Articles | Volume 10, issue 3
https://doi.org/10.5194/gmd-10-1339-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-1339-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
29 Mar 2017
Model description paper |
| 29 Mar 2017
CLEPS 1.0: A new protocol for cloud aqueous phase oxidation of VOC mechanisms
Camille Mouchel-Vallon
CORRESPONDING AUTHOR
Université Clermont Auvergne, CNRS Laboratoire de
Météorologie Physique, 63000 Clermont-Ferrand, France
now at:
Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry,
University of York, Heslington, York, YO10 5DD, UK
Laurent Deguillaume
CORRESPONDING AUTHOR
Université Clermont Auvergne, CNRS Laboratoire de
Météorologie Physique, 63000 Clermont-Ferrand, France
Anne Monod
Aix
Marseille Université, CNRS, LCE UMR 7376, 13331 Marseille, France
Hélène Perroux
Université Clermont Auvergne, CNRS Laboratoire de
Météorologie Physique, 63000 Clermont-Ferrand, France
Clémence Rose
Université Clermont Auvergne, CNRS Laboratoire de
Météorologie Physique, 63000 Clermont-Ferrand, France
Giovanni Ghigo
Dipartimento di Chimica, Universita di Torino, V. Giuria 7, 10125
Turin, Italy
Yoann Long
Université Clermont Auvergne, CNRS Laboratoire de
Météorologie Physique, 63000 Clermont-Ferrand, France
now at: Ramboll Environ, 155 rue Louis de Broglie, 13100
Aix-en-Provence, France
Maud Leriche
Université de Toulouse, UPS, CNRS, Laboratoire
d'Aérologie, 31400 Toulouse, France
Bernard Aumont
LISA UMR CNRS 7583,
Université Paris Est Créteil et Université Paris Diderot, Paris,
France
Luc Patryl
CEA, DAM, DIF, 91297 Arpajon, France
Patrick Armand
CEA, DAM, DIF, 91297 Arpajon, France
Nadine Chaumerliac
Université Clermont Auvergne, CNRS Laboratoire de
Météorologie Physique, 63000 Clermont-Ferrand, France
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Atmos. Chem. Phys., 24, 5549–5565, https://doi.org/10.5194/acp-24-5549-2024, https://doi.org/10.5194/acp-24-5549-2024, 2024
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Maud Leriche, Pierre Tulet, Laurent Deguillaume, Frédéric Burnet, Aurélie Colomb, Agnès Borbon, Corinne Jambert, Valentin Duflot, Stéphan Houdier, Jean-Luc Jaffrezo, Mickaël Vaïtilingom, Pamela Dominutti, Manon Rocco, Camille Mouchel-Vallon, Samira El Gdachi, Maxence Brissy, Maroua Fathalli, Nicolas Maury, Bert Verreyken, Crist Amelynck, Niels Schoon, Valérie Gros, Jean-Marc Pichon, Mickael Ribeiro, Eric Pique, Emmanuel Leclerc, Thierry Bourrianne, Axel Roy, Eric Moulin, Joël Barrie, Jean-Marc Metzger, Guillaume Péris, Christian Guadagno, Chatrapatty Bhugwant, Jean-Mathieu Tibere, Arnaud Tournigand, Evelyn Freney, Karine Sellegri, Anne-Marie Delort, Pierre Amato, Muriel Joly, Jean-Luc Baray, Pascal Renard, Angelica Bianco, Anne Réchou, and Guillaume Payen
Atmos. Chem. Phys., 24, 4129–4155, https://doi.org/10.5194/acp-24-4129-2024, https://doi.org/10.5194/acp-24-4129-2024, 2024
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Atmos. Chem. Phys., 24, 3785–3812, https://doi.org/10.5194/acp-24-3785-2024, https://doi.org/10.5194/acp-24-3785-2024, 2024
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-206, https://doi.org/10.5194/amt-2023-206, 2024
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An optimized and controlled protocol for generating quasi-adiabatic expansion clouds under simulated dark and light conditions was presented. The irradiated clouds clearly showed a gradual activation of seed particles into droplets. In contrast, non-irradiated clouds faced a flash activation. This paper will lay the foundation for multiphase photochemical studies implying water-soluble volatile organic compounds and particulate matter formation during cloud formation-evaporation cycles.
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Atmos. Chem. Phys., 23, 15135–15147, https://doi.org/10.5194/acp-23-15135-2023, https://doi.org/10.5194/acp-23-15135-2023, 2023
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Organic nitrates play a crucial role in air pollution, as they are NOx reservoirs. This work investigated for the first time their reactivity with light in the aqueous phase (cloud and fog and wet aerosol), proving it slower than in the gas phase. Therefore, our findings reveal that partitioning of organic nitrates in the aqueous phase leads to longer atmospheric lifetimes of these compounds and thus a broader spatial distribution of their related pollution.
Maija Peltola, Clémence Rose, Jonathan V. Trueblood, Sally Gray, Mike Harvey, and Karine Sellegri
Atmos. Chem. Phys., 23, 3955–3983, https://doi.org/10.5194/acp-23-3955-2023, https://doi.org/10.5194/acp-23-3955-2023, 2023
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We measured the chemical composition of ambient ions at a coastal New Zealand site and connected these data with aerosol size distribution data to study the chemical precursors of new particle formation at the site. Our results showed that iodine oxides and sulfur species were important for particle formation in marine air, while in land-influenced air sulfuric acid and organics were connected to new particle formation events.
Suzanne Crumeyrolle, Jenni S. S. Kontkanen, Clémence Rose, Alejandra Velazquez Garcia, Eric Bourrianne, Maxime Catalfamo, Véronique Riffault, Emmanuel Tison, Joel Ferreira de Brito, Nicolas Visez, Nicolas Ferlay, Frédérique Auriol, and Isabelle Chiapello
Atmos. Chem. Phys., 23, 183–201, https://doi.org/10.5194/acp-23-183-2023, https://doi.org/10.5194/acp-23-183-2023, 2023
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Ultrafine particles (UFPs) are particles with an aerodynamic diameter of 100 nm or less and negligible mass concentration but are the dominant contributor to the total particle number concentration. The present study aims to better understand the environmental factors favoring or inhibiting atmospheric new particle formation (NPF) over Lille, a large city in the north of France, and to analyze the impact of such an event on urban air quality using a long-term dataset (3 years).
Junteng Wu, Nicolas Brun, Juan Miguel González-Sánchez, Badr R'Mili, Brice Temime Roussel, Sylvain Ravier, Jean-Louis Clément, and Anne Monod
Atmos. Meas. Tech., 15, 3859–3874, https://doi.org/10.5194/amt-15-3859-2022, https://doi.org/10.5194/amt-15-3859-2022, 2022
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This work quantified and tentatively identified the organic impurities on ammonium sulfate aerosols generated in the laboratory. They are likely low volatile and high mass molecules containing oxygen, nitrogen, and/or sulfur. Our results show that these organic impurities likely originate from the commercial AS crystals. It is recommended to use AS seeds with caution, especially when small particles are used, in terms of AS purity and water purity when aqueous solutions are used for atomization.
