Articles | Volume 10, issue 2
https://doi.org/10.5194/gmd-10-927-2017
© 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-10-927-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
23 Feb 2017
Model evaluation paper |
| 23 Feb 2017
Aerosol–radiation interaction modelling using online coupling between the WRF 3.7.1 meteorological model and the CHIMERE 2016 chemistry-transport model, through the OASIS3-MCT coupler
Régis Briant
CORRESPONDING AUTHOR
LMD, Laboratoire de météorologie dynamique, École Polytechnique, 91128 Palaiseau, France
Climatic Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, Boulevard Carl-Vogt 66, 1205 Geneva, Switzerland
Paolo Tuccella
LMD, Laboratoire de météorologie dynamique, École Polytechnique, 91128 Palaiseau, France
Adrien Deroubaix
LMD, Laboratoire de météorologie dynamique, École Polytechnique, 91128 Palaiseau, France
Dmitry Khvorostyanov
LMD, Laboratoire de météorologie dynamique, École Polytechnique, 91128 Palaiseau, France
Laurent Menut
LMD, Laboratoire de météorologie dynamique, École Polytechnique, 91128 Palaiseau, France
Sylvain Mailler
LMD, Laboratoire de météorologie dynamique, École Polytechnique, 91128 Palaiseau, France
Solène Turquety
LMD, Laboratoire de météorologie dynamique, École Polytechnique, 91128 Palaiseau, France
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Juan Cuesta, Lorenzo Costantino, Matthias Beekmann, Guillaume Siour, Laurent Menut, Bertrand Bessagnet, Tony C. Landi, Gaëlle Dufour, and Maxim Eremenko
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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
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Alexandre Siméon, Fabien Waquet, Jean-Christophe Péré, Fabrice Ducos, François Thieuleux, Fanny Peers, Solène Turquety, and Isabelle Chiapello
Atmos. Chem. Phys., 21, 17775–17805, https://doi.org/10.5194/acp-21-17775-2021, https://doi.org/10.5194/acp-21-17775-2021, 2021
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Laurent Menut, Bertrand Bessagnet, Régis Briant, Arineh Cholakian, Florian Couvidat, Sylvain Mailler, Romain Pennel, Guillaume Siour, Paolo Tuccella, Solène Turquety, and Myrto Valari
Geosci. Model Dev., 14, 6781–6811, https://doi.org/10.5194/gmd-14-6781-2021, https://doi.org/10.5194/gmd-14-6781-2021, 2021
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Thierno Doumbia, Claire Granier, Nellie Elguindi, Idir Bouarar, Sabine Darras, Guy Brasseur, Benjamin Gaubert, Yiming Liu, Xiaoqin Shi, Trissevgeni Stavrakou, Simone Tilmes, Forrest Lacey, Adrien Deroubaix, and Tao Wang
Earth Syst. Sci. Data, 13, 4191–4206, https://doi.org/10.5194/essd-13-4191-2021, https://doi.org/10.5194/essd-13-4191-2021, 2021
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Most countries around the world have implemented control measures to combat the spread of the COVID-19 pandemic, resulting in significant changes in economic and personal activities. We developed the CONFORM (COvid-19 adjustmeNt Factors fOR eMissions) dataset to account for changes in emissions during lockdowns. This dataset was created with the intention of being directly applicable to existing global and regional inventories used in chemical transport models.
Sanhita Ghosh, Shubha Verma, Jayanarayanan Kuttippurath, and Laurent Menut
Atmos. Chem. Phys., 21, 7671–7694, https://doi.org/10.5194/acp-21-7671-2021, https://doi.org/10.5194/acp-21-7671-2021, 2021
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Wintertime direct radiative perturbation due to black carbon (BC) aerosols was assessed over the Indo-Gangetic Plain with an efficiently modelled BC distribution. The atmospheric radiative warming due to BC was about 50–70 % larger than surface cooling. Compared to the atmosphere without BC, for which a net cooling at the top of the atmosphere was exhibited, enhanced atmospheric radiative warming by 2–3 times and a reduction in surface cooling by 10–20 % were found due to BC.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Mathieu Lachâtre
Geosci. Model Dev., 14, 2221–2233, https://doi.org/10.5194/gmd-14-2221-2021, https://doi.org/10.5194/gmd-14-2221-2021, 2021
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Representing the advection of thin polluted plumes in numerical models is a challenging task since these models usually tend to excessively diffuse these plumes in the vertical direction. This numerical diffusion process is the cause of major difficulties in representing such dense and thin polluted plumes in numerical models. We propose here, and test in an academic framework, a novel method to solve this problem through the use of an antidiffusive advection scheme in the vertical direction.
Rémy Lapere, Laurent Menut, Sylvain Mailler, and Nicolás Huneeus
Atmos. Chem. Phys., 21, 6431–6454, https://doi.org/10.5194/acp-21-6431-2021, https://doi.org/10.5194/acp-21-6431-2021, 2021
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Based on modeling, the transport dynamics of ozone and fine particles in central Chile are investigated. Santiago emissions are found to influence air quality along a 1000 km plume as far as Argentina and northern Chile. In turn, emissions outside the metropolis contribute significantly to its recorded particles concentration. Emissions of precursors from Santiago are found to lead to the formation of a persistent ozone bubble in altitude, a phenomenon which is described for the first time.
