Articles | Volume 12, issue 6
https://doi.org/10.5194/gmd-12-2607-2019
© Author(s) 2019. 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-12-2607-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
01 Jul 2019
Development and technical paper |
| 01 Jul 2019
| 01 Jul 2019
Implementation of an immersed boundary method in the Meso-NH v5.2 model: applications to an idealized urban environment
Franck Auguste
CORRESPONDING AUTHOR
Centre Européen de Recherche Avancée et de Formation en Calcul Scientifique (CERFACS), CECI-CNRS, Toulouse, France
Géraldine Réa
Centre Européen de Recherche Avancée et de Formation en Calcul Scientifique (CERFACS), CECI-CNRS, Toulouse, France
Roberto Paoli
Computational Science Division and Leadership Computing Facility, Argonne National Laboratory, Lemont, IL, USA
Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, USA
Christine Lac
Centre National de Recherches Météorologiques (CNRM), Météo-France-CNRS, Toulouse, France
Valery Masson
Centre National de Recherches Météorologiques (CNRM), Météo-France-CNRS, Toulouse, France
Daniel Cariolle
Centre Européen de Recherche Avancée et de Formation en Calcul Scientifique (CERFACS), CECI-CNRS, Toulouse, France
Centre National de Recherches Météorologiques (CNRM), Météo-France-CNRS, Toulouse, France
Related authors
No articles found.
Théophane Costabloz, Frédéric Burnet, Christine Lac, Pauline Martinet, Julien Delanoë, Susana Jorquera, and Maroua Fathalli
Atmos. Chem. Phys., 25, 6539–6573, https://doi.org/10.5194/acp-25-6539-2025, https://doi.org/10.5194/acp-25-6539-2025, 2025
Short summary
Short summary
This study documents vertical profiles of liquid water content (LWC) in fogs from in situ measurements collected during the SOFOG3D field campaign in 2019–2020. The analysis of 140 vertical profiles reveals a reverse trend in LWC, maximum values at ground decreasing with height, during stable conditions in optically thin fogs, evolving towards quasi-adiabatic characteristics when fogs become thick. These results offer new perspectives for better constraining fog numerical simulations.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
Short summary
Short summary
In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Adrien Marcel, Sébastien Riette, Didier Ricard, and Christine Lac
EGUsphere, https://doi.org/10.5194/egusphere-2025-2504, https://doi.org/10.5194/egusphere-2025-2504, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This paper provides substantial consistent updates to the atmospheric boundary layer schemes of the AROME model, yet they can be used for both forecasting and climate modelling. The study employs a single-column model versus large eddy simulations comparison and uses a machine learning tool to calibrate parameterizations. The model's ability to simulate shallow clouds has been enhanced, especially for shallow precipitating cumulus and stratocumulus clouds.
William Morrison, Dana Looschelders, Jonnathan Céspedes, Bernie Claxton, Marc-Antoine Drouin, Jean-Charles Dupont, Aurélien Faucheux, Martial Haeffelin, Christopher C. Holst, Simone Kotthaus, Valéry Masson, James McGregor, Jeremy Price, Matthias Zeeman, Sue Grimmond, and Andreas Christen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-167, https://doi.org/10.5194/essd-2025-167, 2025
Preprint under review for ESSD
Short summary
Short summary
We conducted research using sophisticated wind sensors to better understand wind patterns in Paris. By installing these sensors across the city, we gathered detailed data on wind speeds and directions from 2022 to 2024. This information helps improve weather and climate models, making them more accurate for city environments. Our findings offer valuable insights for scientists studying urban air and weather, improving predictions and understanding of city-scale atmospheric processes.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
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
Short summary
Short summary
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.