Emily B. Franklin, Lindsay D. Yee, Bernard Aumont, Robert J. Weber, Paul Grigas, and Allen H. Goldstein
Atmos. Meas. Tech., 15, 3779–3803, https://doi.org/10.5194/amt-15-3779-2022, https://doi.org/10.5194/amt-15-3779-2022, 2022
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The composition of atmospheric aerosols are extremely complex, containing hundreds of thousands of estimated individual compounds. The majority of these compounds have never been catalogued in widely used databases, making them extremely difficult for atmospheric chemists to identify and analyze. In this work, we present Ch3MS-RF, a machine-learning-based model to enable characterization of complex mixtures and prediction of structure-specific properties of unidentifiable organic compounds.
Maija Peltola, Clémence Rose, Jonathan V. Trueblood, Sally Gray, Mike Harvey, and Karine Sellegri
Atmos. Chem. Phys., 22, 6231–6254, https://doi.org/10.5194/acp-22-6231-2022, https://doi.org/10.5194/acp-22-6231-2022, 2022
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Despite the importance of marine aerosol measurements for constraining climate models, these measurements are scarce. We measured the aerosol particle number size distribution in coastal New Zealand over a total period of 10 months. This paper analyses the aerosol properties at the site, with a special focus on new particle formation and marine air masses. New particle formation was observed frequently, but in marine air masses it did not follow traditional event criteria.
Mike J. Newland, Camille Mouchel-Vallon, Richard Valorso, Bernard Aumont, Luc Vereecken, Michael E. Jenkin, and Andrew R. Rickard
Atmos. Chem. Phys., 22, 6167–6195, https://doi.org/10.5194/acp-22-6167-2022, https://doi.org/10.5194/acp-22-6167-2022, 2022
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Alkene ozonolysis produces Criegee intermediates, which can act as oxidants or decompose to give a range of closed-shell and radical products, including OH. Therefore it is essential to accurately represent the chemistry of Criegee intermediates in atmospheric models in order to understand their impacts on atmospheric composition. Here we provide a mechanism construction protocol by which the central features of alkene ozonolysis chemistry can be included in an automatic mechanism generator.
Pascal Renard, Maxence Brissy, Florent Rossi, Martin Leremboure, Saly Jaber, Jean-Luc Baray, Angelica Bianco, Anne-Marie Delort, and Laurent Deguillaume
Atmos. Chem. Phys., 22, 2467–2486, https://doi.org/10.5194/acp-22-2467-2022, https://doi.org/10.5194/acp-22-2467-2022, 2022
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Amino acids (AAs) have been quantified in cloud water collected at the Puy de Dôme station (France). Concentrations and speciation of those compounds are highly variable among the samples. Sources from the sea surface and atmospheric transformations during the air mass transport, mainly in the free troposphere, have been shown to modulate AA levels in cloud water.
Pamela A. Dominutti, Pascal Renard, Mickaël Vaïtilingom, Angelica Bianco, Jean-Luc Baray, Agnès Borbon, Thierry Bourianne, Frédéric Burnet, Aurélie Colomb, Anne-Marie Delort, Valentin Duflot, Stephan Houdier, Jean-Luc Jaffrezo, Muriel Joly, Martin Leremboure, Jean-Marc Metzger, Jean-Marc Pichon, Mickaël Ribeiro, Manon Rocco, Pierre Tulet, Anthony Vella, Maud Leriche, and Laurent Deguillaume
Atmos. Chem. Phys., 22, 505–533, https://doi.org/10.5194/acp-22-505-2022, https://doi.org/10.5194/acp-22-505-2022, 2022
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We present here the results obtained during an intensive field campaign conducted in March to April 2019 in Reunion. Our study integrates a comprehensive chemical and microphysical characterization of cloud water. Our investigations reveal that air mass history and cloud microphysical properties do not fully explain the variability observed in their chemical composition. This highlights the complexity of emission sources, multiphasic exchanges, and transformations in clouds.
Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
Atmos. Chem. Phys., 21, 17185–17223, https://doi.org/10.5194/acp-21-17185-2021, https://doi.org/10.5194/acp-21-17185-2021, 2021
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Aerosol particles are a complex component of the atmospheric system the effects of which are among the most uncertain in climate change projections. Using data collected at 62 stations, this study provides the most up-to-date picture of the spatial distribution of particle number concentration and size distribution worldwide, with the aim of contributing to better representation of aerosols and their interactions with clouds in models and, therefore, better evaluation of their impact on climate.
Zhe Peng, Julia Lee-Taylor, Harald Stark, John J. Orlando, Bernard Aumont, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 14649–14669, https://doi.org/10.5194/acp-21-14649-2021, https://doi.org/10.5194/acp-21-14649-2021, 2021
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We use the fully explicit GECKO-A model to study the OH reactivity (OHR) evolution in the NO-free photooxidation of several volatile organic compounds. Oxidation progressively produces more saturated and functionalized species, then breaks them into small species. OHR per C atom evolution is similar for different precursors once saturated multifunctional species are formed. We also find that partitioning of these species to chamber walls leads to large deviations in chambers from the atmosphere.
Isaac Kwadjo Afreh, Bernard Aumont, Marie Camredon, and Kelley Claire Barsanti
Atmos. Chem. Phys., 21, 11467–11487, https://doi.org/10.5194/acp-21-11467-2021, https://doi.org/10.5194/acp-21-11467-2021, 2021
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This is the first mechanistic modeling study of secondary organic aerosol (SOA) from the understudied monoterpene, camphene. The semi-explicit chemical model GECKO-A predicted camphene SOA yields that were ~2 times α-pinene. Using 50/50 α-pinene + limonene as a surrogate for camphene increased predicted SOA mass from biomass burning fuels by up to ~100 %. The accurate representation of camphene in air quality models can improve predictions of SOA when camphene is a dominant monoterpene.
Patrick Chazette, Cyrille Flamant, Harald Sodemann, Julien Totems, Anne Monod, Elsa Dieudonné, Alexandre Baron, Andrew Seidl, Hans Christian Steen-Larsen, Pascal Doira, Amandine Durand, and Sylvain Ravier
Atmos. Chem. Phys., 21, 10911–10937, https://doi.org/10.5194/acp-21-10911-2021, https://doi.org/10.5194/acp-21-10911-2021, 2021
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To gain understanding on the vertical structure of atmospheric water vapour above mountain lakes and to assess its link to the isotopic composition of the lake water and small-scale dynamics, the L-WAIVE field campaign was conducted in the Annecy valley in the French Alps in June 2019. Based on a synergy between ground-based, boat-borne, and airborne measuring platforms, significant gradients of isotopic content have been revealed at the transitions to the lake and to the free troposphere.
