Articles | Volume 18, issue 11
https://doi.org/10.5194/gmd-18-3211-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3211-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
02 Jun 2025
Methods for assessment of models |
| 02 Jun 2025
| 02 Jun 2025
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Maurin Zouzoua
CORRESPONDING AUTHOR
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, CNES, Guyancourt, France
Sophie Bastin
CORRESPONDING AUTHOR
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, CNES, Guyancourt, France
Fabienne Lohou
Centre de Recherches Atmosphériques (CRA)/Laboratoire d'Aérologie de Toulouse (LAERO), Toulouse, France
Marie Lothon
Centre de Recherches Atmosphériques (CRA)/Laboratoire d'Aérologie de Toulouse (LAERO), Toulouse, France
Marjolaine Chiriaco
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, CNES, Guyancourt, France
Mathilde Jome
Centre de Recherches Atmosphériques (CRA)/Laboratoire d'Aérologie de Toulouse (LAERO), Toulouse, France
Cécile Mallet
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, CNES, Guyancourt, France
Laurent Barthes
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, CNES, Guyancourt, France
Guylaine Canut
Centre National de Recherches Météorologiques (CNRM)/Météo-France, Toulouse, France
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Atmos. Meas. Tech., 18, 93–114, https://doi.org/10.5194/amt-18-93-2025, https://doi.org/10.5194/amt-18-93-2025, 2025
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Sandrine Bony, Marie Lothon, Julien Delanoë, Pierre Coutris, Jean-Claude Etienne, Franziska Aemisegger, Anna Lea Albright, Thierry André, Hubert Bellec, Alexandre Baron, Jean-François Bourdinot, Pierre-Etienne Brilouet, Aurélien Bourdon, Jean-Christophe Canonici, Christophe Caudoux, Patrick Chazette, Michel Cluzeau, Céline Cornet, Jean-Philippe Desbios, Dominique Duchanoy, Cyrille Flamant, Benjamin Fildier, Christophe Gourbeyre, Laurent Guiraud, Tetyana Jiang, Claude Lainard, Christophe Le Gac, Christian Lendroit, Julien Lernould, Thierry Perrin, Frédéric Pouvesle, Pascal Richard, Nicolas Rochetin, Kevin Salaün, Alfons Schwarzenboeck, Guillaume Seurat, Bjorn Stevens, Julien Totems, Ludovic Touzé-Peiffer, Gilles Vergez, Jessica Vial, Leonie Villiger, and Raphaela Vogel
Earth Syst. Sci. Data, 14, 2021–2064, https://doi.org/10.5194/essd-14-2021-2022, https://doi.org/10.5194/essd-14-2021-2022, 2022
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The French ATR42 research aircraft participated in the EUREC4A international field campaign that took place in 2020 over the tropical Atlantic, east of Barbados. We present the extensive instrumentation of the aircraft, the research flights and the different measurements. We show that the ATR measurements of humidity, wind, aerosols and cloudiness in the lower atmosphere are robust and consistent with each other. They will make it possible to advance understanding of cloud–climate interactions.
Adrien Deroubaix, Laurent Menut, Cyrille Flamant, Peter Knippertz, Andreas H. Fink, Anneke Batenburg, Joel Brito, Cyrielle Denjean, Cheikh Dione, Régis Dupuy, Valerian Hahn, Norbert Kalthoff, Fabienne Lohou, Alfons Schwarzenboeck, Guillaume Siour, Paolo Tuccella, and Christiane Voigt
Atmos. Chem. Phys., 22, 3251–3273, https://doi.org/10.5194/acp-22-3251-2022, https://doi.org/10.5194/acp-22-3251-2022, 2022
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During the summer monsoon in West Africa, pollutants emitted in urbanized areas modify cloud cover and precipitation patterns. We analyze these patterns with the WRF-CHIMERE model, integrating the effects of aerosols on meteorology, based on the numerous observations provided by the Dynamics-Aerosol-Climate-Interactions campaign. This study adds evidence to recent findings that increased pollution levels in West Africa delay the breakup time of low-level clouds and reduce precipitation.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, Rodrigo Guzman, Cyprien Gindre, Po-Lun Ma, and Marjolaine Chiriaco
Atmos. Meas. Tech., 15, 1055–1074, https://doi.org/10.5194/amt-15-1055-2022, https://doi.org/10.5194/amt-15-1055-2022, 2022
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Oscar Javier Rojas Muñoz, Marjolaine Chiriaco, Sophie Bastin, and Justine Ringard