Bertrand Bessagnet, Laurent Menut, and Maxime Beauchamp
Geosci. Model Dev., 14, 91–106, https://doi.org/10.5194/gmd-14-91-2021, https://doi.org/10.5194/gmd-14-91-2021, 2021
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This paper presents a new interpolator useful for geophysics applications. It can explore N-dimensional meshes, grids or look-up tables. The code accepts irregular but structured grids. Written in Fortran, it is easy to implement in existing codes and very fast and portable. We have compared it with a Python library. Python is convenient but suffers from portability and is sometimes not optimized enough. As an application case, this method is applied to atmospheric sciences.
Mathieu Lachatre, Sylvain Mailler, Laurent Menut, Solène Turquety, Pasquale Sellitto, Henda Guermazi, Giuseppe Salerno, Tommaso Caltabiano, and Elisa Carboni
Geosci. Model Dev., 13, 5707–5723, https://doi.org/10.5194/gmd-13-5707-2020, https://doi.org/10.5194/gmd-13-5707-2020, 2020
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Excessive numerical diffusion is a major limitation in the representation of long-range transport in atmospheric models. In the present study, we focus on excessive diffusion in the vertical direction. We explore three possible ways of addressing this problem: increased vertical resolution, an advection scheme with anti-diffusive properties and more accurate representation of vertical wind. This study focused on a particular volcanic eruption event to improve atmospheric transport modeling.
Solène Turquety, Laurent Menut, Guillaume Siour, Sylvain Mailler, Juliette Hadji-Lazaro, Maya George, Cathy Clerbaux, Daniel Hurtmans, and Pierre-François Coheur
Geosci. Model Dev., 13, 2981–3009, https://doi.org/10.5194/gmd-13-2981-2020, https://doi.org/10.5194/gmd-13-2981-2020, 2020
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Biomass burning emissions are a major source of trace gases and aerosols that need to be accounted for in air quality assessment and forecasting. The APIFLAME model presented in this paper allows the calculation of these emissions based on merged satellite observations at hourly time steps and kilometer scales. Implementing emissions in a chemistry transport model allows realistic simulations of fire plumes as illustrated for wildfires in Portugal in August 2016 using the CHIMERE model.
Nicolas Da Silva, Sylvain Mailler, and Philippe Drobinski
Atmos. Chem. Phys., 20, 6207–6223, https://doi.org/10.5194/acp-20-6207-2020, https://doi.org/10.5194/acp-20-6207-2020, 2020
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Microphysical effects of aerosols were found to weaken precipitation in a Euro-Mediterranean area. The present numerical study quantifies the processes that may be involved through the use of the temperature–precipitation relationship. It shows larger aerosol effects at low temperatures. At these temperatures, the process that contributes most is the increase in atmospheric stability through an enhanced aerosol cooling effect in the lower troposphere compared to the upper troposphere.
Laurent Menut, Guillaume Siour, Bertrand Bessagnet, Florian Couvidat, Emilie Journet, Yves Balkanski, and Karine Desboeufs
Geosci. Model Dev., 13, 2051–2071, https://doi.org/10.5194/gmd-13-2051-2020, https://doi.org/10.5194/gmd-13-2051-2020, 2020
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Modelling of mineral dust is often done using one single mean species. In this study, differentiated mineral species with their chemical composition are implemented in the CHIMERE regional chemistry-transport model by using global databases. Simulations are carried out to quantify the realism and gain of such mineralogy.
Rémy Lapere, Laurent Menut, Sylvain Mailler, and Nicolás Huneeus
Atmos. Chem. Phys., 20, 4681–4694, https://doi.org/10.5194/acp-20-4681-2020, https://doi.org/10.5194/acp-20-4681-2020, 2020
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Based on measurements and modeling, this study shows that recent record-breaking peak events of fine particles in Santiago, Chile, can be traced back to massive barbecue cooking by its inhabitants during international soccer games. Decontamination plans in Santiago focus on decreasing emissions of pollutants from traffic, industry, and residential heating. This study implies that cultural habits such as barbecue cooking also need to be taken into account.
Laurent Menut, Paolo Tuccella, Cyrille Flamant, Adrien Deroubaix, and Marco Gaetani
Atmos. Chem. Phys., 19, 14657–14676, https://doi.org/10.5194/acp-19-14657-2019, https://doi.org/10.5194/acp-19-14657-2019, 2019
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Aerosol direct and indirect effects are studied over west Africa in the summer of 2016 using the coupled WRF-CHIMERE regional model including aerosol–cloud interaction parameterization. Sensitivity experiments are designed to gain insights into the impact of the aerosols dominating the atmospheric composition in southern west Africa. It is shown that the decrease of anthropogenic emissions along the coast has an impact on the mineral dust load over west Africa by increasing their emissions.