Tommaso Galeazzo, Richard Valorso, Ying Li, Marie Camredon, Bernard Aumont, and Manabu Shiraiwa
Atmos. Chem. Phys., 21, 10199–10213, https://doi.org/10.5194/acp-21-10199-2021, https://doi.org/10.5194/acp-21-10199-2021, 2021
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We simulate SOA viscosity with explicit modeling of gas-phase oxidation of isoprene and α-pinene. While the viscosity dependence on relative humidity and mass loadings is captured well by simulations, the model underestimates measured viscosity, indicating missing processes. Kinetic limitations and reduction in mass accommodation may cause an increase in viscosity. The developed model is powerful for investigation of the interplay among gas reactions, chemical composition and phase state.
Gabriel Isaacman-VanWertz and Bernard Aumont
Atmos. Chem. Phys., 21, 6541–6563, https://doi.org/10.5194/acp-21-6541-2021, https://doi.org/10.5194/acp-21-6541-2021, 2021
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There are tens of thousands of different chemical compounds in the atmosphere. To tackle this complexity, there are a wide range of different methods to estimate their physical and chemical properties. We use these methods to understand how much the detailed structure of a molecule impacts its properties, and the extent to which properties can be estimated without knowing this level of detail. We find that structure matters, but methods lacking that level of detail still perform reasonably well.
Juan Miguel González-Sánchez, Nicolas Brun, Junteng Wu, Julien Morin, Brice Temime-Roussel, Sylvain Ravier, Camille Mouchel-Vallon, Jean-Louis Clément, and Anne Monod
Atmos. Chem. Phys., 21, 4915–4937, https://doi.org/10.5194/acp-21-4915-2021, https://doi.org/10.5194/acp-21-4915-2021, 2021
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Organic nitrates play a crucial role in air pollution as they are considered NOx reservoirs. This work lights up the importance of their reactions with OH radicals in the aqueous phase (cloud/fog, wet aerosol), which is slower than in the gas phase. For compounds that significantly partition in water such as polyfunctional biogenic nitrates, these aqueous-phase reactions should drive their atmospheric removal, leading to a broader spatial distribution of NOx than previously accounted for.
Clémence Rose, Matti P. Rissanen, Siddharth Iyer, Jonathan Duplissy, Chao Yan, John B. Nowak, Aurélie Colomb, Régis Dupuy, Xu-Cheng He, Janne Lampilahti, Yee Jun Tham, Daniela Wimmer, Jean-Marc Metzger, Pierre Tulet, Jérôme Brioude, Céline Planche, Markku Kulmala, and Karine Sellegri
Atmos. Chem. Phys., 21, 4541–4560, https://doi.org/10.5194/acp-21-4541-2021, https://doi.org/10.5194/acp-21-4541-2021, 2021
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Sulfuric acid (H2SO4) is commonly accepted as a key precursor for atmospheric new particle formation. However, direct measurements of [H2SO4] remain challenging, motivating the development of proxies. Using data collected in two different volcanic plumes, we show, under these specific conditions, the good performance of a proxy from the literature and also highlight the benefit of the newly developed proxies for the prediction of the highest [H2SO4] values.
Keun-Ok Lee, Brice Barret, Eric L. Flochmoën, Pierre Tulet, Silvia Bucci, Marc von Hobe, Corinna Kloss, Bernard Legras, Maud Leriche, Bastien Sauvage, Fabrizio Ravegnani, and Alexey Ulanovsky
Atmos. Chem. Phys., 21, 3255–3274, https://doi.org/10.5194/acp-21-3255-2021, https://doi.org/10.5194/acp-21-3255-2021, 2021
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This paper focuses on the emission sources and pathways of pollution from the boundary layer to the Asian monsoon anticyclone (AMA) during the StratoClim aircraft campaign period. Simulations with the Meso-NH cloud-chemistry model at a horizontal resolution of 15 km are performed over the Asian region to characterize the impact of monsoon deep convection on the composition of AMA and on the formation of the Asian tropopause aerosol layer during the StratoClim campaign.
Setigui Aboubacar Keita, Eric Girard, Jean-Christophe Raut, Maud Leriche, Jean-Pierre Blanchet, Jacques Pelon, Tatsuo Onishi, and Ana Cirisan
Geosci. Model Dev., 13, 5737–5755, https://doi.org/10.5194/gmd-13-5737-2020, https://doi.org/10.5194/gmd-13-5737-2020, 2020
Michael E. Jenkin, Richard Valorso, Bernard Aumont, Mike J. Newland, and Andrew R. Rickard
Atmos. Chem. Phys., 20, 12921–12937, https://doi.org/10.5194/acp-20-12921-2020, https://doi.org/10.5194/acp-20-12921-2020, 2020
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Unsaturated organic compounds are emitted in large quantities from natural and human-influenced sources. Atmospheric removal occurs significantly by reaction with ozone, initiating reaction sequences forming free radicals and organic pollutants in the gaseous and particulate phases. Due to their very large number, it is impossible to study the reaction rate for every compound, and most have to be estimated. Updated and extended estimation methods are reported for use in atmospheric models.
