Articles | Volume 8, issue 7
https://doi.org/10.5194/gmd-8-1919-2015
© Author(s) 2015. 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-8-1919-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model experiment description paper
| 
01 Jul 2015
Model experiment description paper |
| 01 Jul 2015
AROME-WMED, a real-time mesoscale model designed for the HyMeX special observation periods
N. Fourrié
CNRM-GAME, Météo-France and CNRS, Toulouse, France
É. Bresson
CNRM-GAME, Météo-France and CNRS, Toulouse, France
M. Nuret
CNRM-GAME, Météo-France and CNRS, Toulouse, France
C. Jany
CNRM-GAME, Météo-France and CNRS, Toulouse, France
P. Brousseau
CNRM-GAME, Météo-France and CNRS, Toulouse, France
A. Doerenbecher
CNRM-GAME, Météo-France and CNRS, Toulouse, France
M. Kreitz
École Nationale de la Météorologie, Météo-France, Toulouse, France
O. Nuissier
CNRM-GAME, Météo-France and CNRS, Toulouse, France
E. Sevault
CNRM-GAME, Météo-France and CNRS, Toulouse, France
H. Bénichou
Direction des Opérations pour la Prévision/COMPAS, Météo-France, Toulouse, France
M. Amodei
Direction des Opérations pour la Prévision/COMPAS, Météo-France, Toulouse, France
F. Pouponneau
Direction des Opérations pour la Prévision/COMPAS, Météo-France, Toulouse, France
Related authors
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech., 17, 5279–5299, https://doi.org/10.5194/amt-17-5279-2024, https://doi.org/10.5194/amt-17-5279-2024, 2024
Short summary
Short summary
The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and acquiring data with a high temporal frequency. This work aims to evaluate its potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on ozone analysis.
Ethel Villeneuve, Philippe Chambon, and Nadia Fourrié
Atmos. Meas. Tech., 17, 3567–3582, https://doi.org/10.5194/amt-17-3567-2024, https://doi.org/10.5194/amt-17-3567-2024, 2024
Short summary
Short summary
In cloudy situations, infrared and microwave observations are complementary, with infrared being sensitive to cloud tops and microwave sensitive to precipitation. However, infrared satellite observations are underused. This study aims to quantify if the inconsistencies in the modelling of clouds prevent the use of cloudy infrared observations in the process of weather forecasting. It shows that the synergistic use of infrared and microwave observations is beneficial, despite inconsistencies.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
Short summary
Short summary
Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 21, 463–480, https://doi.org/10.5194/nhess-21-463-2021, https://doi.org/10.5194/nhess-21-463-2021, 2021
Short summary
Short summary
The assimilation impact of four observation data sets on forecasts is studied in a mesoscale weather model. The ground-based Global Navigation Satellite System (GNSS) zenithal total delay data set with information on humidity has the largest impact on analyses and forecasts, representing an evenly spread and frequent data set for each analysis time over the model domain. Moreover, the reprocessing of these data also improves the forecast quality, but this impact is not statistically significant.
Olivier Coopmann, Vincent Guidard, Nadia Fourrié, Béatrice Josse, and Virginie Marécal
Atmos. Meas. Tech., 13, 2659–2680, https://doi.org/10.5194/amt-13-2659-2020, https://doi.org/10.5194/amt-13-2659-2020, 2020
Short summary
Short summary
The objective of this paper is to make a new selection of IASI channels by taking into account inter-channel observation-error correlations. Our selection further reduces the analysis error by 3 % in temperature, 1.8 % in humidity and 0.9 % in ozone compared to Collard’s selection, when using the same number of channels. A selection of 400 IASI channels is proposed at the end of the paper which is able to further reduce analysis errors.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, Olivier Caumont, Alexis Doerenbecher, Eric Wattrelot, Patrick Moll, Hervé Bénichou, Dominique Puech, Olivier Bock, Pierre Bosser, Patrick Chazette, Cyrille Flamant, Paolo Di Girolamo, Evelyne Richard, and Frédérique Saïd
Geosci. Model Dev., 12, 2657–2678, https://doi.org/10.5194/gmd-12-2657-2019, https://doi.org/10.5194/gmd-12-2657-2019, 2019
Short summary
Short summary
The AROME-WMED (western Mediterranean) model is a dedicated version of the mesoscale Numerical Weather Prediction AROME-France model that ran in real time during the first special observation period of HyMeX. Two reanalyses were performed after the campaign. This paper depicts the main differences between the real-time version and the benefits brought by both HyMeX reanalyses. The second reanalysis is found to be closer to observations than the previous AROME-WMED analyses.