Atmos. Chem. Phys., 21, 15699–15723, https://doi.org/10.5194/acp-21-15699-2021, https://doi.org/10.5194/acp-21-15699-2021, 2021
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A method is developed and evaluated to quantify each process that affects hourly 2 m temperature variations on a local scale, based almost exclusively on observations retrieved from an observatory near the Paris region. Each term involved in surface temperature variations is estimated, and its contribution and importance are also assessed. It is found that clouds are the main modulator on hourly temperature variations for most hours of the day, and thus their characterization is addressed.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Pierre-Etienne Brilouet, Marie Lothon, Jean-Claude Etienne, Pascal Richard, Sandrine Bony, Julien Lernoult, Hubert Bellec, Gilles Vergez, Thierry Perrin, Julien Delanoë, Tetyana Jiang, Frédéric Pouvesle, Claude Lainard, Michel Cluzeau, Laurent Guiraud, Patrice Medina, and Theotime Charoy
Earth Syst. Sci. Data, 13, 3379–3398, https://doi.org/10.5194/essd-13-3379-2021, https://doi.org/10.5194/essd-13-3379-2021, 2021
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During the EUREC4A field experiment that took place over the tropical Atlantic Ocean east of Barbados, the French ATR 42 environment research aircraft of SAFIRE aimed to characterize the shallow cloud properties near cloud base and the turbulent structure of the subcloud layer. The high-frequency measurements of wind, temperature and humidity as well as their translation in terms of turbulent fluctuations, turbulent moments and characteristic length scales of turbulence are presented.
Carlos Román-Cascón, Marie Lothon, Fabienne Lohou, Oscar Hartogensis, Jordi Vila-Guerau de Arellano, David Pino, Carlos Yagüe, and Eric R. Pardyjak
Geosci. Model Dev., 14, 3939–3967, https://doi.org/10.5194/gmd-14-3939-2021, https://doi.org/10.5194/gmd-14-3939-2021, 2021
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The type of vegetation (or land cover) and its status influence the heat and water transfers between the surface and the air, affecting the processes that develop in the atmosphere at different (but connected) spatiotemporal scales. In this work, we investigate how these transfers are affected by the way the surface is represented in a widely used weather model. The results encourage including realistic high-resolution and updated land cover databases in models to improve their predictions.
Maurin Zouzoua, Fabienne Lohou, Paul Assamoi, Marie Lothon, Véronique Yoboue, Cheikh Dione, Norbert Kalthoff, Bianca Adler, Karmen Babić, Xabier Pedruzo-Bagazgoitia, and Solène Derrien
Atmos. Chem. Phys., 21, 2027–2051, https://doi.org/10.5194/acp-21-2027-2021, https://doi.org/10.5194/acp-21-2027-2021, 2021
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Based on a field experiment conducted in June and July 2016, we analyzed the daytime breakup of continental low-level stratiform clouds over southern West Africa in order to provide complementary guidance for model evaluation during the monsoon season. Those clouds exhibit weaker temperature and moisture jumps at the top compared to marine stratiform clouds. Their lifetime and the transition towards shallow convective clouds during daytime hours depend on their coupling with the surface.
Barbara Altstädter, Konrad Deetz, Bernhard Vogel, Karmen Babić, Cheikh Dione, Federica Pacifico, Corinne Jambert, Friederike Ebus, Konrad Bärfuss, Falk Pätzold, Astrid Lampert, Bianca Adler, Norbert Kalthoff, and Fabienne Lohou
Atmos. Chem. Phys., 20, 7911–7928, https://doi.org/10.5194/acp-20-7911-2020, https://doi.org/10.5194/acp-20-7911-2020, 2020
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We present the high vertical variability of the black carbon (BC) mass concentration measured with the unmanned aerial system ALADINA during the field experiment of DACCIWA. The COSMO-ART model output was applied for the campaign period and is compared with the observational BC data during a case study on 14–15 July 2016. Enhanced BC concentrations were related to transport processes to the measurement site by maritime inflow and not to local emissions as initially expected.