Martial Haeffelin, Jean-François Ribaud, Jonnathan Céspedes, Jean-Charles Dupont, Aude Lemonsu, Valéry Masson, Tim Nagel, and Simone Kotthaus
Atmos. Chem. Phys., 24, 14101–14122, https://doi.org/10.5194/acp-24-14101-2024, https://doi.org/10.5194/acp-24-14101-2024, 2024
Short summary
Short summary
This study highlights how the state of the urban atmospheric boundary layer impacts urban park cooling effect intensity at night. Under summertime heat wave conditions, the urban atmosphere becomes stable at night, which inhibits turbulent motions. Under those specific conditions, urban parks and woods cool much more efficiently than the surrounding built-up neighbourhoods in the evening and through the night, providing cooler air temperatures by 4 to 6° C depending on park size.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
Short summary
Short summary
With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Erwan Jézéquel, Frédéric Blondel, and Valéry Masson
Wind Energ. Sci., 9, 97–117, https://doi.org/10.5194/wes-9-97-2024, https://doi.org/10.5194/wes-9-97-2024, 2024
Short summary
Short summary
Wind turbine wakes affect the production and lifecycle of downstream turbines. They can be predicted with the dynamic wake meandering (DWM) method. In this paper, the authors break down the velocity and turbulence in the wake of a wind turbine into several terms. They show that it is implicitly assumed in the DWM that some of these terms are neglected. With high-fidelity simulations, it is shown that this can lead to some errors, in particular for the maximum turbulence added by the wake.
Erwan Jézéquel, Frédéric Blondel, and Valéry Masson
Wind Energ. Sci., 9, 119–139, https://doi.org/10.5194/wes-9-119-2024, https://doi.org/10.5194/wes-9-119-2024, 2024
Short summary
Short summary
Analytical models allow us to quickly compute the decreased power output and lifetime induced by wakes in a wind farm. This is achieved by evaluating the modified velocity and turbulence in the wake. In this work, we present a new model based on the velocity and turbulence breakdowns presented in Part 1. This new model is physically based, allows us to compute the whole turbulence profile (rather than the maximum value) and is built to take atmospheric stability into account.
Cheikh Dione, Martial Haeffelin, Frédéric Burnet, Christine Lac, Guylaine Canut, Julien Delanoë, Jean-Charles Dupont, Susana Jorquera, Pauline Martinet, Jean-François Ribaud, and Felipe Toledo
Atmos. Chem. Phys., 23, 15711–15731, https://doi.org/10.5194/acp-23-15711-2023, https://doi.org/10.5194/acp-23-15711-2023, 2023
Short summary
Short summary
This paper documents the role of thermodynamics and turbulence in the fog life cycle over southwestern France. It is based on a unique dataset collected during the SOFOG3D field campaign in autumn and winter 2019–2020. The paper gives a threshold for turbulence driving the different phases of the fog life cycle and the role of advection in the night-time dissipation of fog. The results can be operationalised to nowcast fog and improve short-range forecasts in numerical weather prediction models.
Maxime Perini, Laurent Terray, Daniel Cariolle, Saloua Peatier, and Marie-Pierre Moine
EGUsphere, https://doi.org/10.5194/egusphere-2023-2478, https://doi.org/10.5194/egusphere-2023-2478, 2023
Preprint archived
Short summary
Short summary
Uncertainty about aviation radiative forcing is essentially due to uncertainties about non-CO2 forcing, especially for condensation trails (contrails). This study uses a new parameterization for ice-supersaturation and additional contrail coverage in the CNRM-CM6-1 atmospheric component to estimate contrail radiative forcing for the year 2000. The range of contrail radiative forcing due to parametric uncertainty is analyzed. Our contrail radiative forcing best estimate is 56 (38−70) mW.m-2.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
Short summary
Short summary
We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Jérémy Bernard, Erwan Bocher, Elisabeth Le Saux Wiederhold, François Leconte, and Valéry Masson
Geosci. Model Dev., 15, 7505–7532, https://doi.org/10.5194/gmd-15-7505-2022, https://doi.org/10.5194/gmd-15-7505-2022, 2022
Short summary
Short summary
OpenStreetMap is a collaborative project aimed at creaing a free dataset containing topographical information. Since these data are available worldwide, they can be used as standard data for geoscience studies. However, most buildings miss the height information that constitutes key data for numerous fields (urban climate, noise propagation, air pollution). In this work, the building height is estimated using statistical modeling using indicators that characterize the building's environment.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Olivier Nuissier, Fanny Duffourg, Maxime Martinet, Véronique Ducrocq, and Christine Lac
Atmos. Chem. Phys., 20, 14649–14667, https://doi.org/10.5194/acp-20-14649-2020, https://doi.org/10.5194/acp-20-14649-2020, 2020
Short summary
Short summary
This present article demonstrates how numerical simulations with very high horizontal resolution (150 m) can contribute to better understanding the key physical processes (turbulence and microphysics) that lead to Mediterranean heavy precipitation.