Imane Farouk, Nadia Fourrié, and Vincent Guidard
Atmos. Meas. Tech., 12, 3001–3017, https://doi.org/10.5194/amt-12-3001-2019, https://doi.org/10.5194/amt-12-3001-2019, 2019
Short summary
Short summary
A selection for homogeneous scenes for the assimilation of IASI radiances is proposed by using information on the collocated imager pixels inside each infrared observation. A revised method for the selection, which represents a compromise between two methods to select homogeneous scenes using homogeneity criteria already proposed in the literature, has a positive impact on the observation minus the simulation statistics. It has been tested in a numerical weather prediction model for clear sky.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, Nadia Fourrié, and Pascal Marquet
Nat. Hazards Earth Syst. Sci., 19, 907–926, https://doi.org/10.5194/nhess-19-907-2019, https://doi.org/10.5194/nhess-19-907-2019, 2019
Short summary
Short summary
The potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area is investigated. The 1D + 3DVar assimilation method has been adapted to assimilate the W-band reflectivity in the Météo-France kilometre-scale NWP model AROME. The results suggest that the joint assimilation of W-band reflectivity and horizontal wind profiles lead to a slight improvement of moisture analyses and rainfall precipitation forecasts.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, and Nadia Fourrié
Nat. Hazards Earth Syst. Sci., 19, 821–835, https://doi.org/10.5194/nhess-19-821-2019, https://doi.org/10.5194/nhess-19-821-2019, 2019
Short summary
Short summary
The study reports on the impact of the assimilation of wind data from airborne Doppler cloud-profiling radar in a kilometre-scale NWP model on predicting heavy precipitation events in the Mediterranean area. The positive impact of the assimilation of such data is particularly evidenced for a heavy precipitation event and results are slightly encouraging over a 45-day period. In addition, the impact of the length of the assimilation window in a 3h-3DVar assimilation system is investigated.
Javier Andrey-Andrés, Nadia Fourrié, Vincent Guidard, Raymond Armante, Pascal Brunel, Cyril Crevoisier, and Bernard Tournier
Atmos. Meas. Tech., 11, 803–818, https://doi.org/10.5194/amt-11-803-2018, https://doi.org/10.5194/amt-11-803-2018, 2018
Short summary
Short summary
A new generation of the Infrared Atmospheric Sounding Interferometer (IASI) sounders, whose highly accurate measurements are commonly used in environment applications, has already been designed: IASI New Generation (IASI-NG). A database of IASI and IASI-NG simulated observations was built to set a common framework for future impact studies. This first study showed the IASI-NG benefit with an improvement of the temperature retrievals throughout the atmosphere and a lower benefit for the humidity.
Pierre Brousseau, Valérie Vogt, Etienne Arbogast, Maud Martet, Guillaume Thomas, and Loïk Berre
EGUsphere, https://doi.org/10.5194/egusphere-2025-2642, https://doi.org/10.5194/egusphere-2025-2642, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Since October 2024, the Météo-France operational convective scale model AROME-France uses a three-dimensional ensemble-based variational data assimilation system. This allows observations to be spatialised in a flow-dependent way, leading to improved initial conditions. Numerous sensitivity studies allowed to configure this scheme in an operational context. Major positive impacts on the forecast quality have been demonstrated over a long period and on several severe meteorological situations.
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech., 17, 5279–5299, https://doi.org/10.5194/amt-17-5279-2024, https://doi.org/10.5194/amt-17-5279-2024, 2024
Short summary
Short summary
The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and acquiring data with a high temporal frequency. This work aims to evaluate its potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on ozone analysis.