Xabier Pedruzo-Bagazgoitia, Stephan R. de Roode, Bianca Adler, Karmen Babić, Cheikh Dione, Norbert Kalthoff, Fabienne Lohou, Marie Lothon, and Jordi Vilà-Guerau de Arellano
Atmos. Chem. Phys., 20, 2735–2754, https://doi.org/10.5194/acp-20-2735-2020, https://doi.org/10.5194/acp-20-2735-2020, 2020
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Using a high-resolution model we simulate the transition from night to day clouds on southern West Africa using observations from the DACCIWA project. We find that the radiative effects of clouds help mantain a thick cloud layer in the night, while the mixing of cloud air with air above during the day, aided by moisture and heat fluxes at the surface, thins this layer and promotes its transition to other clouds. The effect of changing wind with height accelerates the transition.
Fabienne Lohou, Norbert Kalthoff, Bianca Adler, Karmen Babić, Cheikh Dione, Marie Lothon, Xabier Pedruzo-Bagazgoitia, and Maurin Zouzoua
Atmos. Chem. Phys., 20, 2263–2275, https://doi.org/10.5194/acp-20-2263-2020, https://doi.org/10.5194/acp-20-2263-2020, 2020
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A conceptual model of the low-level stratiform clouds (LLSCs), which develop almost every night in southern West Africa, is built with the dataset acquired during the DACCIWA (Dynamics Aerosol Chemistry Cloud Interactions in West Africa) ground-based field experiment. Several processes occur during the four phases composing this diurnal cycle: the cooling of the air until saturation (stable and jet phases), LLSC and low-level jet interactions (stratus phase), and LLSC breakup (convective phase).
Karmen Babić, Norbert Kalthoff, Bianca Adler, Julian F. Quinting, Fabienne Lohou, Cheikh Dione, and Marie Lothon
Atmos. Chem. Phys., 19, 13489–13506, https://doi.org/10.5194/acp-19-13489-2019, https://doi.org/10.5194/acp-19-13489-2019, 2019
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This study investigates differences in atmospheric conditions between nights with and without low-level stratus clouds (LLCs) over southern West Africa. We use high-quality observations collected during 2016 summer monsoon season and the ERA5 reanalysis data set. Our results show that the formation of LLCs depends on the interplay between the onset time and strength of the nocturnal low-level jet, horizontal cold-air advection, and the overall moisture level in the whole region.
Justine Ringard, Marjolaine Chiriaco, Sophie Bastin, and Florence Habets
Atmos. Chem. Phys., 19, 13129–13155, https://doi.org/10.5194/acp-19-13129-2019, https://doi.org/10.5194/acp-19-13129-2019, 2019
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This study characterizes the changes observed at Paris urban scale and attempts to identify the surface–atmosphere feedbacks likely to explain the trends observed as a function of the different configurations of large-scale dynamics. This article is interested in several atmospheric parameters and their possible retroactions. Finally, to study urban environments, the analysis at the local scale is essential because it is very poorly represented in the model.
Marie Lothon, Paul Barnéoud, Omar Gabella, Fabienne Lohou, Solène Derrien, Sylvain Rondi, Marjolaine Chiriaco, Sophie Bastin, Jean-Charles Dupont, Martial Haeffelin, Jordi Badosa, Nicolas Pascal, and Nadège Montoux
Atmos. Meas. Tech., 12, 5519–5534, https://doi.org/10.5194/amt-12-5519-2019, https://doi.org/10.5194/amt-12-5519-2019, 2019
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In the context of an atmospheric network of instrumented sites equipped with sky cameras for cloud monitoring, we present an algorithm named ELIFAN, which aims to estimate the cloud cover amount from full-sky visible daytime images. ELIFAN is based on red-to-blue ratio thresholding applied on the image pixels and on the use of a blue-sky library. We present its principle and its performance and highlight the interest of combining several complementary instruments.
Jesús Yus-Díez, Mireia Udina, Maria Rosa Soler, Marie Lothon, Erik Nilsson, Joan Bech, and Jielun Sun
Atmos. Chem. Phys., 19, 9495–9514, https://doi.org/10.5194/acp-19-9495-2019, https://doi.org/10.5194/acp-19-9495-2019, 2019
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This study helps improve the understanding of the turbulence description and the interactions occurring in the lower part of the boundary layer. It is carried out at an orographically influenced site close to the Pyrenees to explore the hockey-stick transition (HOST) theory. HOST is seen to be strongly dependent on both the meteorological conditions and the orographic features. Examples of intermittent turbulence events that lead to transitions between the turbulence regimes are also identified.