Robert Schoetter, Yu Ting Kwok, Cécile de Munck, Kevin Ka Lun Lau, Wai Kin Wong, and Valéry Masson
Geosci. Model Dev., 13, 5609–5643, https://doi.org/10.5194/gmd-13-5609-2020, https://doi.org/10.5194/gmd-13-5609-2020, 2020
Short summary
Short summary
Cities change the local meteorological conditions, e.g. by increasing air temperature, which can negatively impact humans and infrastructure. The urban climate model TEB is able to calculate the meteorological conditions in low- and mid-rise cities since it interacts with the lowest level of an atmospheric model. Here, a multi-layer coupling of TEB is introduced to enable modelling the urban climate of cities with many skyscrapers; the new version is tested for the high-rise city of Hong Kong.
Emilie Redon, Aude Lemonsu, and Valéry Masson
Geosci. Model Dev., 13, 385–399, https://doi.org/10.5194/gmd-13-385-2020, https://doi.org/10.5194/gmd-13-385-2020, 2020
Short summary
Short summary
The TEB urban climate model simulates micrometeorological conditions from the neighborhood scale to the entire city. It has recently been improved to more realistically address the radiative effects of trees within the urban canopy. This article presents additional developments that have been made to better represent the effect of trees on heat and moisture exchange, as well as on air flow in the streets, and on thermal comfort.
Xenia Stavropulos-Laffaille, Katia Chancibault, Jean-Marc Brun, Aude Lemonsu, Valéry Masson, Aaron Boone, and Hervé Andrieu
Geosci. Model Dev., 11, 4175–4194, https://doi.org/10.5194/gmd-11-4175-2018, https://doi.org/10.5194/gmd-11-4175-2018, 2018
Short summary
Short summary
Integrating vegetation in urban planning is promoted to counter steer potential impacts of climate and demographic changes. Assessing the multiple benefits of such strategies on the urban microclimate requires a detailed coupling of both the water and energy transfers in numerical tools. In this respect, the representation of water-related processes in the urban subsoil of the existing model TEB-Veg has been improved. The new model thus allows a better evaluation of urban adaptation strategies.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
Short summary
Short summary
This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Irène Xueref-Remy, Elsa Dieudonné, Cyrille Vuillemin, Morgan Lopez, Christine Lac, Martina Schmidt, Marc Delmotte, Frédéric Chevallier, François Ravetta, Olivier Perrussel, Philippe Ciais, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, T. Gerard Spain, and Christophe Ampe
Atmos. Chem. Phys., 18, 3335–3362, https://doi.org/10.5194/acp-18-3335-2018, https://doi.org/10.5194/acp-18-3335-2018, 2018
Short summary
Short summary
Urbanized and industrialized areas are the largest source of fossil CO2. This work analyses the atmospheric CO2 variability observed from the first in situ network deployed in the Paris megacity area. Gradients of several ppm are found between the rural, peri-urban and urban sites at the diurnal to the seasonal scales. Wind direction and speed as well as boundary layer dynamics, correlated to highly variable urban emissions, are shown to be key regulator factors of the observed CO2 records.
Jeanne Colin, Christine Lac, Valéry Massion, and Alexandre Paci
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-226, https://doi.org/10.5194/gmd-2017-226, 2017
Preprint withdrawn
Short summary
Short summary
The meteorological model Meso-NH is adapted in order to be run in DNS mode (Direct Numerical Simulation) to represent atmospheric flows generated in laboratory. The implementations we performed are validated against exact solutions and experimental data. Thus, Meso-NH can now be used as a complement to laboratory experiments, to complete and/or extend the data. The ability to run it in DNS also brings new prospects as it offers a new framework to test parametrizations of fine-scale processes.
Marie Mazoyer, Christine Lac, Odile Thouron, Thierry Bergot, Valery Masson, and Luc Musson-Genon
Atmos. Chem. Phys., 17, 13017–13035, https://doi.org/10.5194/acp-17-13017-2017, https://doi.org/10.5194/acp-17-13017-2017, 2017
Short summary
Short summary
Large eddy simulations of a radiation fog event occurring during the ParisFog experiment have been studied to analyze the impact of the dynamics on the fog life cycle. They included a sophisticated microphysical scheme, the drag effect of a trees barrier and deposition on vegetation. The blocking effect of the trees induces elevated fog formation and limits cooling and cloud water production. The deposition process was found to exert the most significant impact on the fog prediction.