Henda Guermazi, Pasquale Sellitto, Juan Cuesta, Maxim Eremenko, Mathieu Lachatre, Sylvain Mailler, Elisa Carboni, Giuseppe Salerno, Tommaso Caltabiano, Laurent Menut, Mohamed Moncef Serbaji, Farhat Rekhiss, and Bernard Legras
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-341, https://doi.org/10.5194/amt-2019-341, 2019
Revised manuscript not accepted
Vanessa Brocchi, Gisèle Krysztofiak, Adrien Deroubaix, Greta Stratmann, Daniel Sauer, Hans Schlager, Konrad Deetz, Guillaume Dayma, Claude Robert, Stéphane Chevrier, and Valéry Catoire
Atmos. Chem. Phys., 19, 11401–11411, https://doi.org/10.5194/acp-19-11401-2019, https://doi.org/10.5194/acp-19-11401-2019, 2019
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This study reports the first flaring in situ measurements in southern West Africa. According to the measurements, oil rig flaring plumes in Ghana lead to increases in NO2 and aerosols but not always in CO and not in SO2. Flaring measurements can be reproduced using FLEXPART model, adjusting both the emission flux and the injection height. The DACCIWA satellite flaring inventory provides a reasonable estimate of flaring emission.
Marwa Majdi, Karine Sartelet, Grazia Maria Lanzafame, Florian Couvidat, Youngseob Kim, Mounir Chrit, and Solene Turquety
Atmos. Chem. Phys., 19, 5543–5569, https://doi.org/10.5194/acp-19-5543-2019, https://doi.org/10.5194/acp-19-5543-2019, 2019
Marwa Majdi, Solene Turquety, Karine Sartelet, Carole Legorgeu, Laurent Menut, and Youngseob Kim
Atmos. Chem. Phys., 19, 785–812, https://doi.org/10.5194/acp-19-785-2019, https://doi.org/10.5194/acp-19-785-2019, 2019
Adrien Deroubaix, Laurent Menut, Cyrille Flamant, Joel Brito, Cyrielle Denjean, Volker Dreiling, Andreas Fink, Corinne Jambert, Norbert Kalthoff, Peter Knippertz, Russ Ladkin, Sylvain Mailler, Marlon Maranan, Federica Pacifico, Bruno Piguet, Guillaume Siour, and Solène Turquety
Atmos. Chem. Phys., 19, 473–497, https://doi.org/10.5194/acp-19-473-2019, https://doi.org/10.5194/acp-19-473-2019, 2019
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This article presents a detailed analysis of anthropogenic and biomass burning pollutants over the Gulf of Guinea coastal region, using observations from the DACCIWA field campaign and modeling. The novelty is that we focus on how these two pollution sources are mixed and transported further inland. We show that during the day pollutants are accumulated along the coastline and transported northward as soon as the daytime convection in the atmospheric boundary layer ceases (16:00 UTC).
Cyrille Flamant, Adrien Deroubaix, Patrick Chazette, Joel Brito, Marco Gaetani, Peter Knippertz, Andreas H. Fink, Gaëlle de Coetlogon, Laurent Menut, Aurélie Colomb, Cyrielle Denjean, Rémi Meynadier, Philip Rosenberg, Regis Dupuy, Pamela Dominutti, Jonathan Duplissy, Thierry Bourrianne, Alfons Schwarzenboeck, Michel Ramonet, and Julien Totems
Atmos. Chem. Phys., 18, 12363–12389, https://doi.org/10.5194/acp-18-12363-2018, https://doi.org/10.5194/acp-18-12363-2018, 2018
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This work sheds light on the complex mechanisms by which coastal shallow circulations distribute atmospheric pollutants over the densely populated southern West African region. Pollutants of concern are anthropogenic emissions from coastal cities, as well as biomass burning aerosol and dust associated with long-range transport. The complex vertical distribution of aerosols over coastal southern West Africa is investigated using airborne observations and numerical simulations.
Angela Benedetti, Jeffrey S. Reid, Peter Knippertz, John H. Marsham, Francesca Di Giuseppe, Samuel Rémy, Sara Basart, Olivier Boucher, Ian M. Brooks, Laurent Menut, Lucia Mona, Paolo Laj, Gelsomina Pappalardo, Alfred Wiedensohler, Alexander Baklanov, Malcolm Brooks, Peter R. Colarco, Emilio Cuevas, Arlindo da Silva, Jeronimo Escribano, Johannes Flemming, Nicolas Huneeus, Oriol Jorba, Stelios Kazadzis, Stefan Kinne, Thomas Popp, Patricia K. Quinn, Thomas T. Sekiyama, Taichu Tanaka, and Enric Terradellas
Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, https://doi.org/10.5194/acp-18-10615-2018, 2018
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Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation authorities, solar energy plant managers, climate service providers, and health professionals. This paper describes the advances in the field and sets out requirements for observations for the sustainability of these activities.
Alessandro Anav, Chiara Proietti, Laurent Menut, Stefano Carnicelli, Alessandra De Marco, and Elena Paoletti
Atmos. Chem. Phys., 18, 5747–5763, https://doi.org/10.5194/acp-18-5747-2018, https://doi.org/10.5194/acp-18-5747-2018, 2018
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Soil moisture and water stress play a pivotal role in regulating stomatal behaviour of plants; however, the role of water availability is often neglected in atmospheric chemistry modelling studies.
We show how dry deposition significantly declines when soil moisture is used to regulate the stomatal opening, mainly in semi-arid environments. Despite the fact that dry deposition occurs from the top of canopy to ground level, it affects the concentration of gases remaining in the lower atmosphere.