Cheikh Dione, Fabienne Lohou, Marie Lothon, Bianca Adler, Karmen Babić, Norbert Kalthoff, Xabier Pedruzo-Bagazgoitia, Yannick Bezombes, and Omar Gabella
Atmos. Chem. Phys., 19, 8979–8997, https://doi.org/10.5194/acp-19-8979-2019, https://doi.org/10.5194/acp-19-8979-2019, 2019
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Low atmospheric dynamics and low-level cloud (LLC) macrophysical properties are analyzed using in situ and remote sensing data collected from 20 June to 30 July at Savè, Benin, during the DACCIWA field campaign in 2016. We find that the low-level jet (LLJ), LLCs, monsoon flow, and maritime inflow reveal a day-to-day variability. LLCs form at the same level as the jet core height. The cloud base height is stationary at night and remains below the jet. The cloud top height is found above the jet.
Lluís Fita, Jan Polcher, Theodore M. Giannaros, Torge Lorenz, Josipa Milovac, Giannis Sofiadis, Eleni Katragkou, and Sophie Bastin
Geosci. Model Dev., 12, 1029–1066, https://doi.org/10.5194/gmd-12-1029-2019, https://doi.org/10.5194/gmd-12-1029-2019, 2019
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Regional climate experiments coordinated throughout CORDEX aim to study and provide high-quality climate data over a given region. The data are used in climate change mitigation and adaptation policy studies and by stakeholders. CORDEX requires a list of variables, most of which are not provided by atmospheric models. Aiming to help the community and to maximize the use of CORDEX exercises, we create a new module for WRF models to directly produce them by adding
genericand
additionalones.
Federica Pacifico, Claire Delon, Corinne Jambert, Pierre Durand, Eleanor Morris, Mat J. Evans, Fabienne Lohou, Solène Derrien, Venance H. E. Donnou, Arnaud V. Houeto, Irene Reinares Martínez, and Pierre-Etienne Brilouet
Atmos. Chem. Phys., 19, 2299–2325, https://doi.org/10.5194/acp-19-2299-2019, https://doi.org/10.5194/acp-19-2299-2019, 2019
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Biogenic fluxes from soil at a local and regional scale are crucial to study air pollution and climate. Here we present field measurements of soil fluxes of nitric oxide (NO) and ammonia (NH3) observed over four different land cover types, i.e. bare soil, grassland, maize field, and forest, at an inland rural site in Benin, West Africa, during the DACCIWA field campaign in
June and July 2016.
Sophie L. Haslett, Jonathan W. Taylor, Konrad Deetz, Bernhard Vogel, Karmen Babić, Norbert Kalthoff, Andreas Wieser, Cheikh Dione, Fabienne Lohou, Joel Brito, Régis Dupuy, Alfons Schwarzenboeck, Paul Zieger, and Hugh Coe
Atmos. Chem. Phys., 19, 1505–1520, https://doi.org/10.5194/acp-19-1505-2019, https://doi.org/10.5194/acp-19-1505-2019, 2019
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As the population in West Africa grows and air pollution increases, it is becoming ever more important to understand the effects of this pollution on the climate and on health. Aerosol particles can grow by absorbing water from the air around them. This paper shows that during the monsoon season, aerosol particles in the region are likely to grow significantly because of the high moisture in the air. This means that climate effects from increasing pollution will be enhanced.
Sophie Bastin, Philippe Drobinski, Marjolaine Chiriaco, Olivier Bock, Romain Roehrig, Clemente Gallardo, Dario Conte, Marta Domínguez Alonso, Laurent Li, Piero Lionello, and Ana C. Parracho
Atmos. Chem. Phys., 19, 1471–1490, https://doi.org/10.5194/acp-19-1471-2019, https://doi.org/10.5194/acp-19-1471-2019, 2019
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This paper uses colocated observations of temperature, precipitation and humidity to investigate the triggering of precipitation. It shows that there is a critical value of humidity above which precipitation picks up. This critical value depends on T and varies spatially. It also analyses how this dependency is reproduced in regional climate simulations over Europe. Models with too little and too light precipitation have both lower critical value of humidity and higher probability to exceed it.
Karmen Babić, Bianca Adler, Norbert Kalthoff, Hendrik Andersen, Cheikh Dione, Fabienne Lohou, Marie Lothon, and Xabier Pedruzo-Bagazgoitia
Atmos. Chem. Phys., 19, 1281–1299, https://doi.org/10.5194/acp-19-1281-2019, https://doi.org/10.5194/acp-19-1281-2019, 2019
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The first detailed observational analysis of the complete diurnal cycle of low-level clouds (LLC) and associated atmospheric processes over southern West Africa is performed using the data gathered within the DACCIWA (Dynamics-Aerosol-Chemistry-Cloud-Interactions in West Africa) ground-based campaign. We find cooling related to the horizontal advection, which occurs in connection with the inflow of cool maritime air mass and a prominent low-level jet, to have the dominant role in LLC formation.