Robert Schoetter, Valéry Masson, Alexis Bourgeois, Margot Pellegrino, and Jean-Pierre Lévy
Geosci. Model Dev., 10, 2801–2831, https://doi.org/10.5194/gmd-10-2801-2017, https://doi.org/10.5194/gmd-10-2801-2017, 2017
Short summary
Short summary
We enhance the urban climate model TEB to take into account for the variety of building use and human behaviour related to building energy consumption. This can improve urban climate simulations and is crucial for quantification of the impact of climate change mitigation and adaptation measures in urban areas (e.g. white roofs, insulation of buildings). An evaluation for Toulouse shows that the enhanced version of TEB captures well the spatio-temporal variability of building energy consumption.
Daniel Cariolle, Philippe Moinat, Hubert Teyssèdre, Luc Giraud, Béatrice Josse, and Franck Lefèvre
Geosci. Model Dev., 10, 1467–1485, https://doi.org/10.5194/gmd-10-1467-2017, https://doi.org/10.5194/gmd-10-1467-2017, 2017
Short summary
Short summary
This article reports on the development and tests of the adaptive semi-implicit scheme (ASIS) solver for the simulation of atmospheric chemistry. To solve the ordinary differential equations associated with the time evolution of the species concentrations, ASIS adopts a one-step linearized implicit scheme. It conserves mass and has a time-stepping module to control the accuracy of the numerical solution. ASIS was found competitive in terms of computation cost against higher-order schemes.
Emilie C. Redon, Aude Lemonsu, Valéry Masson, Benjamin Morille, and Marjorie Musy
Geosci. Model Dev., 10, 385–411, https://doi.org/10.5194/gmd-10-385-2017, https://doi.org/10.5194/gmd-10-385-2017, 2017
Short summary
Short summary
In order to assess the potential of cooling of urban vegetation in cities, we need to refine some processes in the microclimate models running on cities as the TEB model. The shading effects of trees on roads, low vegetation (grass), or walls are key processes impacting both air and surface temperatures in the streets by reducing them and improving the thermal comfort of inhabitants. They have been implemented into the TEB model and simulations have been evaluated by a fine-scale model, SOLENE.
Johannes Staufer, Grégoire Broquet, François-Marie Bréon, Vincent Puygrenier, Frédéric Chevallier, Irène Xueref-Rémy, Elsa Dieudonné, Morgan Lopez, Martina Schmidt, Michel Ramonet, Olivier Perrussel, Christine Lac, Lin Wu, and Philippe Ciais
Atmos. Chem. Phys., 16, 14703–14726, https://doi.org/10.5194/acp-16-14703-2016, https://doi.org/10.5194/acp-16-14703-2016, 2016
Alicia Gressent, Bastien Sauvage, Daniel Cariolle, Mathew Evans, Maud Leriche, Céline Mari, and Valérie Thouret
Atmos. Chem. Phys., 16, 5867–5889, https://doi.org/10.5194/acp-16-5867-2016, https://doi.org/10.5194/acp-16-5867-2016, 2016
Short summary
Short summary
In chemical transport models, NOx emitted by lightning (LNOx) is instantaneously diluted into the grid. A plume-in-grid parameterization to account for the sub-grid chemistry of LNOx is presented. This approach was implemented into the GEOS-Chem model and leads to a relative increase of NOx and O3 (18 % and 2 %, respectively, in July) on a large scale downwind of lightning emissions and a relative decrease (25 % and 8 %, respectively, over central Africa in July) over the regions of emissions.