Ethel Villeneuve, Philippe Chambon, and Nadia Fourrié
Atmos. Meas. Tech., 17, 3567–3582, https://doi.org/10.5194/amt-17-3567-2024, https://doi.org/10.5194/amt-17-3567-2024, 2024
Short summary
Short summary
In cloudy situations, infrared and microwave observations are complementary, with infrared being sensitive to cloud tops and microwave sensitive to precipitation. However, infrared satellite observations are underused. This study aims to quantify if the inconsistencies in the modelling of clouds prevent the use of cloudy infrared observations in the process of weather forecasting. It shows that the synergistic use of infrared and microwave observations is beneficial, despite inconsistencies.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
Short summary
Short summary
Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
Claudia Christine Stephan, Sabrina Schnitt, Hauke Schulz, Hugo Bellenger, Simon P. de Szoeke, Claudia Acquistapace, Katharina Baier, Thibaut Dauhut, Rémi Laxenaire, Yanmichel Morfa-Avalos, Renaud Person, Estefanía Quiñones Meléndez, Gholamhossein Bagheri, Tobias Böck, Alton Daley, Johannes Güttler, Kevin C. Helfer, Sebastian A. Los, Almuth Neuberger, Johannes Röttenbacher, Andreas Raeke, Maximilian Ringel, Markus Ritschel, Pauline Sadoulet, Imke Schirmacher, M. Katharina Stolla, Ethan Wright, Benjamin Charpentier, Alexis Doerenbecher, Richard Wilson, Friedhelm Jansen, Stefan Kinne, Gilles Reverdin, Sabrina Speich, Sandrine Bony, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 491–514, https://doi.org/10.5194/essd-13-491-2021, https://doi.org/10.5194/essd-13-491-2021, 2021
Short summary
Short summary
The EUREC4A field campaign took place in the western tropical Atlantic during January and February 2020. A total of 811 radiosondes, launched regularly (usually 4-hourly) from Barbados, and 4 ships measured wind, temperature, and relative humidity. They sampled atmospheric variability associated with different ocean surface conditions, synoptic variability, and mesoscale convective organization. The methods of data collection and post-processing for the radiosonde data are described here.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 21, 463–480, https://doi.org/10.5194/nhess-21-463-2021, https://doi.org/10.5194/nhess-21-463-2021, 2021
Short summary
Short summary
The assimilation impact of four observation data sets on forecasts is studied in a mesoscale weather model. The ground-based Global Navigation Satellite System (GNSS) zenithal total delay data set with information on humidity has the largest impact on analyses and forecasts, representing an evenly spread and frequent data set for each analysis time over the model domain. Moreover, the reprocessing of these data also improves the forecast quality, but this impact is not statistically significant.
Olivier Coopmann, Vincent Guidard, Nadia Fourrié, Béatrice Josse, and Virginie Marécal
Atmos. Meas. Tech., 13, 2659–2680, https://doi.org/10.5194/amt-13-2659-2020, https://doi.org/10.5194/amt-13-2659-2020, 2020
Short summary
Short summary
The objective of this paper is to make a new selection of IASI channels by taking into account inter-channel observation-error correlations. Our selection further reduces the analysis error by 3 % in temperature, 1.8 % in humidity and 0.9 % in ozone compared to Collard’s selection, when using the same number of channels. A selection of 400 IASI channels is proposed at the end of the paper which is able to further reduce analysis errors.
Alexis Doerenbecher and Jean-François Mahfouf
Adv. Sci. Res., 16, 215–222, https://doi.org/10.5194/asr-16-215-2019, https://doi.org/10.5194/asr-16-215-2019, 2019
Short summary
Short summary
In May 2017, E-AMDAR service temporarily increased the number of aircraft data over France, especially from from planes ascending from or descending towards French airports. This was the opportunity to check the impact of these additional data on forecast skill scores in AROME-France model. An OSE was carried out by removing about 14 % of E-AMDAR data but a critical step before the OSE was to identify which data could be considered as supplementary. Results of the one-month OSE are discussed.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, Olivier Caumont, Alexis Doerenbecher, Eric Wattrelot, Patrick Moll, Hervé Bénichou, Dominique Puech, Olivier Bock, Pierre Bosser, Patrick Chazette, Cyrille Flamant, Paolo Di Girolamo, Evelyne Richard, and Frédérique Saïd
Geosci. Model Dev., 12, 2657–2678, https://doi.org/10.5194/gmd-12-2657-2019, https://doi.org/10.5194/gmd-12-2657-2019, 2019
Short summary
Short summary
The AROME-WMED (western Mediterranean) model is a dedicated version of the mesoscale Numerical Weather Prediction AROME-France model that ran in real time during the first special observation period of HyMeX. Two reanalyses were performed after the campaign. This paper depicts the main differences between the real-time version and the benefits brought by both HyMeX reanalyses. The second reanalysis is found to be closer to observations than the previous AROME-WMED analyses.