Nicolas Da Silva, Sylvain Mailler, and Philippe Drobinski
Ann. Geophys., 36, 321–335, https://doi.org/10.5194/angeo-36-321-2018, https://doi.org/10.5194/angeo-36-321-2018, 2018
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Aerosols affect atmospheric dynamics because they absorb radiations (direct effects) and because they act as cloud condensation nuclei (indirect effects). The present study shows that aerosol indirect effects reduce summer precipitation in the Euro-Mediterranean region through reduction of the radiative heating of the surface and corresponding reductions of surface temperature, resulting in increased atmospheric stability in the presence of high aerosol loads.
Laurent Menut, Cyrille Flamant, Solène Turquety, Adrien Deroubaix, Patrick Chazette, and Rémi Meynadier
Atmos. Chem. Phys., 18, 2687–2707, https://doi.org/10.5194/acp-18-2687-2018, https://doi.org/10.5194/acp-18-2687-2018, 2018
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During the DACCIWA project, the tropospheric chemical composition in large cities along the Gulf of Guinea is modelled using WRF and CHIMERE, with and without biomass burning emissions. The difference shows the net impact of fires on air quality in Lagos and Abidjan.
Joel Brito, Evelyn Freney, Pamela Dominutti, Agnes Borbon, Sophie L. Haslett, Anneke M. Batenburg, Aurelie Colomb, Regis Dupuy, Cyrielle Denjean, Frederic Burnet, Thierry Bourriane, Adrien Deroubaix, Karine Sellegri, Stephan Borrmann, Hugh Coe, Cyrille Flamant, Peter Knippertz, and Alfons Schwarzenboeck
Atmos. Chem. Phys., 18, 757–772, https://doi.org/10.5194/acp-18-757-2018, https://doi.org/10.5194/acp-18-757-2018, 2018
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This work focuses on sources of submicron aerosol particles over southern West Africa (SWA). Results have shown that isoprene, a gas-phase compound of biogenic origin, is responsible for roughly 25 % of the organic aerosol (OA) loading, under most background or urban plumes alike. This fraction represents a lower estimate from the biogenic contribution in this fairly polluted region. This work sheds light upon the role of anthropogenic and biogenic emissions on the pollution burden over SWA.
Adrien Deroubaix, Cyrille Flamant, Laurent Menut, Guillaume Siour, Sylvain Mailler, Solène Turquety, Régis Briant, Dmitry Khvorostyanov, and Suzanne Crumeyrolle
Atmos. Chem. Phys., 18, 445–465, https://doi.org/10.5194/acp-18-445-2018, https://doi.org/10.5194/acp-18-445-2018, 2018
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CO and PM2.5 are analyzed over the Guinean Gulf coastal region during the beginning of the 2006 West African monsoon. A biomass burning plume from Central Africa is observed since June at the Guinean coast. In June, the modeled anthropogenic PM2.5 concentrations are higher than in May or July. An important part of the pollution emitted along the coastline is transported to the north at night within the surface layer and within the nocturnal low-level jet.
Florian Couvidat, Bertrand Bessagnet, Marta Garcia-Vivanco, Elsa Real, Laurent Menut, and Augustin Colette
Geosci. Model Dev., 11, 165–194, https://doi.org/10.5194/gmd-11-165-2018, https://doi.org/10.5194/gmd-11-165-2018, 2018
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This paper includes the development of a new aerosol module in the air quality model CHIMERE to improve particulate matter (PM) simulation. The results of the model are compared to numerous measurements over Europe to evaluate the strengths and weaknesses of the model.
Bastien Sauvage, Alain Fontaine, Sabine Eckhardt, Antoine Auby, Damien Boulanger, Hervé Petetin, Ronan Paugam, Gilles Athier, Jean-Marc Cousin, Sabine Darras, Philippe Nédélec, Andreas Stohl, Solène Turquety, Jean-Pierre Cammas, and Valérie Thouret
Atmos. Chem. Phys., 17, 15271–15292, https://doi.org/10.5194/acp-17-15271-2017, https://doi.org/10.5194/acp-17-15271-2017, 2017
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We provide the scientific community with a SOFT-IO tool based on the coupling of Lagrangian modeling with emission inventories and aircraft CO measurements, which is able to calculate the contribution of the sources and geographical origins of CO measurements, with good performances. Calculated CO added-value products will help scientists in interpreting large IAGOS CO data set. SOFT-IO could further be applied to other CO data sets or used to help validate emission inventories.
Peter Knippertz, Andreas H. Fink, Adrien Deroubaix, Eleanor Morris, Flore Tocquer, Mat J. Evans, Cyrille Flamant, Marco Gaetani, Christophe Lavaysse, Celine Mari, John H. Marsham, Rémi Meynadier, Abalo Affo-Dogo, Titike Bahaga, Fabien Brosse, Konrad Deetz, Ridha Guebsi, Issaou Latifou, Marlon Maranan, Philip D. Rosenberg, and Andreas Schlueter
Atmos. Chem. Phys., 17, 10893–10918, https://doi.org/10.5194/acp-17-10893-2017, https://doi.org/10.5194/acp-17-10893-2017, 2017
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In June–July 2016 DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa), a large, EU-funded European–African project, organised an international field campaign in densely populated southern West Africa, including measurements from ground sites, research aircraft, weather balloons and urban sites. This paper gives an overview of the atmospheric evolution during this period focusing on meteorological (precipitation, cloudiness, winds) and composition (gases, particles) aspects.