Bianca Adler, Karmen Babić, Norbert Kalthoff, Fabienne Lohou, Marie Lothon, Cheikh Dione, Xabier Pedruzo-Bagazgoitia, and Hendrik Andersen
Atmos. Chem. Phys., 19, 663–681, https://doi.org/10.5194/acp-19-663-2019, https://doi.org/10.5194/acp-19-663-2019, 2019
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This study deals with nocturnal stratiform low-level clouds that frequently form in the atmospheric boundary layer over southern West Africa. We use observational data from 11 nights to characterize the clouds and intranight variability of boundary layer conditions as well as to assess the physical processes relevant for cloud formation. We find that cooling is crucial to reach saturation and a large part of the cooling is related to horizontal advection of cool air from the Gulf of Guinea.
Ana C. Parracho, Olivier Bock, and Sophie Bastin
Atmos. Chem. Phys., 18, 16213–16237, https://doi.org/10.5194/acp-18-16213-2018, https://doi.org/10.5194/acp-18-16213-2018, 2018
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Integrated water vapour from GPS observations and two modern atmospheric reanalyses were compared for 1995–2010. Means, variability and trend signs were in general good agreement. Regions and GPS stations with poor agreement were investigated further. Representativeness issues, uncertainties in reanalyses, and inhomogeneities in GPS were evidenced. Reanalyses were compared for an extended period, and a focus on north Africa and Australia highlighted the impact of dynamics on water vapour trends.
Vincent Noel, Hélène Chepfer, Marjolaine Chiriaco, and John Yorks
Atmos. Chem. Phys., 18, 9457–9473, https://doi.org/10.5194/acp-18-9457-2018, https://doi.org/10.5194/acp-18-9457-2018, 2018
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From 3 years of observations from the CATS lidar on the International Space Station we document the daily cycle of the vertical distribution of clouds.
This is the first time this is documented over several continents and oceans using finely resolved measurements on a near-global scale from a single instrument.
We show that other instruments observing clouds from space, like CALIPSO, document extremes of the daily cycle over ocean and closer to the average over land.
Hervé Petetin, Bastien Sauvage, Herman G. J. Smit, François Gheusi, Fabienne Lohou, Romain Blot, Hannah Clark, Gilles Athier, Damien Boulanger, Jean-Marc Cousin, Philippe Nedelec, Patrick Neis, Susanne Rohs, and Valérie Thouret
Atmos. Chem. Phys., 18, 9561–9581, https://doi.org/10.5194/acp-18-9561-2018, https://doi.org/10.5194/acp-18-9561-2018, 2018
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Based on the numerous profiles available since 1994, this paper investigates the vertical stratification of ozone, carbon monoxide and relative humidity in the lower part of the troposphere (planetary boundary layer, lower free troposphere). Such a characterization of the vertical distribution of pollution is notably important for better understanding vertical exchanges and evaluating models on the vertical dimension.
Marjolaine Chiriaco, Jean-Charles Dupont, Sophie Bastin, Jordi Badosa, Julio Lopez, Martial Haeffelin, Helene Chepfer, and Rodrigo Guzman
Earth Syst. Sci. Data, 10, 919–940, https://doi.org/10.5194/essd-10-919-2018, https://doi.org/10.5194/essd-10-919-2018, 2018
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A scientific approach is presented to aggregate and harmonize a set of 60 geophysical variables at hourly scale over a decade, and to allow multiannual and multi-variable studies combining atmospheric dynamics and thermodynamics, radiation, clouds and aerosols from ground-based observations.