Imane Farouk, Nadia Fourrié, and Vincent Guidard
Atmos. Meas. Tech., 12, 3001–3017, https://doi.org/10.5194/amt-12-3001-2019, https://doi.org/10.5194/amt-12-3001-2019, 2019
Short summary
Short summary
A selection for homogeneous scenes for the assimilation of IASI radiances is proposed by using information on the collocated imager pixels inside each infrared observation. A revised method for the selection, which represents a compromise between two methods to select homogeneous scenes using homogeneity criteria already proposed in the literature, has a positive impact on the observation minus the simulation statistics. It has been tested in a numerical weather prediction model for clear sky.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, Nadia Fourrié, and Pascal Marquet
Nat. Hazards Earth Syst. Sci., 19, 907–926, https://doi.org/10.5194/nhess-19-907-2019, https://doi.org/10.5194/nhess-19-907-2019, 2019
Short summary
Short summary
The potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area is investigated. The 1D + 3DVar assimilation method has been adapted to assimilate the W-band reflectivity in the Météo-France kilometre-scale NWP model AROME. The results suggest that the joint assimilation of W-band reflectivity and horizontal wind profiles lead to a slight improvement of moisture analyses and rainfall precipitation forecasts.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, and Nadia Fourrié
Nat. Hazards Earth Syst. Sci., 19, 821–835, https://doi.org/10.5194/nhess-19-821-2019, https://doi.org/10.5194/nhess-19-821-2019, 2019
Short summary
Short summary
The study reports on the impact of the assimilation of wind data from airborne Doppler cloud-profiling radar in a kilometre-scale NWP model on predicting heavy precipitation events in the Mediterranean area. The positive impact of the assimilation of such data is particularly evidenced for a heavy precipitation event and results are slightly encouraging over a 45-day period. In addition, the impact of the length of the assimilation window in a 3h-3DVar assimilation system is investigated.
Javier Andrey-Andrés, Nadia Fourrié, Vincent Guidard, Raymond Armante, Pascal Brunel, Cyril Crevoisier, and Bernard Tournier
Atmos. Meas. Tech., 11, 803–818, https://doi.org/10.5194/amt-11-803-2018, https://doi.org/10.5194/amt-11-803-2018, 2018
Short summary
Short summary
A new generation of the Infrared Atmospheric Sounding Interferometer (IASI) sounders, whose highly accurate measurements are commonly used in environment applications, has already been designed: IASI New Generation (IASI-NG). A database of IASI and IASI-NG simulated observations was built to set a common framework for future impact studies. This first study showed the IASI-NG benefit with an improvement of the temperature retrievals throughout the atmosphere and a lower benefit for the humidity.
François Gheusi, Pierre Durand, Nicolas Verdier, François Dulac, Jean-Luc Attié, Philippe Commun, Brice Barret, Claude Basdevant, Antoine Clenet, Solène Derrien, Alexis Doerenbecher, Laaziz El Amraoui, Alain Fontaine, Emeric Hache, Corinne Jambert, Elodie Jaumouillé, Yves Meyerfeld, Laurent Roblou, and Flore Tocquer
Atmos. Meas. Tech., 9, 5811–5832, https://doi.org/10.5194/amt-9-5811-2016, https://doi.org/10.5194/amt-9-5811-2016, 2016
Short summary
Short summary
Boundary-layer pressurised balloons allow for horizontal multi-day flights in the lower atmosphere, carrying light scientific payloads. Ozonesondes, usually used for balloon soundings have too short a lifetime for such flights. An adaptation is proposed, whereby conventional sondes are operated with short measurement phases alternating with longer periods of dormancy. The sondes were operated over the western Mediterranean, offering an original perspective on tropospheric ozone.