Martin Heinritzi, Lubna Dada, Mario Simon, Dominik Stolzenburg, Andrea C. Wagner, Lukas Fischer, Lauri R. Ahonen, Stavros Amanatidis, Rima Baalbaki, Andrea Baccarini, Paulus S. Bauer, Bernhard Baumgartner, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, Antonio Dias, Josef Dommen, Jonathan Duplissy, Henning Finkenzeller, Carla Frege, Claudia Fuchs, Olga Garmash, Hamish Gordon, Manuel Granzin, Imad El Haddad, Xucheng He, Johanna Helm, Victoria Hofbauer, Christopher R. Hoyle, Juha Kangasluoma, Timo Keber, Changhyuk Kim, Andreas Kürten, Houssni Lamkaddam, Tiia M. Laurila, Janne Lampilahti, Chuan Ping Lee, Katrianne Lehtipalo, Markus Leiminger, Huajun Mai, Vladimir Makhmutov, Hanna Elina Manninen, Ruby Marten, Serge Mathot, Roy Lee Mauldin, Bernhard Mentler, Ugo Molteni, Tatjana Müller, Wei Nie, Tuomo Nieminen, Antti Onnela, Eva Partoll, Monica Passananti, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti P. Rissanen, Clémence Rose, Siegfried Schobesberger, Wiebke Scholz, Kay Scholze, Mikko Sipilä, Gerhard Steiner, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, Miguel Vazquez-Pufleau, Annele Virtanen, Alexander L. Vogel, Rainer Volkamer, Robert Wagner, Mingyi Wang, Lena Weitz, Daniela Wimmer, Mao Xiao, Chao Yan, Penglin Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Urs Baltensperger, Armin Hansel, Markku Kulmala, António Tomé, Paul M. Winkler, Douglas R. Worsnop, Neil M. Donahue, Jasper Kirkby, and Joachim Curtius
Atmos. Chem. Phys., 20, 11809–11821, https://doi.org/10.5194/acp-20-11809-2020, https://doi.org/10.5194/acp-20-11809-2020, 2020
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With experiments performed at CLOUD, we show how isoprene interferes in monoterpene oxidation via RO2 termination at atmospherically relevant concentrations. This interference shifts the distribution of highly oxygenated organic molecules (HOMs) away from C20 class dimers towards C15 class dimers, which subsequently reduces both biogenic nucleation and early growth rates. Our results may help to understand the absence of new-particle formation in isoprene-rich environments.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
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The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Jean-Luc Baray, Laurent Deguillaume, Aurélie Colomb, Karine Sellegri, Evelyn Freney, Clémence Rose, Joël Van Baelen, Jean-Marc Pichon, David Picard, Patrick Fréville, Laëtitia Bouvier, Mickaël Ribeiro, Pierre Amato, Sandra Banson, Angelica Bianco, Agnès Borbon, Lauréline Bourcier, Yannick Bras, Marcello Brigante, Philippe Cacault, Aurélien Chauvigné, Tiffany Charbouillot, Nadine Chaumerliac, Anne-Marie Delort, Marc Delmotte, Régis Dupuy, Antoine Farah, Guy Febvre, Andrea Flossmann, Christophe Gourbeyre, Claude Hervier, Maxime Hervo, Nathalie Huret, Muriel Joly, Victor Kazan, Morgan Lopez, Gilles Mailhot, Angela Marinoni, Olivier Masson, Nadège Montoux, Marius Parazols, Frédéric Peyrin, Yves Pointin, Michel Ramonet, Manon Rocco, Martine Sancelme, Stéphane Sauvage, Martina Schmidt, Emmanuel Tison, Mickaël Vaïtilingom, Paolo Villani, Miao Wang, Camille Yver-Kwok, and Paolo Laj
Atmos. Meas. Tech., 13, 3413–3445, https://doi.org/10.5194/amt-13-3413-2020, https://doi.org/10.5194/amt-13-3413-2020, 2020
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CO-PDD (Cézeaux-Aulnat-Opme-puy de Dôme) is a fully instrumented platform for atmospheric research. The four sites located at different altitudes from 330 to 1465 m around Clermont-Ferrand (France) host in situ and remote sensing instruments to measure atmospheric composition, including long-term trends and variability, to study interconnected processes (microphysical, chemical, biological, chemical, and dynamical) and to provide a reference point for climate models.
Camille Mouchel-Vallon, Julia Lee-Taylor, Alma Hodzic, Paulo Artaxo, Bernard Aumont, Marie Camredon, David Gurarie, Jose-Luis Jimenez, Donald H. Lenschow, Scot T. Martin, Janaina Nascimento, John J. Orlando, Brett B. Palm, John E. Shilling, Manish Shrivastava, and Sasha Madronich
Atmos. Chem. Phys., 20, 5995–6014, https://doi.org/10.5194/acp-20-5995-2020, https://doi.org/10.5194/acp-20-5995-2020, 2020
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The GoAmazon 2014/5 field campaign took place near the city of Manaus, Brazil, isolated in the Amazon rainforest, to study the impacts of urban pollution on natural air masses. We simulated this campaign with an extremely detailed organic chemistry model to understand how the city would affect the growth and composition of natural aerosol particles. Discrepancies between the model and the measurements indicate that the chemistry of naturally emitted organic compounds is still poorly understood.
Victor Lannuque, Florian Couvidat, Marie Camredon, Bernard Aumont, and Bertrand Bessagnet
Atmos. Chem. Phys., 20, 4905–4931, https://doi.org/10.5194/acp-20-4905-2020, https://doi.org/10.5194/acp-20-4905-2020, 2020
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Large uncertainties remain in modeling secondary organic aerosol (SOA) and evolution and properties in air quality models. In this article, the recently developed VBS-GECKO parameterization for SOA formation has been implemented in the air quality model CHIMERE. Simulations have been driven to identify the main SOA sources and to evaluate the sensitivity of simulated SOA concentrations to (i) secondary organic compound properties and (ii) emissions from traffic and transportation sources.
Clémence Rose, Brice Foucart, David Picard, Aurélie Colomb, Jean-Marc Metzger, Pierre Tulet, and Karine Sellegri
Atmos. Chem. Phys., 19, 13243–13265, https://doi.org/10.5194/acp-19-13243-2019, https://doi.org/10.5194/acp-19-13243-2019, 2019
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New particle formation (NPF) is a significant climate-relevant source of aerosols in the atmosphere. We show that during the eruptive periods of the Piton de la Fournaise in 2015, NPF was favoured compared to regular days. Using the largest dataset ever reported in volcanic plume conditions, we quantify the emission rates of particles over a broad size range and provide a new statistically robust parameterization to take into account this important source of atmospheric particles in models.
Émilie Poirier, Julie M. Thériault, and Maud Leriche
Hydrol. Earth Syst. Sci., 23, 4097–4111, https://doi.org/10.5194/hess-23-4097-2019, https://doi.org/10.5194/hess-23-4097-2019, 2019
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The impact of phase changes aloft on the precipitation distribution in the Kananaskis Valley, Alberta, was studied. The model reproduces well the atmospheric conditions and precipitation pattern. In this region, sublimation has a greater impact on the evolution of the precipitation than melting. The trajectories of hydrometeors explain the precipitation distribution in the valley, which can impact snowpacks. The amount of snow at the surface also depends on the strength of the downslope flow.
Valentin Duflot, Pierre Tulet, Olivier Flores, Christelle Barthe, Aurélie Colomb, Laurent Deguillaume, Mickael Vaïtilingom, Anne Perring, Alex Huffman, Mark T. Hernandez, Karine Sellegri, Ellis Robinson, David J. O'Connor, Odessa M. Gomez, Frédéric Burnet, Thierry Bourrianne, Dominique Strasberg, Manon Rocco, Allan K. Bertram, Patrick Chazette, Julien Totems, Jacques Fournel, Pierre Stamenoff, Jean-Marc Metzger, Mathilde Chabasset, Clothilde Rousseau, Eric Bourrianne, Martine Sancelme, Anne-Marie Delort, Rachel E. Wegener, Cedric Chou, and Pablo Elizondo
Atmos. Chem. Phys., 19, 10591–10618, https://doi.org/10.5194/acp-19-10591-2019, https://doi.org/10.5194/acp-19-10591-2019, 2019
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The Forests gAses aeRosols Clouds Exploratory (FARCE) campaign was conducted in March–April 2015 on the tropical island of La Réunion. For the first time, several scientific teams from different disciplines collaborated to provide reference measurements and characterization of La Réunion vegetation, volatile organic compounds (VOCs), biogenic VOCs (BVOCs), (bio)aerosols and composition of clouds, with a strong focus on the Maïdo mount slope area.