Norbert Kalthoff, Fabienne Lohou, Barbara Brooks, Gbenga Jegede, Bianca Adler, Karmen Babić, Cheikh Dione, Adewale Ajao, Leonard K. Amekudzi, Jeffrey N. A. Aryee, Muritala Ayoola, Geoffrey Bessardon, Sylvester K. Danuor, Jan Handwerker, Martin Kohler, Marie Lothon, Xabier Pedruzo-Bagazgoitia, Victoria Smith, Lukman Sunmonu, Andreas Wieser, Andreas H. Fink, and Peter Knippertz
Atmos. Chem. Phys., 18, 2913–2928, https://doi.org/10.5194/acp-18-2913-2018, https://doi.org/10.5194/acp-18-2913-2018, 2018
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Extended low-level stratus clouds (LLC) form frequently in southern West Africa during the night-time and persist long into the next day. They affect the radiation budget, atmospheric boundary-layer (BL) evolution and regional climate. The relevant processes governing their formation and dissolution are not fully understood. Thus, a field campaign was conducted in summer 2016, which provided a comprehensive data set for process studies, specifically of interactions between LLC and BL conditions.
Pauline Martinet, Domenico Cimini, Francesco De Angelis, Guylaine Canut, Vinciane Unger, Remi Guillot, Diane Tzanos, and Alexandre Paci
Atmos. Meas. Tech., 10, 3385–3402, https://doi.org/10.5194/amt-10-3385-2017, https://doi.org/10.5194/amt-10-3385-2017, 2017
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Microwave radiometers have the capability of observing temperature and humidity profiles with a few minute time resolution. This study investigates the potential benefit of this instrument to improve weather forecasts thanks to a better initialization of the model. Our results show that a significant improvement can be expected in the model initialization in the first 3 km with potential impacts on weather forecasts.
Lucie Rottner, Christophe Baehr, Fleur Couvreux, Guylaine Canut, and Thomas Rieutord
Atmos. Chem. Phys., 17, 6531–6546, https://doi.org/10.5194/acp-17-6531-2017, https://doi.org/10.5194/acp-17-6531-2017, 2017
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In this study we explore a new way to model sub-grid turbulence using particle systems. The ability of particle systems to model small-scale turbulence is evaluated using high-resolution numerical simulations performed with the atmospheric model Meso-NH. The study shows that the particle system is able to reproduce much finer turbulent structures than the high-resolution simulations. It also provides an estimate of the effective spatial and temporal resolution of the numerical models.
Mohamed Djallel Dilmi, Cécile Mallet, Laurent Barthes, and Aymeric Chazottes
Atmos. Meas. Tech., 10, 1557–1574, https://doi.org/10.5194/amt-10-1557-2017, https://doi.org/10.5194/amt-10-1557-2017, 2017
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The concept of a rain event is used to obtain a parsimonious characterisation of rain events using a minimal subset of variables at macrophysical scale. A classification in five classes is obtained in a unsupervised way from this subset. Relationships between these classes of microphysical parameters of precipitation are highlighted. There are several implications especially for remote sensing in the context of weather radar applications and quantitative precipitation estimation.
Line Båserud, Joachim Reuder, Marius O. Jonassen, Stephan T. Kral, Mostafa B. Paskyabi, and Marie Lothon
Atmos. Meas. Tech., 9, 4901–4913, https://doi.org/10.5194/amt-9-4901-2016, https://doi.org/10.5194/amt-9-4901-2016, 2016
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The micro-RPAS SUMO (Small Unmanned Meteorological Observer) equipped with a five-hole-probe (5HP) system for turbulent flow measurements was operated in 49 flight missions during the BLLAST (Boundary-Layer Late Afternoon and Sunset Turbulence) field campaign in 2011. Based on data sets from these flights, we investigate the potential and limitations of airborne velocity variance and TKE (turbulent kinetic energy) estimations by an RPAS with a take-off weight below 1 kg.
Guylaine Canut, Fleur Couvreux, Marie Lothon, Dominique Legain, Bruno Piguet, Astrid Lampert, William Maurel, and Eric Moulin
Atmos. Meas. Tech., 9, 4375–4386, https://doi.org/10.5194/amt-9-4375-2016, https://doi.org/10.5194/amt-9-4375-2016, 2016
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Turbulent processes of the atmospheric boundary layer contribute the most to transfers between the surface and the atmosphere. Typically, turbulent boundary layer parameters are measured by sonic anemometers on masts and by research aircraft. This is to measure in situ turbulent parameters in the planetary boundary layer (PBL) at altitudes above 50 m. For this purpose, our team have developed a system under a tethered balloon which has been in use since 2010.