J. Picot, R. Paoli, O. Thouron, and D. Cariolle
Atmos. Chem. Phys., 15, 7369–7389, https://doi.org/10.5194/acp-15-7369-2015, https://doi.org/10.5194/acp-15-7369-2015, 2015
R. Paoli, O. Thouron, J. Escobar, J. Picot, and D. Cariolle
Atmos. Chem. Phys., 14, 5037–5055, https://doi.org/10.5194/acp-14-5037-2014, https://doi.org/10.5194/acp-14-5037-2014, 2014
S. Unterstrasser, R. Paoli, I. Sölch, C. Kühnlein, and T. Gerz
Atmos. Chem. Phys., 14, 2713–2733, https://doi.org/10.5194/acp-14-2713-2014, https://doi.org/10.5194/acp-14-2713-2014, 2014
V. Vionnet, E. Martin, V. Masson, G. Guyomarc'h, F. Naaim-Bouvet, A. Prokop, Y. Durand, and C. Lac
The Cryosphere, 8, 395–415, https://doi.org/10.5194/tc-8-395-2014, https://doi.org/10.5194/tc-8-395-2014, 2014
C. Lac, R. P. Donnelly, V. Masson, S. Pal, S. Riette, S. Donier, S. Queguiner, G. Tanguy, L. Ammoura, and I. Xueref-Remy
Atmos. Chem. Phys., 13, 4941–4961, https://doi.org/10.5194/acp-13-4941-2013, https://doi.org/10.5194/acp-13-4941-2013, 2013
Related subject area
Atmospheric sciences
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Implementation of a dry deposition module (DEPAC v3.11) in a large eddy simulation code (DALES v4.4)
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
Short summary
Short summary
Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
Short summary
Short summary
This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
Short summary
Short summary
Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
Short summary
Short summary
This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
Short summary
Short summary
We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
Short summary
Short summary
Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
Short summary
Short summary
In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
Short summary
Short summary
Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
Short summary
Short summary
The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
Short summary
Short summary
This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
Short summary
Short summary
This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
Short summary
Short summary
We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
Short summary
Short summary
Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
Short summary
We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
Short summary
Short summary
Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
Short summary
Short summary
The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
Short summary
Short summary
The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
Short summary
Short summary
Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
Short summary
Short summary
This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
Short summary
Short summary
This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
Short summary
Short summary
High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
Short summary
Short summary
We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
Short summary
Short summary
Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
Cited articles
Allwine, K. J., Shinn, J. H., Streit, G. E., Clawson, K. L., and Brown, M.:
Overview of URBAN 2000: A multiscale field study of dispersion through an urban environment,
B. Am. Meteorol. Soc., 83, 521–536, 2002. a
Angot, P., Bruneau, C. H., and Fabrie, P.:
A penalization method to take into account obstacles in incompressible viscous flows,
Numer. Math., 81, 497–520, 1999. a
Auguste, F.:
Instabilités de sillage et de trajectoire dans un fluide visqueux,
PhD thesis, University of Toulouse, Toulouse, France, 2010. a
Auguste, F.: MNH-IBM: Source code and input files, available at: https://cerfacs.fr/MNHIBM/Auguste-GMD-2019, last access: 13 May 2019. a
Bernadet, P.:
The pressure term in the anelastic model: A symmetric elliptic solver for an Arakawa C grid in generalized coordinates,
Mon. Weather Rev., 123, 2474–2490, 1995. a
Biltoft, C. A., Yee, E., and Jones, C. D.:
Overview of the Mock Urban Setting Test (MUST),