Peter Bräuer, Camille Mouchel-Vallon, Andreas Tilgner, Anke Mutzel, Olaf Böge, Maria Rodigast, Laurent Poulain, Dominik van Pinxteren, Ralf Wolke, Bernard Aumont, and Hartmut Herrmann
Atmos. Chem. Phys., 19, 9209–9239, https://doi.org/10.5194/acp-19-9209-2019, https://doi.org/10.5194/acp-19-9209-2019, 2019
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The article presents a new protocol for computer-assisted automated aqueous-phase chemistry mechanism generation, which has been validated against chamber experiments. Together with a large kinetics database and improved prediction methods for kinetic data, the novel protocol provides an unmatched tool for detailed studies of tropospheric aqueous-phase chemistry in complex model studies and for the design and analysis of chamber experiments.
Michael E. Jenkin, Richard Valorso, Bernard Aumont, and Andrew R. Rickard
Atmos. Chem. Phys., 19, 7691–7717, https://doi.org/10.5194/acp-19-7691-2019, https://doi.org/10.5194/acp-19-7691-2019, 2019
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Organic compounds are emitted in large amounts from natural and human-influenced sources. Peroxy radicals are key intermediates formed during oxidation of organic compounds, and play a central role in mechanisms forming pollutants such as ozone and organic particles. Due to the large number of different peroxy radicals formed, it is impossible to study the rates of all of their reactions, and most have to be estimated. Updated and new estimation methods are reported for use in atmospheric models
Audrey Lallement, Ludovic Besaury, Elise Tixier, Martine Sancelme, Pierre Amato, Virginie Vinatier, Isabelle Canet, Olga V. Polyakova, Viatcheslay B. Artaev, Albert T. Lebedev, Laurent Deguillaume, Gilles Mailhot, and Anne-Marie Delort
Biogeosciences, 15, 5733–5744, https://doi.org/10.5194/bg-15-5733-2018, https://doi.org/10.5194/bg-15-5733-2018, 2018
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The main objective of this work was to evaluate the potential degradation of phenol, a highly toxic pollutant, by cloud microorganisms. Phenol concentrations measured on five cloud samples collected at the PUY station in France were from 0.15 to 0.74 µg L−1. Metatranscriptomic analysis suggested that phenol could be biodegraded directly in clouds, likely by Gammaproteobacteria. A large screening showed that 93 % of 145 bacterial strains isolated from clouds were able to degrade phenol.
Victor Lannuque, Marie Camredon, Florian Couvidat, Alma Hodzic, Richard Valorso, Sasha Madronich, Bertrand Bessagnet, and Bernard Aumont
Atmos. Chem. Phys., 18, 13411–13428, https://doi.org/10.5194/acp-18-13411-2018, https://doi.org/10.5194/acp-18-13411-2018, 2018
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Large uncertainties remain in understanding the influence of atmospheric environmental conditions on secondary organic aerosol (SOA) formation, evolution and properties. In this article, the GECKO-A modelling tool has been used in a box model under various environmental conditions to (i) explore the sensitivity of SOA formation and properties to changes on physical and chemical conditions and (ii) develop a volatility-basis-set-type parameterization for air quality models.
Michael E. Jenkin, Richard Valorso, Bernard Aumont, Andrew R. Rickard, and Timothy J. Wallington
Atmos. Chem. Phys., 18, 9297–9328, https://doi.org/10.5194/acp-18-9297-2018, https://doi.org/10.5194/acp-18-9297-2018, 2018
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Organic compounds are emitted in large quantities from natural and human-influenced sources. Removal from the atmosphere occurs mainly by reaction with hydroxyl (OH) radicals, and initiates reaction sequences forming pollutants such as ozone and organic particles. Due to their very large number, it is impossible to measure the removal rate for all compounds, and most have to be estimated. An updated and extended estimation method is reported for use in atmospheric models and impact assessments.
Michael E. Jenkin, Richard Valorso, Bernard Aumont, Andrew R. Rickard, and Timothy J. Wallington
Atmos. Chem. Phys., 18, 9329–9349, https://doi.org/10.5194/acp-18-9329-2018, https://doi.org/10.5194/acp-18-9329-2018, 2018
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Organic compounds are emitted in large quantities from natural and human-influenced sources. Removal from the atmosphere occurs mainly by reaction with hydroxyl (OH) radicals, and initiates reaction sequences forming pollutants such as ozone and organic particles. Due to their very large number, it is impossible to measure the removal rate for all compounds, and most have to be estimated. An updated and extended estimation method is reported for use in atmospheric models and impact assessments.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Fabien Brosse, Maud Leriche, Céline Mari, and Fleur Couvreux
Atmos. Chem. Phys., 18, 6601–6624, https://doi.org/10.5194/acp-18-6601-2018, https://doi.org/10.5194/acp-18-6601-2018, 2018
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The cleansing capacity of the atmosphere is studied through the hydroxyl radical (OH) chemical reactivity in numerical simulations of natural and urban environments. Turbulence-driven segregation of chemical compounds in the atmospheric boundary layer is explored and may partially explain discrepancies between observed and modeled OH reactivity in both environments.
Clémence Rose, Nadine Chaumerliac, Laurent Deguillaume, Hélène Perroux, Camille Mouchel-Vallon, Maud Leriche, Luc Patryl, and Patrick Armand
Atmos. Chem. Phys., 18, 2225–2242, https://doi.org/10.5194/acp-18-2225-2018, https://doi.org/10.5194/acp-18-2225-2018, 2018
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A detailed aqueous phase mechanism CLEPS 1.1 is coupled with warm microphysics including activation of aerosol particles into cloud droplets. Simulated aqueous concentrations of carboxylic acids are close to the long-term measurements conducted at Puy de Dôme (France). Sensitivity tests show that formic and acetic acids mainly originate from the gas phase with highly variable aqueous-phase reactivity depending on cloud pH, while C3–C4 carboxylic acids mainly originate from the particulate phase.
Nolwenn Wirgot, Virginie Vinatier, Laurent Deguillaume, Martine Sancelme, and Anne-Marie Delort
Atmos. Chem. Phys., 17, 14841–14851, https://doi.org/10.5194/acp-17-14841-2017, https://doi.org/10.5194/acp-17-14841-2017, 2017
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This article highlights the interactions between H2O2 and microorganisms within the cloud system. Experiments performed in microcosms with bacterial strains isolated from clouds showed that H2O2 strongly impacted the microbial energetic state. The ATP depletion measured in the presence of H2O2 was not due to the loss of cell viability. The strong correlation between ATP and H2O2 based on the analysis of 37 real cloud samples confirmed that H2O2 modulates the metabolism of cloud microorganisms.