Sylvain Mailler, Laurent Menut, Dmitry Khvorostyanov, Myrto Valari, Florian Couvidat, Guillaume Siour, Solène Turquety, Régis Briant, Paolo Tuccella, Bertrand Bessagnet, Augustin Colette, Laurent Létinois, Kostantinos Markakis, and Frédérik Meleux
Geosci. Model Dev., 10, 2397–2423, https://doi.org/10.5194/gmd-10-2397-2017, https://doi.org/10.5194/gmd-10-2397-2017, 2017
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CHIMERE is a chemistry-transport model initially designed for box-modelling of the regional atmospheric composition. In the recent years, CHIMERE has been extended to be able to model atmospheric composition at all scales from urban to hemispheric scale, which implied major changes on the coordinate systems as well as on physical processes. This study describes how and why these changes have been brought to the model, largely increasing the range of its possible use.
Laurent Menut, Sylvain Mailler, Bertrand Bessagnet, Guillaume Siour, Augustin Colette, Florian Couvidat, and Frédérik Meleux
Geosci. Model Dev., 10, 1199–1208, https://doi.org/10.5194/gmd-10-1199-2017, https://doi.org/10.5194/gmd-10-1199-2017, 2017
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A simple and complementary model evaluation technique for regional chemistry transport is discussed. The methodology is based on the concept that we can learn about model performance by comparing the simulation results with observational data available for time periods other than the period originally targeted.
Laurent Menut, Guillaume Siour, Sylvain Mailler, Florian Couvidat, and Bertrand Bessagnet
Atmos. Chem. Phys., 16, 12961–12982, https://doi.org/10.5194/acp-16-12961-2016, https://doi.org/10.5194/acp-16-12961-2016, 2016
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The aerosol is modelled during the summer 2013 with the WRF and CHIMERE models and over a large area encompassing Africa, Mediterranean sea and west Europe. The modelled aerosol is compared to available measurements such as the AERONET and EMEP networks. The model ability to estimate the aerosol speciation and size distribution is quantified.
Bertrand Bessagnet, Guido Pirovano, Mihaela Mircea, Cornelius Cuvelier, Armin Aulinger, Giuseppe Calori, Giancarlo Ciarelli, Astrid Manders, Rainer Stern, Svetlana Tsyro, Marta García Vivanco, Philippe Thunis, Maria-Teresa Pay, Augustin Colette, Florian Couvidat, Frédérik Meleux, Laurence Rouïl, Anthony Ung, Sebnem Aksoyoglu, José María Baldasano, Johannes Bieser, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Sandro Finardi, Richard Kranenburg, Camillo Silibello, Claudio Carnevale, Wenche Aas, Jean-Charles Dupont, Hilde Fagerli, Lucia Gonzalez, Laurent Menut, André S. H. Prévôt, Pete Roberts, and Les White
Atmos. Chem. Phys., 16, 12667–12701, https://doi.org/10.5194/acp-16-12667-2016, https://doi.org/10.5194/acp-16-12667-2016, 2016
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The EURODELTA III exercise allows a very comprehensive intercomparison and evaluation of air quality models' performance. On average, the models provide a rather good picture of the particulate matter (PM) concentrations over Europe even if the highest concentrations are underestimated. The meteorology is responsible for model discrepancies, while the lack of emissions, particularly in winter, is mentioned as the main reason for the underestimations of PM.
Vincent E. P. Lemaire, Augustin Colette, and Laurent Menut
Atmos. Chem. Phys., 16, 2559–2574, https://doi.org/10.5194/acp-16-2559-2016, https://doi.org/10.5194/acp-16-2559-2016, 2016
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Because of its sensitivity to unfavorable weather patterns, air pollution is sensitive to climate change. Its impact is typically assessed using deterministic chemistry-transport models forced by an ensemble of climate projection. Because of the high computational cost of such initiative, elaborated techniques are required to optimize the exploration of ensemble of future projections. We develop such a technique, which also allows quantifying uncertainties in climate and air quality projections.
S. Mailler, L. Menut, A. G. di Sarra, S. Becagli, T. Di Iorio, B. Bessagnet, R. Briant, P. Formenti, J.-F. Doussin, J. L. Gómez-Amo, M. Mallet, G. Rea, G. Siour, D. M. Sferlazzo, R. Traversi, R. Udisti, and S. Turquety
Atmos. Chem. Phys., 16, 1219–1244, https://doi.org/10.5194/acp-16-1219-2016, https://doi.org/10.5194/acp-16-1219-2016, 2016
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We studied the impact of aerosols on tropospheric photolysis rates at Lampedusa during the CharMEx/ADRIMED campaign in June 2013. It is shown by using the CHIMERE chemistry-transport model (CTM) as well as in situ and remote-sensing measurements that taking into account the radiative effect of the tropospheric aerosols improves the ability of the model to reproduce the observed photolysis rates. It is hence important for CTMs to include the radiative effect of aerosols on photochemistry.
