5194/acp-14-1277-2014, https://doi.org/10.5194/acp-14-1277-2014, 2014
J. Brioude, D. Arnold, A. Stohl, M. Cassiani, D. Morton, P. Seibert, W. Angevine, S. Evan, A. Dingwell, J. D. Fast, R. C. Easter, I. Pisso, J. Burkhart, and G. Wotawa
Geosci. Model Dev., 6, 1889–1904, https://doi.org/10.5194/gmd-6-1889-2013, https://doi.org/10.5194/gmd-6-1889-2013, 2013
M. Cassiani, A. Stohl, and S. Eckhardt
Atmos. Chem. Phys., 13, 9975–9996, https://doi.org/10.5194/acp-13-9975-2013, https://doi.org/10.5194/acp-13-9975-2013, 2013
A. Stohl, Z. Klimont, S. Eckhardt, K. Kupiainen, V. P. Shevchenko, V. M. Kopeikin, and A. N. Novigatsky
Atmos. Chem. Phys., 13, 8833–8855, https://doi.org/10.5194/acp-13-8833-2013, https://doi.org/10.5194/acp-13-8833-2013, 2013
S. Eckhardt, O. Hermansen, H. Grythe, M. Fiebig, K. Stebel, M. Cassiani, A. Baecklund, and A. Stohl
Atmos. Chem. Phys., 13, 8401–8409, https://doi.org/10.5194/acp-13-8401-2013, https://doi.org/10.5194/acp-13-8401-2013, 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
M. Laborde, M. Crippa, T. Tritscher, Z. Jurányi, P. F. Decarlo, B. Temime-Roussel, N. Marchand, S. Eckhardt, A. Stohl, U. Baltensperger, A. S. H. Prévôt, E. Weingartner, and M. Gysel
Atmos. Chem. Phys., 13, 5831–5856, https://doi.org/10.5194/acp-13-5831-2013, https://doi.org/10.5194/acp-13-5831-2013, 2013
F. Freutel, J. Schneider, F. Drewnick, S.-L. von der Weiden-Reinmüller, M. Crippa, A. S. H. Prévôt, U. Baltensperger, L. Poulain, A. Wiedensohler, J. Sciare, R. Sarda-Estève, J. F. Burkhart, S. Eckhardt, A. Stohl, V. Gros, A. Colomb, V. Michoud, J. F. Doussin, A. Borbon, M. Haeffelin, Y. Morille, M. Beekmann, and S. Borrmann
Atmos. Chem. Phys., 13, 933–959, https://doi.org/10.5194/acp-13-933-2013, https://doi.org/10.5194/acp-13-933-2013, 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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Abagyan, A., Ilyin, L., Izrael, Y., Legasov, V., and Petrov, V.: The
information on the Chernobyl accident and its consequences, prepared for
IAEA, Sov. At. Energy, 61, 301–320, https://doi.org/10.1007/BF01122262,
1986. a
Berchet, A., Pison, I., Chevallier, F., Bousquet, P., Conil, S., Geever, M., Laurila, T., Lavrič, J., Lopez, M., Moncrieff, J., Necki, J., Ramonet, M., Schmidt, M., Steinbacher, M., and Tarniewicz, J.: Towards better error statistics for atmospheric inversions of methane surface fluxes, Atmos. Chem. Phys., 13, 7115–7132, https://doi.org/10.5194/acp-13-7115-2013, 2013. a
Bocquet, M.: Reconstruction of an atmospheric tracer source using the principle
of maximum entropy. II: Applications, Q. J. Roy.