Joan Cuxart, Burkhard Wrenger, Daniel Martínez-Villagrasa, Joachim Reuder, Marius O. Jonassen, Maria A. Jiménez, Marie Lothon, Fabienne Lohou, Oscar Hartogensis, Jens Dünnermann, Laura Conangla, and Anirban Garai
Atmos. Chem. Phys., 16, 9489–9504, https://doi.org/10.5194/acp-16-9489-2016, https://doi.org/10.5194/acp-16-9489-2016, 2016
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Estimations of the effect of thermal advection in the surface energy budget are provided. Data from the experimental campaign BLLAST, held in Southern France in summer 2011, are used, including airborne data by drones and surface-based instrumentation. Model data outputs and satellite information are also inspected. Surface heterogeneities of the order of the kilometer or larger seem to have little effect on the budget, whereas hectometer-scale structures may contribute significantly to it.
Fleur Couvreux, Eric Bazile, Guylaine Canut, Yann Seity, Marie Lothon, Fabienne Lohou, Françoise Guichard, and Erik Nilsson
Atmos. Chem. Phys., 16, 8983–9002, https://doi.org/10.5194/acp-16-8983-2016, https://doi.org/10.5194/acp-16-8983-2016, 2016
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This study evaluates the ability of operational models to predict the boundary-layer turbulent processes and mesoscale variability observed during the Boundary Layer Late-Afternoon and Sunset Turbulence field campaign. The models succeed in reproducing the variability from one day to another in terms of cloud cover, temperature and boundary-layer depth. However, they exhibit some systematic biases. The high-resolution model reproduces the vertical structures better.
François Mercier, Aymeric Chazottes, Laurent Barthès, and Cécile Mallet
Atmos. Meas. Tech., 9, 3145–3163, https://doi.org/10.5194/amt-9-3145-2016, https://doi.org/10.5194/amt-9-3145-2016, 2016
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The aim of this study is to retrieve vertical profiles of raindrop size distributions and vertical winds from radar and ground measurements. This is crucial to understand the phenomena acting on the raindrops at small scale during their fall and then to be able to merge measurements of rain at different heights and scales (from radar, rain gauges, satellites etc.). It could also help to improve the treatment of radar data and to better parameterize rain in numerical weather prediction models.
Erik Nilsson, Fabienne Lohou, Marie Lothon, Eric Pardyjak, Larry Mahrt, and Clara Darbieu
Atmos. Chem. Phys., 16, 8849–8872, https://doi.org/10.5194/acp-16-8849-2016, https://doi.org/10.5194/acp-16-8849-2016, 2016
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The evolution of near-surface turbulence kinetic energy (TKE) and its budget in the afternoon transition has been studied based on field measurements. The study shows that TKE transport is an important budget term that needs to be taken into account in modeling of TKE. A non-local parametrization of dissipation using a TKE–length scale model which takes into account of boundary layer depth also gave improved results compared to a local parametrization.
Erik Nilsson, Marie Lothon, Fabienne Lohou, Eric Pardyjak, Oscar Hartogensis, and Clara Darbieu
Atmos. Chem. Phys., 16, 8873–8898, https://doi.org/10.5194/acp-16-8873-2016, https://doi.org/10.5194/acp-16-8873-2016, 2016
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A new simple model for turbulence kinetic energy (TKE) and its budget is presented for the sheared convective atmospheric boundary layer. It is used to study effects of buoyancy and shear on TKE evolution during the afternoon transition, especially near the surface. We also find a region of weak turbulence during unstable afternoon conditions below the inversion top, which we refer to as a "pre-residual layer".
Astrid Lampert, Falk Pätzold, Maria Antonia Jiménez, Lennart Lobitz, Sabrina Martin, Gerald Lohmann, Guylaine Canut, Dominique Legain, Jens Bange, Dani Martínez-Villagrasa, and Joan Cuxart
Atmos. Chem. Phys., 16, 8009–8021, https://doi.org/10.5194/acp-16-8009-2016, https://doi.org/10.5194/acp-16-8009-2016, 2016
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For a large field experiment in summer 2011 in southern France (BLLAST campaign), the development of turbulence in the atmosphere was analysed during the afternoon and evening. Besides ground-based remote sensing and in situ observations, turbulence parameters were measured with an unmanned aerial vehicle and analysed by numerical simulation. Turbulence decreased during the afternoon, but increased after sunset due to local wind systems. Turbulent eddies lost symmetry during the transition.