in: Proceedings of the Fourth Symposium on the Urban Environment, 19 May 2002, Norfolk, VA, USA, 20–24, 2002. a
Bouchon, F., Dubois, T., and James, N.:
A second-order cut-cell method for the numerical simulation of 2D flows past obstacles,
Comput. Fluids, 65, 80–91, 2012. a
Braza, M., Chassaing, P., and Minh, H. H.:
Numerical study and physical analysis of the pressure and velocity fields in the near wake of a circular cylinder,
J. Fluid Mech., 165, 79–130, 1986. a
Brennen, C. E.:
A Review of Added Mass and Fluid Inertial Forces,
Naval Civil Engineering Laboratory, Port Hueneme, CA, USA, CR 82.010, 1982. a
Breuer, M., Lakehal, D., and Rodi, W.:
Flow around a surface mounted cubical obstacle: comparison of LES and RANS-results,
Computation of Three-Dimensional Complex Flows, Vieweg+ Teubner Verlag, 22–30, https://doi.org/10.1007/978-3-322-89838-8, 1996. a
Businger, J. A., Wyngaard, J. C., Izumi, Y., and Bradley, E.:
Flux profile relationship in the atmospheric surface layer,
J. Atmos. Sci., 28, 181–189, 1971. a
Camelli, F., Lohner, R., and Hanna, S.:
VLES study of MUST experiment,
43rd AIAA Aerospace Sciences Meeting and Exhibit, 10–13 January 2005, Reno, Nevada, USA, 2005. a
Capizzano, F.:
Turbulent wall model for immersed boundary methods,
AIAA J., 49, 2367–2381, 2011. a
Carpenter, K. M.:
Note on the paper “Radiation conditions for lateral boundaries of limited area numerical models”,
Q. J. Roy. Meteor. Soc., 110, 717–719M, 1982. a
Castro, I. P. and Robins, A. G.:
The flow around a surface-mounted cube in uniform and turbulent streams,
J. Fluid Mech., 79, 307–335, 1977. a
Clarke, D. K., Hassan, H. A., and Salas, M. D.:
Euler calculations for multielement airfoils using Cartesian grids,
AIAA J., 24, 353–358, 1986. a
Clawson, K. L., Carter, R. G., Lacroix, D. J., Biltoft, C. A., Hukari, N. F., Johnson, R. C., Rich, J. D., Beard, S. A., and Strong, T.:
Joint Urban 2003 (JU03) SF6 atmospheric tracer field tests,
US Department of Commerce, National Oceanic and Atmospheric Administration, Office of Oceanic and Atmospheric Research, Air Resources Laboratory, Idaho, USA, 2005. a
Colella, P. and Woodward, P. R.:
Application of the Piecewise Parabolic Method to meteorological modeling,
J. Comput. Phys., 54, 174–201, 1984. a
Coutanceau, M. and Bouard, R.:
Experimental determination of the main features of the viscous flow in the wake of a circular cylinder in uniform translation. Part I – Steady flow,
J. Fluid Mech., 79, 231–256, 1977. a
Cuxart, J., Bougeault, P., and Redelsperger, J.-L.:
A turbulence scheme allowing for mesoscale and large-eddy simulations,
Q. J. Roy. Meteor. Soc., 126, 1–30, 2000. a
Dejoan, A., Santiago, J.-L., Martilli, A., Martin, F., and Pinelli, A.:
Comparison between large-eddy simulation and Reynolds-averaged Navier–Stokes computations for the MUST field experiment. Part II: effects of incident wind angle deviation on the mean flow and plume dispersion,
Bound.-Lay. Meteorol., 135, 133–150, 2010. a
Depardon, S., Lasserre, J. J., Brizzi, L. E., and Borée, J.:
Instantaneous skin-friction pattern analysis using automated critical point detection on near-wall PIV data,
Meas. Sci. Technol., 17, 1659–1669, 2006. a
Donnelly, R. P., Lyons, T. J., and Flassak, T.:
Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling,
J. Atmos. Environ., 43, 4416–4423, 2009. a
Durran, D. R.:
Improving the anelastic approximation,
J. Atmos. Sci., 46, 1452–1461, 1989. a
Goldstein, D., Handler, R., and Sirovich, L.:
Modeling a no-slip flow boundary with an external force field,
J. Comput. Phys., 105, 354–366, 1993. a
Hanna, S. R., Hansen, O. R., and Dharmavaram, S.:
FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations,
J. Atmos. Env., 38, 4675–4687, 2004. a
Hidalgo, J., Pigeon, G., and Masson, V.:
Urban-breeze circulation during the CAPITOUL experiment: observational data analysis approach,
Meteorol. Atmos. Phys., 102, 223–241, 2008. a
Jiang, G.-S. and Shu, C.-W.:
Efficient Implementation of Weighted ENO Schemes,
J. Comput. Phys., 126, 202–228, 1996. a
Kalitzin, G., Medic, G., Iaccarino, G., and Durbin, P.:
Near-wall behavior of RANS turbulence models and implications for wall functions,