Meteor. Soc., 131, 2209–2223, 2005. a
Bossew, P., Gering, F., Petermann, E., Hamburger, T., Katzlberger, C.,
Hernandez-Ceballos, M., De Cort, M., Gorzkiewicz, K., Kierepko, R., and
Mietelski, J.: An episode of Ru-106 in air over Europe,
September–October 2017–Geographical distribution of inhalation dose
over Europe, J. Environ. Radioactiv., 205, 79–92, 2019. a
Brandt, J., Christensen, J. H., and Frohn, L. M.: Modelling transport and deposition of caesium and iodine from the Chernobyl accident using the DREAM model, Atmos. Chem. Phys., 2, 397–417, https://doi.org/10.5194/acp-2-397-2002, 2002. a
Carrassi, A., Bocquet, M., Bertino, L., and Evensen, G.: Data assimilation in
the geosciences: An overview of methods, issues, and perspectives, Wires. Climate Change, 9, 9:e535, https://doi.org/10.1002/wcc.535, 2018. a
Casella, G. and George, E. I.: Explaining the Gibbs Sampler, Am.
Stat., 46, 167–174, 1992. a
Chai, T., Stein, A., and Ngan, F.: Weak-constraint inverse modeling using HYSPLIT-4 Lagrangian dispersion model and Cross-Appalachian Tracer Experiment (CAPTEX) observations – effect of including model uncertainties on source term estimation, Geosci. Model Dev., 11, 5135–5148, https://doi.org/10.5194/gmd-11-5135-2018, 2018. a
Chib, S. and Greenberg, E.: Understanding the Metropolis-Hastings
Algorithm, Am. Stat., 49, 327–335, 1995. a
Connor, B., Boesch, H., Toon, G., Sen, B., Miller, C., and Crisp, D.: Orbiting
Carbon Observatory: Inverse method and prospective error analysis,
J. Geophys. Res.-Atmos., 113, D05305, https://doi.org/10.1029/2006JD008336, 2008. a
Davoine, X. and Bocquet, M.: Inverse modelling-based reconstruction of the Chernobyl source term available for long-range transport, Atmos. Chem. Phys., 7, 1549–1564, https://doi.org/10.5194/acp-7-1549-2007, 2007. a, b
De Cort, M., Dubois, G., Fridman, S., Germenchuk, M., Izrael, Y., Janssens, A.,
Jones, A., Kelly, G., Kvasnikova, E., Matveenko, I., Nazarov, I., Pokumeiko,
Y., Sitak, V., Stukin, E., Tabachny, L., Tsaturov, Y., and Avdyushin, S.:
Atlas of caesium deposition on Europe after the Chernobyl accident,
Catalogue number CG-NA-16-733-29-C, EUR 16733, eU – Office for
Official Publications of the European Communities, 1–63, 1998. a, b, c, d
Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S.,
Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P., Bechtold, P., Beljaars,
A., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R.,
Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hersbach, H., Hólm, E.,
Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., Mcnally, A.,
Monge-Sanz, B., Morcrette, J., Park, B., Peubey, C., de Rosnay, P., Tavolato,
C., Thepaut, J., and Vitart, F.: The ERA-Interim reanalysis:
Configuration and performance of the data assimilation system, Q.
J. Roy. Meteor. Soc., 137, 553–597, 2011. a
Eckhardt, S., Prata, A. J., Seibert, P., Stebel, K., and Stohl, A.: Estimation of the vertical profile of sulfur dioxide injection into the atmosphere by a volcanic eruption using satellite column measurements and inverse transport modeling, Atmos. Chem. Phys., 8, 3881–3897, https://doi.org/10.5194/acp-8-3881-2008, 2008. a, b, c, d, e, f, g, h
Efron, B. and Tibshirani, R.: Improvements on cross-validation: the 632+