M. Mallet, F. Dulac, P. Formenti, P. Nabat, J. Sciare, G. Roberts, J. Pelon, G. Ancellet, D. Tanré, F. Parol, C. Denjean, G. Brogniez, A. di Sarra, L. Alados-Arboledas, J. Arndt, F. Auriol, L. Blarel, T. Bourrianne, P. Chazette, S. Chevaillier, M. Claeys, B. D'Anna, Y. Derimian, K. Desboeufs, T. Di Iorio, J.-F. Doussin, P. Durand, A. Féron, E. Freney, C. Gaimoz, P. Goloub, J. L. Gómez-Amo, M. J. Granados-Muñoz, N. Grand, E. Hamonou, I. Jankowiak, M. Jeannot, J.-F. Léon, M. Maillé, S. Mailler, D. Meloni, L. Menut, G. Momboisse, J. Nicolas, T. Podvin, V. Pont, G. Rea, J.-B. Renard, L. Roblou, K. Schepanski, A. Schwarzenboeck, K. Sellegri, M. Sicard, F. Solmon, S. Somot, B Torres, J. Totems, S. Triquet, N. Verdier, C. Verwaerde, F. Waquet, J. Wenger, and P. Zapf
Atmos. Chem. Phys., 16, 455–504, https://doi.org/10.5194/acp-16-455-2016, https://doi.org/10.5194/acp-16-455-2016, 2016
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The aim of this article is to present an experimental campaign over the Mediterranean focused on aerosol-radiation measurements and modeling. Results indicate an important atmospheric loading associated with a moderate absorbing ability of mineral dust. Observations suggest a complex vertical structure and size distributions characterized by large aerosols within dust plumes. The radiative effect is highly variable, with negative forcing over the Mediterranean and positive over northern Africa.
C. Hernandez, C. Keribin, P. Drobinski, and S. Turquety
Ann. Geophys., 33, 1495–1506, https://doi.org/10.5194/angeo-33-1495-2015, https://doi.org/10.5194/angeo-33-1495-2015, 2015
V. Marécal, V.-H. Peuch, C. Andersson, S. Andersson, J. Arteta, M. Beekmann, A. Benedictow, R. Bergström, B. Bessagnet, A. Cansado, F. Chéroux, A. Colette, A. Coman, R. L. Curier, H. A. C. Denier van der Gon, A. Drouin, H. Elbern, E. Emili, R. J. Engelen, H. J. Eskes, G. Foret, E. Friese, M. Gauss, C. Giannaros, J. Guth, M. Joly, E. Jaumouillé, B. Josse, N. Kadygrov, J. W. Kaiser, K. Krajsek, J. Kuenen, U. Kumar, N. Liora, E. Lopez, L. Malherbe, I. Martinez, D. Melas, F. Meleux, L. Menut, P. Moinat, T. Morales, J. Parmentier, A. Piacentini, M. Plu, A. Poupkou, S. Queguiner, L. Robertson, L. Rouïl, M. Schaap, A. Segers, M. Sofiev, L. Tarasson, M. Thomas, R. Timmermans, Á. Valdebenito, P. van Velthoven, R. van Versendaal, J. Vira, and A. Ung
Geosci. Model Dev., 8, 2777–2813, https://doi.org/10.5194/gmd-8-2777-2015, https://doi.org/10.5194/gmd-8-2777-2015, 2015
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This paper describes the air quality forecasting system over Europe put in place in the Monitoring Atmospheric Composition and Climate projects. It provides daily and 4-day forecasts and analyses for the previous day for major gas and particulate pollutants and their main precursors. These products are based on a multi-model approach using seven state-of-the-art models developed in Europe. An evaluation of the performance of the system is discussed in the paper.
C. Hernandez, P. Drobinski, and S. Turquety
Ann. Geophys., 33, 931–939, https://doi.org/10.5194/angeo-33-931-2015, https://doi.org/10.5194/angeo-33-931-2015, 2015
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, https://doi.org/10.5194/acp-15-8115-2015, 2015
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The paper presents the first ensemble modelling experiment for forecasting the atmospheric dispersion of birch pollen in Europe. The study included 7 models of MACC-ENS tested over the season of 2010 and applied for 2013 in forecasting and reanalysis modes. The results were compared with observations in 11 countries, members of European Aeroallergen Network. The models successfully reproduced the timing of the unusually late season of 2013 but had more difficulties with absolute concentration.
G. Rea, S. Turquety, L. Menut, R. Briant, S. Mailler, and G. Siour
Atmos. Chem. Phys., 15, 8013–8036, https://doi.org/10.5194/acp-15-8013-2015, https://doi.org/10.5194/acp-15-8013-2015, 2015
L. Menut, G. Rea, S. Mailler, D. Khvorostyanov, and S. Turquety
Atmos. Chem. Phys., 15, 7897–7911, https://doi.org/10.5194/acp-15-7897-2015, https://doi.org/10.5194/acp-15-7897-2015, 2015
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The atmospheric composition was extensively studied in the European Mediterranean region and during summer 2013 within the framework of the ADRIMED project. During the campaign experiment, the WRF and CHIMERE models were used in forecast mode in order to help scientists to decide whether intensive observation periods should be triggered or not. This study quantifies the origin of the forecast error by comparing several forecast leads to the corresponding measurements.