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
Related subject area
Atmospheric sciences
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results
Optimized dynamic mode decomposition for reconstruction and forecasting of atmospheric chemistry data
Interpolating turbulent heat fluxes missing from a prairie observation on the Tibetan Plateau using artificial intelligence models
Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
The Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP1): Evaluating simulated atmospheric transport of air-sea gas exchange tracers and APO flux products
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
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
CoCoMET v1.0: A Unified Open-Source Toolkit for Atmospheric Object Tracking and Analysis
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
Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev., 18, 4855–4876, https://doi.org/10.5194/gmd-18-4855-2025, https://doi.org/10.5194/gmd-18-4855-2025, 2025
Short summary
Short summary
In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled aerosol–meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the China Meteorological Administration Global Forecasting System (CMA-GFS) operational global numerical weather model. The results show that assimilating BC (black carbon) observations can generate analysis increments not only for BC but also for atmospheric variables.
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev., 18, 4667–4684, https://doi.org/10.5194/gmd-18-4667-2025, https://doi.org/10.5194/gmd-18-4667-2025, 2025
Short summary
Short summary
We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced-order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity, and produces uncertainty quantification metrics. It is ideal for the forecasting of atmospheric chemistry in a computationally tractable manner.
Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025, https://doi.org/10.5194/gmd-18-4625-2025, 2025
Short summary
Short summary
This study evaluates various machine learning and statistical methods for interpolating turbulent heat flux data over the Tibetan Plateau. The Transformer model showed the best performance, leading to the development of the Transformer_CNN model, which combines global and local attention mechanisms. Results show that Transformer_CNN outperforms the other models and was successfully applied to interpolate heat flux data from 2007 to 2016.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
Short summary
Short summary
A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
Short summary
Short summary
Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 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, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
Short summary
Short summary
We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
Short summary
Short summary
We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service 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 seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
Short summary
Short summary
A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
Short summary
Short summary
SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
Short summary
Short summary
It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
Short summary
Short summary
Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
EGUsphere, https://doi.org/10.5194/egusphere-2025-1736, https://doi.org/10.5194/egusphere-2025-1736, 2025
Short summary
Short summary
We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 exchange products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
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.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
Short summary
Short summary
We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
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.
Travis Hahn, Hershel Weiner, Calvin Brooks, Jie Xi Li, Siddhant Gupta, and Dié Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1328, https://doi.org/10.5194/egusphere-2025-1328, 2025
Short summary
Short summary
Understanding how clouds evolve is important for improving weather predictions, but existing tools for tracking cloud changes are complex and difficult to compare. To address this, we developed the Community Cloud Model Evaluation Toolkit (CoCoMET) that makes it easier to analyze clouds in both models and observations. By simplifying data processing, standardizing results, and introducing new analysis features, CoCoMET helps researchers better evaluate cloud behavior and improve models.
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.
Cited articles
Amodei, M. and Stein, J.: Deterministic and fuzzy verification methods for a hierarchy of numerical models, Met. Appl., 16, 191–203, 2009.
Bénard, P., Vivoda, J., Mašek, J., Smol\`ikovà, P., Yessad, K., Smith, C., Brožkovà, R., and Geleyn, J.-F.: Dynamical kernel of the Aladin-NH spectral limited area model: revised formulation and sensitivity experiments, Q. J. Roy. Meteorol. Soc., 136, 155–169, 2010.
Bresson, E., Ducrocq, V., Nuissier, O., Ricard, D., and de Saint-Aubin, C.: Idealized numerical simulations of quasi-stationary convective systems over the Northwestern Mediterranean complex terrain, Q. J. Roy. Meteorol. Soc., 138, 1751–1763, 2012.
Brousseau, P., Berre, L., Bouttier, F., and Desroziers, G.: Background error covariances for a convective-scale data-assimilation system: AROME-France 3D-Var, Q. J. Roy. Meteorol. Soc., 137, 409–422, 2011.