bootstrap method, J. Am. Stat. Assoc., 92,
548–560, 1997. a
Evangeliou, N., Hamburger, T., Talerko, N., Zibtsev, S., Bondar, Y., Stohl, A.,
Balkanski, Y., Mousseau, T., and Møller, A.: Reconstructing the
Chernobyl Nuclear Power Plant (CNPP) accident 30 years after. A
unique database of air concentration and deposition measurements over
Europe, Environ. Pollut., 216, 408–418, 2016. a, b, c, d
Evensen, G.: Analysis of iterative ensemble smoothers for solving inverse
problems, Comput. Geosci., 22, 885–908, 2018. a
Ganesan, A. L., Rigby, M., Zammit-Mangion, A., Manning, A. J., Prinn, R. G., Fraser, P. J., Harth, C. M., Kim, K.-R., Krummel, P. B., Li, S., Mühle, J., O'Doherty, S. J., Park, S., Salameh, P. K., Steele, L. P., and Weiss, R. F.: Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods, Atmos. Chem. Phys., 14, 3855–3864, https://doi.org/10.5194/acp-14-3855-2014, 2014. a
George, E. I. and McCulloch, R. E.: Variable selecetion via Gibbs sampling,
J. Am. Stat. Assoc., 88, 881–889, 1993. a
Golub, G., Hansen, P., and O'Leary, D.: Tikhonov regularization and total least
squares, SIAM J. Matrix Anal. A., 21, 185–194,
1999. a
Grant, M. and Boyd, S.: Graph implementations for nonsmooth convex programs,
in: Recent Advances in Learning and Control, edited by: Blondel, V., Boyd, S.,
and Kimura, H., Lecture Notes in Control and Information Sciences,
Springer-Verlag Limited, 95–110, 2008. a
Grant, M. and Boyd, S.: CVX: Matlab Software for Disciplined Convex
Programming, version 2.1, available at: http://cvxr.com/cvx (last access: 26 April 2020), 2018. a
Grythe, H., Kristiansen, N. I., Groot Zwaaftink, C. D., Eckhardt, S., Ström, J., Tunved, P., Krejci, R., and Stohl, A.: A new aerosol wet removal scheme for the Lagrangian particle model FLEXPART v10, Geosci. Model Dev., 10, 1447–1466, https://doi.org/10.5194/gmd-10-1447-2017, 2017. a
Gudiksen, P. H., Harvey, T. F., and Lange, R.: Chernobyl Source Term,
Atmospheric Dispersion, and Dose Estimation, Health Physics, 57, 697–706,
1989. a
Hansen, P. C. and O'Leary, D. P.: The use of the L-curve in the regularization
of discrete ill-posed problems, SIAM J. Sci. Comput., 14,
1487–1503, 1993. a
Henne, S., Brunner, D., Oney, B., Leuenberger, M., Eugster, W., Bamberger, I., Meinhardt, F., Steinbacher, M., and Emmenegger, L.: Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling, Atmos. Chem. Phys., 16, 3683–3710, https://doi.org/10.5194/acp-16-3683-2016, 2016. a, b
Izrael, Y. A., Vakulovsky, S. M., Vetrov, V. A., Petrov, V. N., Rovinsky,
F. Y., and Stukin, E. D.: Chernobyl: Radioactive Contamination of the Environment,
Leningrad, Hydrometereological Publishing, 1990 (in Russian). a
Kullback, S. and Leibler, R.: On information and sufficiency, Ann.
Math. Stat., 22, 79–86, 1951. a
Liu, Y., Haussaire, J.-M., Bocquet, M., Roustan, Y., Saunier, O., and Mathieu,
A.: Uncertainty quantification of pollutant source retrieval: comparison of
Bayesian methods with application to the Chernobyl and Fukushima
Daiichi accidental releases of radionuclides, Q. J.
Roy. Meteor. Soc., 143, 2886–2901, 2017. a, b, c, d
Malá, H., Rulík, P., Bečková, V., Mihalík, J., and
Slezáková, M.: Particle size distribution of radioactive aerosols
after the Fukushima and the Chernobyl accidents, J. Environ.