C. Hernandez, P. Drobinski, S. Turquety, and J.-L. Dupuy
Nat. Hazards Earth Syst. Sci., 15, 1331–1341, https://doi.org/10.5194/nhess-15-1331-2015, https://doi.org/10.5194/nhess-15-1331-2015, 2015
F. Hourdin, M. Gueye, B. Diallo, J.-L. Dufresne, J. Escribano, L. Menut, B. Marticoréna, G. Siour, and F. Guichard
Atmos. Chem. Phys., 15, 6775–6788, https://doi.org/10.5194/acp-15-6775-2015, https://doi.org/10.5194/acp-15-6775-2015, 2015
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New parameterizations of the convective boundary layer are used to better represent the diurnal cycle of near-surface wind over Sahara and Sahel in a climate model and the associated emission of dust.
L. K. Emmons, S. R. Arnold, S. A. Monks, V. Huijnen, S. Tilmes, K. S. Law, J. L. Thomas, J.-C. Raut, I. Bouarar, S. Turquety, Y. Long, B. Duncan, S. Steenrod, S. Strode, J. Flemming, J. Mao, J. Langner, A. M. Thompson, D. Tarasick, E. C. Apel, D. R. Blake, R. C. Cohen, J. Dibb, G. S. Diskin, A. Fried, S. R. Hall, L. G. Huey, A. J. Weinheimer, A. Wisthaler, T. Mikoviny, J. Nowak, J. Peischl, J. M. Roberts, T. Ryerson, C. Warneke, and D. Helmig
Atmos. Chem. Phys., 15, 6721–6744, https://doi.org/10.5194/acp-15-6721-2015, https://doi.org/10.5194/acp-15-6721-2015, 2015
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Eleven 3-D tropospheric chemistry models have been compared and evaluated with observations in the Arctic during the International Polar Year (IPY 2008). Large differences are seen among the models, particularly related to the model chemistry of volatile organic compounds (VOCs) and reactive nitrogen (NOx, PAN, HNO3) partitioning. Consistency among the models in the underestimation of CO, ethane and propane indicates the emission inventory is too low for these compounds.
L. Menut, S. Mailler, G. Siour, B. Bessagnet, S. Turquety, G. Rea, R. Briant, M. Mallet, J. Sciare, P. Formenti, and F. Meleux
Atmos. Chem. Phys., 15, 6159–6182, https://doi.org/10.5194/acp-15-6159-2015, https://doi.org/10.5194/acp-15-6159-2015, 2015
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The ozone and aerosol concentration variability is studied over the Euro-Mediterranean area during the months of June and July 2013 and in the framework of the ADRIMED project. A first analysis is performed using meteorological variables, ozone and aerosol concentrations using routine network station, satellite and specific ADRIMED project airborne measurements. This analysis is complemented by modeling using the WRF and CHIMERE regional models.
S. R. Arnold, L. K. Emmons, S. A. Monks, K. S. Law, D. A. Ridley, S. Turquety, S. Tilmes, J. L. Thomas, I. Bouarar, J. Flemming, V. Huijnen, J. Mao, B. N. Duncan, S. Steenrod, Y. Yoshida, J. Langner, and Y. Long
Atmos. Chem. Phys., 15, 6047–6068, https://doi.org/10.5194/acp-15-6047-2015, https://doi.org/10.5194/acp-15-6047-2015, 2015
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The extent to which forest fires produce the air pollutant and greenhouse gas ozone (O3) in the atmosphere at high latitudes in not well understood. We have compared how fire emissions produce O3 and its precursors in several models of atmospheric chemistry. We find enhancements in O3 in air dominated by fires in all models, which increase on average as fire emissions age. We also find that in situ O3 production in the Arctic is sensitive to details of organic chemistry and vertical lifting.
S. A. Monks, S. R. Arnold, L. K. Emmons, K. S. Law, S. Turquety, B. N. Duncan, J. Flemming, V. Huijnen, S. Tilmes, J. Langner, J. Mao, Y. Long, J. L. Thomas, S. D. Steenrod, J. C. Raut, C. Wilson, M. P. Chipperfield, G. S. Diskin, A. Weinheimer, H. Schlager, and G. Ancellet
Atmos. Chem. Phys., 15, 3575–3603, https://doi.org/10.5194/acp-15-3575-2015, https://doi.org/10.5194/acp-15-3575-2015, 2015
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Multi-model simulations of Arctic CO, O3 and OH are evaluated using observations. Models show highly variable concentrations but the relative importance of emission regions and types is robust across the models, demonstrating the importance of biomass burning as a source. Idealised tracer experiments suggest that some of the model spread is due to variations in simulated transport from Europe in winter and from Asia throughout the year.
K. Haustein, R. Washington, J. King, G. Wiggs, D. S. G. Thomas, F. D. Eckardt, R. G. Bryant, and L. Menut
Geosci. Model Dev., 8, 341–362, https://doi.org/10.5194/gmd-8-341-2015, https://doi.org/10.5194/gmd-8-341-2015, 2015
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In this paper, the performance of three commonly used dust emissions schemes is investigated using a box model environment and observational data obtained in Botswana (Sua Pan). The results suggest that all schemes fail to reproduce the observed horizontal dust flux properly. They overestimate its magnitude by several orders of magnitude. The key parameter for this mismatch is the surface crusting which limits the availability of erosive material, even at higher wind speeds.