J. Comput. Phys., 204, 265–291, 2005. a
Kanda, M., Kanega, M., Kawai, T., Moriwaki, R., and Sugawara, H.:
Roughness lengths for momentum and heat derived from outdoor urban scale models,
J. Appl. Meteorol. Clim., 46, 1067–1079, 2007. a
Kempe, T. and Fröhlich, J.:
An improved immersed boundary method with direct forcing for the simulation of particle laden flows,
J. Comput. Phys., 231, 3663–3684, 2012. a
Kim, J., Kim, D., and Choi, H.:
An immersed-boundary finite-volume method for simulations of flow in complex geometries,
J. Comput. Phys., 171, 132–150, 2001. a
König, M.:
Large-eddy simulation modelling for urban Scale,
PhD thesis, University of Leipzig, Leipzig, Germany, 2014. a
Lac, C., Chaboureau, J.-P., Masson, V., Pinty, J.-P., Tulet, P., Escobar, J., Leriche, M., Barthe, C., Aouizerats, B., Augros, C., Aumond, P., Auguste, F., Bechtold, P., Berthet, S., Bielli, S., Bosseur, F., Caumont, O., Cohard, J.-M., Colin, J., Couvreux, F., Cuxart, J., Delautier, G., Dauhut, T., Ducrocq, V., Filippi, J.-B., Gazen, D., Geoffroy, O., Gheusi, F., Honnert, R., Lafore, J.-P., Lebeaupin Brossier, C., Libois, Q., Lunet, T., Mari, C., Maric, T., Mascart, P., Mogé, M., Molinié, G., Nuissier, O., Pantillon, F., Peyrillé, P., Pergaud, J., Perraud, E., Pianezze, J., Redelsperger, J.-L., Ricard, D., Richard, E., Riette, S., Rodier, Q., Schoetter, R., Seyfried, L., Stein, J., Suhre, K., Taufour, M., Thouron, O., Turner, S., Verrelle, A., Vié, B., Visentin, F., Vionnet, V., and Wautelet, P.: Overview of the Meso-NH model version 5.4 and its applications, Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, 2018. a
Lafore, J. P., Stein, J., Asencio, N., Bougeault, P., Ducrocq, V., Duron, J., Fischer, C., Héreil, P., Mascart, P., Masson, V., Pinty, J. P., Redelsperger, J. L., Richard, E., and Vilà-Guerau de Arellano, J.: The Meso-NH Atmospheric Simulation System. Part I: adiabatic formulation and control simulations, Ann. Geophys., 16, 90–109, https://doi.org/10.1007/s00585-997-0090-6, 1998. a
Leveque, R. J. and Li, Z.:
The immersed interface method for elliptic equations with discontinuous coefficients and singular sources,
SIAM J. Numer. Anal., 31, 1019–1044, 1994. a
Lin, S. and Rood, R. B.:
Multidimensional Flux-Form Semi-Lagrangian Transport Schemes,
Mon. Weather Rev., 124, 2046–2070, 1996. a
Linnick, M. N. and Fasel, H. F.:
A high-order immersed interface method for simulating unsteady incompressible flows on irregular domains,
J. Comput. Phys., 204, 157–192, 2005. a
Lipps, F. and Hemler, R. S.:
A scale analysis of deep moist convection and some related numerical calculations,
J. Atmos. Sci., 39, 2192–2210, 1982. a
Liu, Y., Chen, F., Warner, T., and Basara, J.:
Verification of a mesoscale data-assimilation and forecasting system for the Oklahoma City area during the Joint Urban 2003 field project,
J. Appl. Meteorol. Clim., 45, 912–929, 2006. a
Lund, T. S.:
Generation of Turbulent Inflow Data for Spatially-Developing Boundary Layer Simulations,
J. Comput. Phys., 140, 233-–258, 1998. a
Lunet, T., Lac, C., Auguste, F., Visentin, F., Masson, V., and Escobar, J.:
Combination of WENO and explicit Runge-Kutta methods for wind transport in Meso-NH model,
Mon. Weather Rev., 145, 3817–3838, 2017. a
Masson, V., Gomes, L., Pigeon, G., Liousse, C., Pont, V., Lagouarde, J.-P., Voogt, J., Salmond, J., Oke, T., Hidalgo, J., Legain, D., Garrouste, O., Lac, C., Connan, O., Briottet, X., Lachérade, S., and Tulet, P.:
The canopy and aerosol particles interactions in Toulouse urban layer (CAPITOUL) experiment,
Meteorol. Atmos. Phys., 102, 135–157, 2008. a
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013. a, b
Mayor S., Spalart P., and Tripoli, G. J.:
Application of a Perturbation Recycling Method in the Large-Eddy Simulation of a Mesoscale Convective Internal Boundary Layer,
J. Atmos. Sci., 59, 2385–2395, 2002. a
Milne-Thomson, L. M.:
Theoretical hydrodynamics,
Dover Books on Physics Series, Dover Publications, 1968. a
Mohd-Yusof, J.: Combined immersed-Boundary/B-Spline methods for simulations of flow in complex geometries, CTR Annual Research Briefs, NASA Research Center/Stanford University, Center for Turbulence Research, Stanford, CA, USA, 1997. a