Radioactiv., 126, 92–98, 2013. a
Martinez-Camara, M., Béjar Haro, B., Stohl, A., and Vetterli, M.: A robust method for inverse transport modeling of atmospheric emissions using blind outlier detection, Geosci. Model Dev., 7, 2303–2311, https://doi.org/10.5194/gmd-7-2303-2014, 2014. a
Masson, O., Steinhauser, G., Wershofen, H., Mietelski, J. W., Fischer, H. W.,
Pourcelot, L., Saunier, O., Bieringer, J., Steinkopff, T., Hýža, M.,
Moller, B., Bowyer, T. W., Dalaka, E., Dalheimer, A., de Vismes-Ott, A.,
Eleftheriadis, K., Forte, M., Gasco Leonarte, C., Gorzkiewicz, K., Homoki,
Z., Isajenko, K., Karhunen, T., Katzlberger, C., Kierepko, R.,
Kovendiné Kónyi, J., Malá, H., Nikolic, J., Povinec, P. P., Rajacic, M.,
Ringer, W., Rulík, P., Rusconi, R., Sáfrány, G., Sykora, I., Todorovic,
D., Tschiersch, J., Ungar, K., and Zorko, B.: Potential Source Apportionment
and Meteorological Conditions Involved in Airborne 131I Detections in
January/February 2017 in Europe, Environ. Sci. Technol.,
52, 8488–8500, 2018. a
Mekhaimr, S. and Wahab, M. A.: Sources of uncertainty in atmospheric dispersion
modeling in support of Comprehensive Nuclear–Test–Ban Treaty
monitoring and verification system, Atmos. Pollut. Res., 10, 1383–1395, https://doi.org/10.1016/j.apr.2019.03.008, 2019. a
Michalak, A., Hirsch, A., Bruhwiler, L., Gurney, K., Peters, W., and Tans, P.:
Maximum likelihood estimation of covariance parameters for Bayesian
atmospheric trace gas surface flux inversions, J. Geophys.
Res.-Atmos., 110, D24107, https://doi.org/10.1029/2005JD005970, 2005. a
Miller, S. M., Michalak, A. M., and Levi, P. J.: Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions, Geosci. Model Dev., 7, 303–315, https://doi.org/10.5194/gmd-7-303-2014, 2014. a
Nisbet, E. and Weiss, R.: Top-down versus bottom-up, Science, 328, 1241–1243,
2010. a
Persson, C., Rodhe, H., and De Geer, L.-E.: The Chernobyl accident: A
meteorological analysis of how radionuclides reached and were deposited in
Sweden, Ambio, 16, 20–31, 1987. a
Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., Arnold, D., Morton, D., Thompson, R. L., Groot Zwaaftink, C. D., Evangeliou, N., Sodemann, H., Haimberger, L., Henne, S., Brunner, D., Burkhart, J. F., Fouilloux, A., Brioude, J., Philipp, A., Seibert, P., and Stohl, A.: The Lagrangian particle dispersion model FLEXPART version 10.4, Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, 2019. a, b
Ray, J., Lee, J., Yadav, V., Lefantzi, S., Michalak, A. M., and van Bloemen Waanders, B.: A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion, Geosci. Model Dev., 8, 1259–1273, https://doi.org/10.5194/gmd-8-1259-2015, 2015. a
Saunier, O., Mathieu, A., Didier, D., Tombette, M., Quélo, D., Winiarek, V., and Bocquet, M.: An inverse modeling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations, Atmos. Chem. Phys., 13, 11403–11421, https://doi.org/10.5194/acp-13-11403-2013, 2013. a
Saunier, O., Didier, D., Mathieu, A., Masson, O., and Le Brazidec, J.:
Atmospheric modeling and source reconstruction of radioactive ruthenium from
an undeclared major release in 2017, P. Natl. Acad. Sci. USA, 116, 24991–25000, 2019. a
Seibert, P.: Iverse modelling with a Lagrangian particle disperion model:
application to point releases over limited time intervals, in: Air Pollution
Modeling and its Application XIV, Springer, 381–389, 2001. a
Seibert, P. and Frank, A.: Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode, Atmos. Chem. Phys., 4, 51–63, https://doi.org/10.5194/acp-4-51-2004, 2004. a, b
Šmídl, V. and Quinn, A.: The Variational Bayes Method in Signal
Processing, Springer, https://doi.org/10.1007/3-540-28820-1, 2006. a
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005. a, b, c