E. Terrenoire, B. Bessagnet, L. Rouïl, F. Tognet, G. Pirovano, L. Létinois, M. Beauchamp, A. Colette, P. Thunis, M. Amann, and L. Menut
Geosci. Model Dev., 8, 21–42, https://doi.org/10.5194/gmd-8-21-2015, https://doi.org/10.5194/gmd-8-21-2015, 2015
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The model reproduces the temporal variability of NO2, O3, PM10, PM2.5 better at rural than urban background stations.
The fractional biases show that the model performs slightly better at RB sites than at UB sites for NO2, O3 and PM10.
At UB sites, CHIMERE reproduces PM2.5 better than PM10.
This is primarily the result of an underestimation of coarse particulate matter (PM) associated with uncertainties on SOA chemistry and their precursor emissions, dust and sea salt.
L. Menut, S. Mailler, G. Siour, B. Bessagnet, S. Turquety, G. Rea, R. Briant, M. Mallet, J. Sciare, and P. Formenti
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-23075-2014, https://doi.org/10.5194/acpd-14-23075-2014, 2014
Revised manuscript not accepted
R. Briant, L. Menut, G. Siour, and C. Prigent
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-3441-2014, https://doi.org/10.5194/gmdd-7-3441-2014, 2014
Revised manuscript not accepted
L. Menut, R. Vautard, A. Colette, D. Khvorostyanov, A. Potier, L. Hamaoui-Laguel, N. Viovy, and M. Thibaudon
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-10891-2014, https://doi.org/10.5194/acpd-14-10891-2014, 2014
Revised manuscript not accepted
P. Yiou, M. Boichu, R. Vautard, M. Vrac, S. Jourdain, E. Garnier, F. Fluteau, and L. Menut
Clim. Past, 10, 797–809, https://doi.org/10.5194/cp-10-797-2014, https://doi.org/10.5194/cp-10-797-2014, 2014
S. Turquety, L. Menut, B. Bessagnet, A. Anav, N. Viovy, F. Maignan, and M. Wooster
Geosci. Model Dev., 7, 587–612, https://doi.org/10.5194/gmd-7-587-2014, https://doi.org/10.5194/gmd-7-587-2014, 2014
J. C. Péré, B. Bessagnet, M. Mallet, F. Waquet, I. Chiapello, F. Minvielle, V. Pont, and L. Menut
Atmos. Chem. Phys., 14, 1999–2013, https://doi.org/10.5194/acp-14-1999-2014, https://doi.org/10.5194/acp-14-1999-2014, 2014
M. Boichu, L. Menut, D. Khvorostyanov, L. Clarisse, C. Clerbaux, S. Turquety, and P.-F. Coheur
Atmos. Chem. Phys., 13, 8569–8584, https://doi.org/10.5194/acp-13-8569-2013, https://doi.org/10.5194/acp-13-8569-2013, 2013
A. Colette, B. Bessagnet, R. Vautard, S. Szopa, S. Rao, S. Schucht, Z. Klimont, L. Menut, G. Clain, F. Meleux, G. Curci, and L. Rouïl
Atmos. Chem. Phys., 13, 7451–7471, https://doi.org/10.5194/acp-13-7451-2013, https://doi.org/10.5194/acp-13-7451-2013, 2013
L. Menut, B. Bessagnet, D. Khvorostyanov, M. Beekmann, N. Blond, A. Colette, I. Coll, G. Curci, G. Foret, A. Hodzic, S. Mailler, F. Meleux, J.-L. Monge, I. Pison, G. Siour, S. Turquety, M. Valari, R. Vautard, and M. G. Vivanco
Geosci. Model Dev., 6, 981–1028, https://doi.org/10.5194/gmd-6-981-2013, https://doi.org/10.5194/gmd-6-981-2013, 2013
S. Mailler, D. Khvorostyanov, and L. Menut
Atmos. Chem. Phys., 13, 5987–5998, https://doi.org/10.5194/acp-13-5987-2013, https://doi.org/10.5194/acp-13-5987-2013, 2013
Y. R'Honi, L. Clarisse, C. Clerbaux, D. Hurtmans, V. Duflot, S. Turquety, Y. Ngadi, and P.-F. Coheur
Atmos. Chem. Phys., 13, 4171–4181, https://doi.org/10.5194/acp-13-4171-2013, https://doi.org/10.5194/acp-13-4171-2013, 2013
R. Briant, C. Seigneur, M. Gadrat, and C. Bugajny
Geosci. Model Dev., 6, 445–456, https://doi.org/10.5194/gmd-6-445-2013, https://doi.org/10.5194/gmd-6-445-2013, 2013
S. Stromatas, S. Turquety, L. Menut, H. Chepfer, J. C. Péré, G. Cesana, and B. Bessagnet
Geosci. Model Dev., 5, 1543–1564, https://doi.org/10.5194/gmd-5-1543-2012, https://doi.org/10.5194/gmd-5-1543-2012, 2012
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
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
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
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.
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.
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Short summary
This paper presents the coupling of the CHIMERE chemistry-transport model with the WRF meteorological model, using the OASIS3-MCT coupler. WRF meteorological fields along with CHIMERE aerosol optical properties are exchanged through the coupler at a high frequency in order to model the aerosol direct and semi-direct effects.
This paper presents the coupling of the CHIMERE chemistry-transport model with the WRF...