Allison N. Schwier, Karine Sellegri, Sébastien Mas, Bruno Charrière, Jorge Pey, Clémence Rose, Brice Temime-Roussel, Jean-Luc Jaffrezo, David Parin, David Picard, Mickael Ribeiro, Greg Roberts, Richard Sempéré, Nicolas Marchand, and Barbara D'Anna
Atmos. Chem. Phys., 17, 14645–14660, https://doi.org/10.5194/acp-17-14645-2017, https://doi.org/10.5194/acp-17-14645-2017, 2017
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In the present paper, we quantify sea-to-air emission fluxes of aerosol to the atmosphere and characterize their physical and chemical properties as a function of the seawater biochemical and physical properties. Fluxes are evaluated with an original approach, a "lab in the field" experiment that preserves the seawater and atmospheric complexity while isolating air-to-sea exchanges from their surroundings. We show different features of the aerosol emission fluxes compared to previous findings.
Kevin Berland, Clémence Rose, Jorge Pey, Anais Culot, Evelyn Freney, Nikolaos Kalivitis, Giorgios Kouvarakis, José Carlos Cerro, Marc Mallet, Karine Sartelet, Matthias Beckmann, Thierry Bourriane, Greg Roberts, Nicolas Marchand, Nikolaos Mihalopoulos, and Karine Sellegri
Atmos. Chem. Phys., 17, 9567–9583, https://doi.org/10.5194/acp-17-9567-2017, https://doi.org/10.5194/acp-17-9567-2017, 2017
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New particle formation (NPF) from gas-phase precursors is a process that is expected to drive the total number concentration of particles in the atmosphere. Here we use measurements performed simultaneously in Corsica, Crete and Mallorca to show that the spatial extent of the NPF events are several hundreds of kilometers large. Airborne measurements additionally show that nanoparticles in the marine atmosphere can either be of marine origin or from higher altitudes above the continent.
David O. Topping, James Allan, M. Rami Alfarra, and Bernard Aumont
Geosci. Model Dev., 10, 2365–2377, https://doi.org/10.5194/gmd-10-2365-2017, https://doi.org/10.5194/gmd-10-2365-2017, 2017
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Our ability to model the chemical and thermodynamic processes that lead to secondary organic aerosol (SOA) formation is thought to be hampered by the complexity of the system. In this proof of concept study, the ability to train supervised methods to predict electron impact ionisation (EI) mass spectra for the AMS is evaluated to facilitate improved model evaluation. The study demonstrates the use of a methodology that would be improved with more training data and data from simple mixed systems.
Prakash Karamchandani, Yoann Long, Guido Pirovano, Alessandra Balzarini, and Greg Yarwood
Atmos. Chem. Phys., 17, 5643–5664, https://doi.org/10.5194/acp-17-5643-2017, https://doi.org/10.5194/acp-17-5643-2017, 2017
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We quantify contributions of 13 source sectors to air pollution in Europe using a model (CAMx) with source tracking. This information is needed to develop clean air strategies that will be effective. Contributions differ between summer and winter. Sources outside western Europe and natural sources (vegetation) are important in summer. Important sources within Europe are transportation, energy production, industry, and, in winter, residential wood combustion.
Jenni Kontkanen, Katrianne Lehtipalo, Lauri Ahonen, Juha Kangasluoma, Hanna E. Manninen, Jani Hakala, Clémence Rose, Karine Sellegri, Shan Xiao, Lin Wang, Ximeng Qi, Wei Nie, Aijun Ding, Huan Yu, Shanhu Lee, Veli-Matti Kerminen, Tuukka Petäjä, and Markku Kulmala
Atmos. Chem. Phys., 17, 2163–2187, https://doi.org/10.5194/acp-17-2163-2017, https://doi.org/10.5194/acp-17-2163-2017, 2017
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The concentrations of ~1–3 nm particles were investigated at nine sites around the world. Sub-3 nm particle concentrations were highest at the sites with strong anthropogenic influence. Electrically neutral particles dominated sub-3 nm particle concentrations in polluted environments and in boreal forest during spring and summer. Sub-3 nm particle concentrations were observed to be determined by the availability of precursor vapors rather than the sink caused by preexisting aerosol particles.
Clémence Rose, Karine Sellegri, Isabel Moreno, Fernando Velarde, Michel Ramonet, Kay Weinhold, Radovan Krejci, Marcos Andrade, Alfred Wiedensohler, Patrick Ginot, and Paolo Laj
Atmos. Chem. Phys., 17, 1529–1541, https://doi.org/10.5194/acp-17-1529-2017, https://doi.org/10.5194/acp-17-1529-2017, 2017
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Using an indirect method based on particle size distribution measurements, we show that new particle formation (NPF) is responsible for a large contribution to the cloud condensation nuclei concentration at the highest observatory in the world (Bolivia, 5240 m a.s.l.) as expected from some global model predictions. We also provide unique results related to the influence of the boundary layer on the NPF process, showing direct evidence for the important NPF frequency in the free troposphere.
Alicia Gressent, Bastien Sauvage, Daniel Cariolle, Mathew Evans, Maud Leriche, Céline Mari, and Valérie Thouret
Atmos. Chem. Phys., 16, 5867–5889, https://doi.org/10.5194/acp-16-5867-2016, https://doi.org/10.5194/acp-16-5867-2016, 2016
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In chemical transport models, NOx emitted by lightning (LNOx) is instantaneously diluted into the grid. A plume-in-grid parameterization to account for the sub-grid chemistry of LNOx is presented. This approach was implemented into the GEOS-Chem model and leads to a relative increase of NOx and O3 (18 % and 2 %, respectively, in July) on a large scale downwind of lightning emissions and a relative decrease (25 % and 8 %, respectively, over central Africa in July) over the regions of emissions.
Renee C. McVay, Xuan Zhang, Bernard Aumont, Richard Valorso, Marie Camredon, Yuyi S. La, Paul O. Wennberg, and John H. Seinfeld
Atmos. Chem. Phys., 16, 2785–2802, https://doi.org/10.5194/acp-16-2785-2016, https://doi.org/10.5194/acp-16-2785-2016, 2016
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Secondary organic aerosol (SOA) affects climate change, human health, and cloud formation. We examine SOA formation from the biogenic hydrocarbon α-pinene and observe unexpected experimental results that run contrary to model predictions. Various processes are explored via modeling to rationalize the observations. The paper identifies the importance of further constraining via experiments various steps in the chemical mechanism in order to accurately predict SOA worldwide.