Stohl, A., Seibert, P., Arduini, J., Eckhardt, S., Fraser, P., Greally, B. R., Lunder, C., Maione, M., Mühle, J., O'Doherty, S., Prinn, R. G., Reimann, S., Saito, T., Schmidbauer, N., Simmonds, P. G., Vollmer, M. K., Weiss, R. F., and Yokouchi, Y.: An analytical inversion method for determining regional and global emissions of greenhouse gases: Sensitivity studies and application to halocarbons, Atmos. Chem. Phys., 9, 1597–1620, https://doi.org/10.5194/acp-9-1597-2009, 2009. a
Stohl, A., Prata, A. J., Eckhardt, S., Clarisse, L., Durant, A., Henne, S., Kristiansen, N. I., Minikin, A., Schumann, U., Seibert, P., Stebel, K., Thomas, H. E., Thorsteinsson, T., Tørseth, K., and Weinzierl, B.: Determination of time- and height-resolved volcanic ash emissions and their use for quantitative ash dispersion modeling: the 2010 Eyjafjallajökull eruption, Atmos. Chem. Phys., 11, 4333–4351, https://doi.org/10.5194/acp-11-4333-2011, 2011. a, b
Stohl, A., Seibert, P., Wotawa, G., Arnold, D., Burkhart, J. F., Eckhardt, S., Tapia, C., Vargas, A., and Yasunari, T. J.: Xenon-133 and caesium-137 releases into the atmosphere from the Fukushima Dai-ichi nuclear power plant: determination of the source term, atmospheric dispersion, and deposition, Atmos. Chem. Phys., 12, 2313–2343, https://doi.org/10.5194/acp-12-2313-2012, 2012.
a, b, c
Talerko, N.: Mesoscale modelling of radioactive contamination formation in
Ukraine caused by the Chernobyl accident, J. Environ.
Radioactiv., 78, 311–329, 2005. a
Tibshirani, R.: Regression shrinkage and selection via the lasso, J.
Roy. Stat. Soc., 58, 267–288, 1996. a
Tichý, O., Šmídl, V., Hofman, R., and Evangeliou, N.: Source
term estimation of multi-specie atmospheric release of radiation from gamma
dose rates, Q. J. Roy. Meteor. Soc., 144,
2781–2797, https://doi.org/10.1002/qj.3403, 2018. a, b
Ulrych, L. and Šmídl, V.: Sparse and Smooth Prior for Bayesian Linear
Regression with Application to ETEX Data, arXiv preprint, arXiv:1706.06908,
2017. a
Uppala, S. M., Kallberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C.,
Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X.,
Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K.,
Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J., Bormann,
N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M.,
Fuentes, M., Hagemann, S., Holm, E., Hoskins, B. J., Isaksen, L., Janssen, P.
A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette, J.-J.,
Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E.,
Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40
re-analysis, Q. J. Roy. Meteor. Soc., 131,
2961–3012, 2005. a
Winiarek, V., Bocquet, M., Saunier, O., and Mathieu, A.: Estimation of errors
in the inverse modeling of accidental release of atmospheric pollutant:
Application to the reconstruction of the cesium-137 and iodine-131 source
terms from the Fukushima Daiichi power plant, J. Geophys.
Res.-Atmos., 117, D05122, https://doi.org/10.1029/2011JD016932, 2012. a
Winiarek, V., Bocquet, M., Duhanyan, N., Roustan, Y., Saunier, O., and Mathieu,
A.: Estimation of the caesium-137 source term from the Fukushima Daiichi
nuclear power plant using a consistent joint assimilation of air
concentration and deposition observations, Atmos. Environ., 82,
268–279, 2014. a
Wotawa, G., De Geer, L.-E., Denier, P., Kalinowski, M., Toivonen, H.,
D’Amours, R., Desiato, F., Issartel, J.-P., Langer, M., Seibert, P., Frank,
A., Sloan, C., and Yamazawa, H.: Atmospheric transport modelling in support
of CTBT verification – Overview and basic concepts, Atmos. Environ.,
37, 2529–2537, 2003. a
Short summary
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.
We study the estimation of the temporal profile of an atmospheric release using formalization as...