C. Darbieu, F. Lohou, M. Lothon, J. Vilà-Guerau de Arellano, F. Couvreux, P. Durand, D. Pino, E. G. Patton, E. Nilsson, E. Blay-Carreras, and B. Gioli
Atmos. Chem. Phys., 15, 10071–10086, https://doi.org/10.5194/acp-15-10071-2015, https://doi.org/10.5194/acp-15-10071-2015, 2015
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A case study of the BLLAST experiment is considered to explore the decay of turbulence that occurs in the convective boundary layer over land during the afternoon. Based on observations and on a large-eddy simulation, the analysis reveals two phases in the afternoon: a first quasi-stationary phase when the turbulent kinetic energy slowly decays without significant change in the turbulence structure and a second phase of more rapid decay with a change in spectral turbulence characteristics.
H. P. Pietersen, J. Vilà-Guerau de Arellano, P. Augustin, A. van de Boer, O. de Coster, H. Delbarre, P. Durand, M. Fourmentin, B. Gioli, O. Hartogensis, F. Lohou, M. Lothon, H. G. Ouwersloot, D. Pino, and J. Reuder
Atmos. Chem. Phys., 15, 4241–4257, https://doi.org/10.5194/acp-15-4241-2015, https://doi.org/10.5194/acp-15-4241-2015, 2015
R. G. Sivira, H. Brogniez, C. Mallet, and Y. Oussar
Atmos. Meas. Tech., 8, 1055–1071, https://doi.org/10.5194/amt-8-1055-2015, https://doi.org/10.5194/amt-8-1055-2015, 2015
M. Lothon, F. Lohou, D. Pino, F. Couvreux, E. R. Pardyjak, J. Reuder, J. Vilà-Guerau de Arellano, P Durand, O. Hartogensis, D. Legain, P. Augustin, B. Gioli, D. H. Lenschow, I. Faloona, C. Yagüe, D. C. Alexander, W. M. Angevine, E Bargain, J. Barrié, E. Bazile, Y. Bezombes, E. Blay-Carreras, A. van de Boer, J. L. Boichard, A. Bourdon, A. Butet, B. Campistron, O. de Coster, J. Cuxart, A. Dabas, C. Darbieu, K. Deboudt, H. Delbarre, S. Derrien, P. Flament, M. Fourmentin, A. Garai, F. Gibert, A. Graf, J. Groebner, F. Guichard, M. A. Jiménez, M. Jonassen, A. van den Kroonenberg, V. Magliulo, S. Martin, D. Martinez, L. Mastrorillo, A. F. Moene, F. Molinos, E. Moulin, H. P. Pietersen, B. Piguet, E. Pique, C. Román-Cascón, C. Rufin-Soler, F. Saïd, M. Sastre-Marugán, Y. Seity, G. J. Steeneveld, P. Toscano, O. Traullé, D. Tzanos, S. Wacker, N. Wildmann, and A. Zaldei
Atmos. Chem. Phys., 14, 10931–10960, https://doi.org/10.5194/acp-14-10931-2014, https://doi.org/10.5194/acp-14-10931-2014, 2014
E. Blay-Carreras, E. R. Pardyjak, D. Pino, D. C. Alexander, F. Lohou, and M. Lothon
Atmos. Chem. Phys., 14, 9077–9085, https://doi.org/10.5194/acp-14-9077-2014, https://doi.org/10.5194/acp-14-9077-2014, 2014
E. Blay-Carreras, D. Pino, J. Vilà-Guerau de Arellano, A. van de Boer, O. De Coster, C. Darbieu, O. Hartogensis, F. Lohou, M. Lothon, and H. Pietersen
Atmos. Chem. Phys., 14, 4515–4530, https://doi.org/10.5194/acp-14-4515-2014, https://doi.org/10.5194/acp-14-4515-2014, 2014
F. Lohou, L. Kergoat, F. Guichard, A. Boone, B. Cappelaere, J.-M. Cohard, J. Demarty, S. Galle, M. Grippa, C. Peugeot, D. Ramier, C. M. Taylor, and F. Timouk
Atmos. Chem. Phys., 14, 3883–3898, https://doi.org/10.5194/acp-14-3883-2014, https://doi.org/10.5194/acp-14-3883-2014, 2014
L. Barthès and C. Mallet
Atmos. Meas. Tech., 6, 2181–2193, https://doi.org/10.5194/amt-6-2181-2013, https://doi.org/10.5194/amt-6-2181-2013, 2013
Related subject area
Atmospheric sciences
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
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
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
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.
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.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
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The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
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Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
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Short summary
This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
This study proposes using a statistical model to freeze errors due to differences in...