David Topping, Mark Barley, Michael K. Bane, Nicholas Higham, Bernard Aumont, Nicholas Dingle, and Gordon McFiggans
Geosci. Model Dev., 9, 899–914, https://doi.org/10.5194/gmd-9-899-2016, https://doi.org/10.5194/gmd-9-899-2016, 2016
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In this paper we describe the development and application of a new web-based and open-source facility, UManSysProp (http://umansysprop .seaes.manchester.ac.uk), for automating predictions of molecular and atmospheric aerosol properties. Current facilities include pure component vapour pressures, critical properties, and sub-cooled densities of organic molecules; activity coefficient predictions for mixed inorganic-organic liquid systems; hygroscopic growth factors and CCN activation potential.
L. Brégonzio-Rozier, C. Giorio, F. Siekmann, E. Pangui, S. B. Morales, B. Temime-Roussel, A. Gratien, V. Michoud, M. Cazaunau, H. L. DeWitt, A. Tapparo, A. Monod, and J.-F. Doussin
Atmos. Chem. Phys., 16, 1747–1760, https://doi.org/10.5194/acp-16-1747-2016, https://doi.org/10.5194/acp-16-1747-2016, 2016
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The impact of cloud events on isoprene secondary organic aerosol (SOA) formation has been studied from an isoprene/ NOx/light system in an atmospheric simulation chamber. aqSOA formation can be linked to water soluble volatile organic compounds' dissolution in the aqueous phase and to further aqueous phase reactions. Cloud-induced SOA formation is experimentally demonstrated in this study, thus highlighting the importance of aqueous multiphase systems in atmospheric SOA formation estimations.
B. Vié, J.-P. Pinty, S. Berthet, and M. Leriche
Geosci. Model Dev., 9, 567–586, https://doi.org/10.5194/gmd-9-567-2016, https://doi.org/10.5194/gmd-9-567-2016, 2016
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LIMA, a new quasi two-moment, mixed-phase microphysical scheme, is introduced. LIMA relies on the prognostic evolution of a multimodal aerosol population and the careful description of their nucleating properties that enable cloud droplets and pristine ice to form. This paper describes LIMA and illustrates its ability to represent aerosol-cloud interactions for 2-D idealized simulations of a squall line and orographic cold clouds.
Y. S. La, M. Camredon, P. J. Ziemann, R. Valorso, A. Matsunaga, V. Lannuque, J. Lee-Taylor, A. Hodzic, S. Madronich, and B. Aumont
Atmos. Chem. Phys., 16, 1417–1431, https://doi.org/10.5194/acp-16-1417-2016, https://doi.org/10.5194/acp-16-1417-2016, 2016
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The potential impact of chamber walls on the loss of gaseous organic species and secondary organic aerosol (SOA) formation has been explored using the GECKO-A modeling tool, which explicitly represents SOA formation and gas-wall partitioning. The model was compared with 41 smog chamber experiments of SOA formation under OH oxidation of alkane and alkene serie. The organic vapor loss to the chamber walls is found to affect SOA yields as well as the composition of the gas and the particle phase.
C. Rose, K. Sellegri, E. Freney, R. Dupuy, A. Colomb, J.-M. Pichon, M. Ribeiro, T. Bourianne, F. Burnet, and A. Schwarzenboeck
Atmos. Chem. Phys., 15, 10203–10218, https://doi.org/10.5194/acp-15-10203-2015, https://doi.org/10.5194/acp-15-10203-2015, 2015
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In the present paper we report airborne measurements of new particle formation (NPF) above the Mediterranean Sea (HYMEX campaign). We show that NPF occurs over large areas above the sea, but the process is clearly promoted at high altitude, above 1000m, i.e. frequently in the free troposphere. NPF also seems to be mainly influenced by local processes occurring above the sea. After their formation, particles slowly grow at high altitude while not being greatly depleted or affected by coagulation.
A. Hodzic, S. Madronich, P. S. Kasibhatla, G. Tyndall, B. Aumont, J. L. Jimenez, J. Lee-Taylor, and J. Orlando
Atmos. Chem. Phys., 15, 9253–9269, https://doi.org/10.5194/acp-15-9253-2015, https://doi.org/10.5194/acp-15-9253-2015, 2015
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Our study combines process and global chemistry modeling to investigate the potential effect of gas- and particle-phase organic photolysis reactions on the formation and lifetime of secondary organic aerosols (SOAs). Photolysis of the oxidation intermediates that partition between gas and particle phases to form SOA is not included in 3D models. Our results suggest that exposure to UV light can suppress the formation of SOA or even lead to its substantial loss (comparable to wet deposition).
B. Ervens, P. Renard, S. Tlili, S. Ravier, J.-L. Clément, and A. Monod
Atmos. Chem. Phys., 15, 9109–9127, https://doi.org/10.5194/acp-15-9109-2015, https://doi.org/10.5194/acp-15-9109-2015, 2015
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A detailed chemical mechanism is developed based on laboratory studies that predicts the formation of high molecular weight compounds in the aqueous phase of atmospheric aerosol particles. Model simulations using this mechanism for atmospheric conditions show that these pathways are likely not a substantial source of particle mass, unless unidentified precursors for these compounds exist that were not taken into account so far and/or the solubility of oxygen in aerosol water is overestimated.
A. N. Schwier, C. Rose, E. Asmi, A. M. Ebling, W. M. Landing, S. Marro, M.-L. Pedrotti, A. Sallon, F. Iuculano, S. Agusti, A. Tsiola, P. Pitta, J. Louis, C. Guieu, F. Gazeau, and K. Sellegri
Atmos. Chem. Phys., 15, 7961–7976, https://doi.org/10.5194/acp-15-7961-2015, https://doi.org/10.5194/acp-15-7961-2015, 2015
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The effect of ocean acidification and changing water conditions on primary (and secondary) marine aerosol emissions is not well understood on a regional or a global scale. To investigate this effect, we deployed mesocosms in the Mediterranean Sea for several weeks during both winter pre-bloom and summer oligotrophic conditions and subjected them to various levels of CO2. We observed larger effects due to the differences between a pre-bloom and oligotrophic environment than due to CO2 levels.