Monin, A. S. and Obukhov, A. M. F.:
Basic laws of turbulent mixing in the surface layer of the atmosphere,
Contrib. Geophys. Inst. Acad. Sci. USSR, 151, 163–187, 1954. a
Moriwaki, R. and Kanda, M.:
Seasonal and diurnal fluxes of radiation, heat, water vapor, and carbon dioxide over a suburban area,
J. Appl. Meteorol., 43, 1700–1710, 2004. a
Park, J., Kwon, K., and Choi, H.:
Numerical solutions of flow past a circular cylinder at Reynolds numbers up to 160,
KSME Int. J., 12, 1200–1205, 1998. a
Peskin, C. S.:
Flow patterns around heart valves: a numerical method,
J. Comput. Phys., 10, 252–271, 1972. a
Pierson, J.-L.:
Traversée d'une interface entre deux fluides par une sphère,
PhD thesis, University of Toulouse, Toulouse, France, 2015. a
Piomelli, U. and Balaras, E.:
Wall-layer models for large-eddy simulations,
Annu. Rev. Fluid Mech., 34, 349–374, 2002. a
Prandtl, L.:
Bericht über Untersuchungen zur ausgebildeten Turbulenz,
Z. Angew. Math, Meth., 5, 136–139, 1925. a
Redelsperger, J.-L. and Sommeria, G.:
Methode de representation de la turbulence inferieure a la maille pour un modele tri-dimensionnel de convection nuageuse,
Bound.-Lay. Meteorol., 21, 509–530, 1981. a
Redelsperger, J.-L., Mahe, F., and Carlotti, P.:
A simple and general subgrid model suitable both surface layer and free-stream turbulence,
Bound.-Lay. Meteorol., 101, 375–408, 2001. a
Shu, C.-W. and Osher, S.:
Efficient implementation of essentially non-oscillatory shock capturing schemes,
J. Comput. Phys., 83, 32–78, 1989. a
Skamarock, W. C., Smolarkiewicz, P. K., and Klemp, J. B.:
Preconditioned conjugate-residual solvers for Helmhotz equations in nonhydrostatic models,
Mon. Weather Rev., 125, 587–599, 1997. a
Stålberg, E., Brüger, A., Lötstedt, P., Johansson, A. V., and Henningson, D. S.:
High order accurate solution of flow past a circular cylinder,
J. Sci. Comput., 27, 431–441, 2006. a
Stein, J., Richard, E., Lafore, J.-P., Pinty, J.-P., Asencio, N., and Cosma, S.:
High-resolution non-hydrostatic simulations of flash-flood episodes with grid-nesting and ice-phase parametrization,
Meteorol. Atmos. Phys., 72, 101–110, 2000. a
Straka, J. M., Wilhelmson, R. B., Wicker, L. J., Anderson, J. R., and Droegemeier, K. K.:
Numerical solutions of a non-linear density current: A benchmark solution and comparisons,
Int. J. Numer. Meth. Fl., 17, 1–22, 1993. a
Taira, K. and Colonius, T.:
The immersed boundary method: a projection approach,
J. Comput. Phys., 225, 2118–2137, 2007. a
Udaykumar, H. S. and Shyy, W.:
A grid-supported marker particle scheme for interface tracking,
Numer. Heat Transfer, 27, 127–153, 1995. a
Wang, K., Li, Y., Li, Y., and Yuan, M.:
The stone forest as a small-scale field model for urban climate studies,
9th International Conference on Urban Climate (ICUC9), 20–24 July 2015, Toulouse, France, 2015. a
Yang, G., Causon, D. M., Ingram, D. M., Saunders, R., and Batten, P.:
A Cartesian cut cell method for compressible flows part A: Static body problems,
Aeronaut. J., 101, 47–56, 1997. a
Yang, X. I. and Meneveau, C.:
Recycling inflow method for simulations of spatially evolving turbulent boundary layers over rough surfaces,
J. Turbul., 17, 75–93, 2016. a
Ye, T., Mittal, R., Udaykumar, H. S., and Shyy, W.:
An accurate Cartesian grid method for viscous incompressible flows with complex immersed boundaries,
J. Comput. Phys., 156, 209–240, 1999. a
Young, D. M. and Jea, K. C.:
Generalized conjugate-gradient acceleration of nonsymmetrizable iterative methods,
Linear Algebra Appl., 34, 159–194, 1980. a
Short summary
The numerical implementation of an immersed boundary method in the atmospheric solver Meso-NH is presented. This technique models fluid–solid interaction and allows for the simulation of urban flows by considering buildings to be part of the resolved scales. This study constitutes a first robust step towards a better understanding of the interactions between weather and cities and better predictions of such interactions.
The numerical implementation of an immersed boundary method in the atmospheric solver Meso-NH is...