C. Barbet, L. Deguillaume, N. Chaumerliac, M. Leriche, A. Berger, E. Freney, A. Colomb, K. Sellegri, L. Patryl, and P. Armand
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-13395-2015, https://doi.org/10.5194/acpd-15-13395-2015, 2015
Preprint withdrawn
C. Rose, K. Sellegri, E. Asmi, M. Hervo, E. Freney, A. Colomb, H. Junninen, J. Duplissy, M. Sipilä, J. Kontkanen, K. Lehtipalo, and M. Kulmala
Atmos. Chem. Phys., 15, 3413–3428, https://doi.org/10.5194/acp-15-3413-2015, https://doi.org/10.5194/acp-15-3413-2015, 2015
C. Denjean, P. Formenti, B. Picquet-Varrault, E. Pangui, P. Zapf, Y. Katrib, C. Giorio, A. Tapparo, A. Monod, B. Temime-Roussel, P. Decorse, C. Mangeney, and J. F. Doussin
Atmos. Chem. Phys., 15, 3339–3358, https://doi.org/10.5194/acp-15-3339-2015, https://doi.org/10.5194/acp-15-3339-2015, 2015
L. Brégonzio-Rozier, F. Siekmann, C. Giorio, E. Pangui, S. B. Morales, B. Temime-Roussel, A. Gratien, V. Michoud, S. Ravier, M. Cazaunau, A. Tapparo, A. Monod, and J.-F. Doussin
Atmos. Chem. Phys., 15, 2953–2968, https://doi.org/10.5194/acp-15-2953-2015, https://doi.org/10.5194/acp-15-2953-2015, 2015
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First- and higher order -generation products formed from the oxidation of isoprene and methacrolein with OH radicals in the presence of NOx have been studied in a simulation chamber. Differences in light source are proposed to partially explain the discrepancies observed between different studies in the literature for both isoprene- and methacrolein-SOA mass yields. According to our results, these SOA yields in the atmosphere could be lower than suggested by most of the current chamber studies.
C. Denjean, P. Formenti, B. Picquet-Varrault, M. Camredon, E. Pangui, P. Zapf, Y. Katrib, C. Giorio, A. Tapparo, B. Temime-Roussel, A. Monod, B. Aumont, and J. F. Doussin
Atmos. Chem. Phys., 15, 883–897, https://doi.org/10.5194/acp-15-883-2015, https://doi.org/10.5194/acp-15-883-2015, 2015
J. Lee-Taylor, A. Hodzic, S. Madronich, B. Aumont, M. Camredon, and R. Valorso
Atmos. Chem. Phys., 15, 595–615, https://doi.org/10.5194/acp-15-595-2015, https://doi.org/10.5194/acp-15-595-2015, 2015
P. Renard, F. Siekmann, G. Salque, C. Demelas, B. Coulomb, L. Vassalo, S. Ravier, B. Temime-Roussel, D. Voisin, and A. Monod
Atmos. Chem. Phys., 15, 21–35, https://doi.org/10.5194/acp-15-21-2015, https://doi.org/10.5194/acp-15-21-2015, 2015
H. Holmgren, K. Sellegri, M. Hervo, C. Rose, E. Freney, P. Villani, and P. Laj
Atmos. Chem. Phys., 14, 9537–9554, https://doi.org/10.5194/acp-14-9537-2014, https://doi.org/10.5194/acp-14-9537-2014, 2014
M. Joly, P. Amato, L. Deguillaume, M. Monier, C. Hoose, and A.-M. Delort
Atmos. Chem. Phys., 14, 8185–8195, https://doi.org/10.5194/acp-14-8185-2014, https://doi.org/10.5194/acp-14-8185-2014, 2014
V. Michoud, A. Colomb, A. Borbon, K. Miet, M. Beekmann, M. Camredon, B. Aumont, S. Perrier, P. Zapf, G. Siour, W. Ait-Helal, C. Afif, A. Kukui, M. Furger, J. C. Dupont, M. Haeffelin, and J. F. Doussin
Atmos. Chem. Phys., 14, 2805–2822, https://doi.org/10.5194/acp-14-2805-2014, https://doi.org/10.5194/acp-14-2805-2014, 2014
L. Deguillaume, T. Charbouillot, M. Joly, M. Vaïtilingom, M. Parazols, A. Marinoni, P. Amato, A.-M. Delort, V. Vinatier, A. Flossmann, N. Chaumerliac, J. M. Pichon, S. Houdier, P. Laj, K. Sellegri, A. Colomb, M. Brigante, and G. Mailhot
Atmos. Chem. Phys., 14, 1485–1506, https://doi.org/10.5194/acp-14-1485-2014, https://doi.org/10.5194/acp-14-1485-2014, 2014
J.-F. Doussin and A. Monod
Atmos. Chem. Phys., 13, 11625–11641, https://doi.org/10.5194/acp-13-11625-2013, https://doi.org/10.5194/acp-13-11625-2013, 2013
C. Rose, J. Boulon, M. Hervo, H. Holmgren, E. Asmi, M. Ramonet, P. Laj, and K. Sellegri
Atmos. Chem. Phys., 13, 11573–11594, https://doi.org/10.5194/acp-13-11573-2013, https://doi.org/10.5194/acp-13-11573-2013, 2013
M. Leriche, J.-P. Pinty, C. Mari, and D. Gazen
Geosci. Model Dev., 6, 1275–1298, https://doi.org/10.5194/gmd-6-1275-2013, https://doi.org/10.5194/gmd-6-1275-2013, 2013
P. Renard, F. Siekmann, A. Gandolfo, J. Socorro, G. Salque, S. Ravier, E. Quivet, J.-L. Clément, M. Traikia, A.-M. Delort, D. Voisin, V. Vuitton, R. Thissen, and A. Monod
Atmos. Chem. Phys., 13, 6473–6491, https://doi.org/10.5194/acp-13-6473-2013, https://doi.org/10.5194/acp-13-6473-2013, 2013
C. Mouchel-Vallon, P. Bräuer, M. Camredon, R. Valorso, S. Madronich, H. Herrmann, and B. Aumont
Atmos. Chem. Phys., 13, 1023–1037, https://doi.org/10.5194/acp-13-1023-2013, https://doi.org/10.5194/acp-13-1023-2013, 2013
V. Michoud, A. Kukui, M. Camredon, A. Colomb, A. Borbon, K. Miet, B. Aumont, M. Beekmann, R. Durand-Jolibois, S. Perrier, P. Zapf, G. Siour, W. Ait-Helal, N. Locoge, S. Sauvage, C. Afif, V. Gros, M. Furger, G. Ancellet, and J. F. Doussin
Atmos. Chem. Phys., 12, 11951–11974, https://doi.org/10.5194/acp-12-11951-2012, https://doi.org/10.5194/acp-12-11951-2012, 2012
Related subject area
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Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
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
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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
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SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
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Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
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Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
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High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
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Short summary
The Cloud Explicit Physico-chemical Scheme (CLEPS 1.0) describes oxidation of water-soluble organic compounds resulting from isoprene oxidation. It is based on structure activity relationships (SARs) (global rate constants and branching ratios for HO• abstraction and addition) and GROMHE SAR (Henry's law constants for undocumented species). It is coupled to the MCM gas phase mechanism and is included in a model using the DSMACC model and KPP to analyze experimental and field data.
The Cloud Explicit Physico-chemical Scheme (CLEPS 1.0) describes oxidation of water-soluble...