Brousseau, P., Berre, L., Bouttier, F., and Desroziers, G.: Flow-dependent background-error covariances for a convective-scale data assimilation system, Q. J. Roy. Meteorol. Soc., 138, 320–322, https://doi.org/10.1002/qj.920, 2012.
Caniaux, G., Redelsperger, J.-L., and Lafore, J.-P.: A numerical study of the stratiform region of a fast-moving squall line, Part I: General description and water and heat budgets, J. Atmos. Sci., 51, 2046–2074, 1994.
Caumont, O., Ducrocq, V., Wattrelot, E., Jaubert, G., and Pradier-Vabre, S.: 1D+3D-Var assimilation of radar reflectivity data: a proof of concept, Tellus, 62, 173–187, 2010.
Courtier, P., Freydier, C., Geleyn, J.-F., Rabier, F., and Rochas, M.: The A}rpege project at Meteo-France. Proceedings of the {ECMWF workshop on numerical methods in atmospheric models, Reading, UK, 09–13 September, pp. 193–231, 1991.
Cuxart, J., Bougeault, P., and Redelsperger, J.-L.: A turbulence scheme allowing for mesoscale and large eddy simulations, Q. J. Roy. Meteorol. Soc., 126, 1–30, 2000.
Doerenbecher, A., Basdevant, C., Bernard, F., Cocquerez, P., Verdier, N., and Durand, P.: Boundary Layer Pressurized Balloons Deployed in the Mediterranean, in: Proceedings of the 21st ESA Symposium European Rocket & Balloon Programmes and Related Research, Thun Switzerland, 09–13 June 2013 (ESA SP-721, October 2013), 99–106, 2013.
Drobinski, P., Ducrocq, V., Alpert, P., Anagnostou, E., Béranger, K., Borga, M., Braud, I., Chanzy, A., Davolio, S., Delrieu, G., Estournel, C., Boubrahmi, N. F., Font, J., Grubisic, V., Gualdi, S., Homar, V., Ivancan-Picek, B., Kottmeier, C., Kotroni, V., Lagouvardos, K., Lionello, P., Llasat, M., Ludwig, W., Lutoff, C., Mariotti, A., Richard, E., Romero, R., Rotunno, R., Roussot, O., Ruin, I., Somot, S., Taupier-Letage, I., Tintore, J., Uijlenhoet, R., and Wernli, H.: HyMeX, a 10 year multidisciplinary program on the Mediterranean water cycle, BAMS, 95, 1063–1082, https://doi.org/10.1175/BAMS-D-12-00242.1, 2014.
Ducrocq, V., Braud, I., Davolio, S., Ferretti, R., Flamant, C., Jansa, A., Kalthoff, N., Richard, E., Taupier-Letage, I., Ayral, P.-A., Belamari, S., B.erne, A., Borga, M., Boudevillain, B., Bock, O., Boichard, J.-L., Bouin, M.-N., Bousquet, O., Bouvier, C., Chiggiato, J., Cimini, D., Corsmeier, U., Coppola, L., Cocquerez, P., Defer, E., Delanoë, J., Girolamo, P. D., Doerenbecher, A., Drobinski, P., Dufournet, Y., Fourrié, N., Gourley, J. J., Labatut, L., Lambert, D., Coz, J. L., Marzano, F. S., Molinié, G., Montani, A., Nord, G., Nuret, M., Ramage, K., Rison, B., Roussot, O., Said, F., Schwarzenboeck, A., Testor, P., Van-Baelen, J., Vincendon, B., Aran, M., and Tamayo, J.: HyMeX-SOP1, the field campaign dedicated to heavy precipitation and flash-flooding in the northwestern Mediterranean, B. Am. Meteorol. Soc., 95, 1083–1100, https://doi.org/10.1175/BAMS-D-12-00075.1, 2014.
Duffourg, F. and Ducrocq, V.: Origin of the moisture feeding the Heavy Precipitating Systems over Southeastern France, Nat. Hazards Earth Syst. Sci., 11, 1163–1178, https://doi.org/10.5194/nhess-11-1163-2011, 2011.
Ebert, E. E.: Fuzzy verification of high-resolution gridded forecast: a review and proposed framework, Meteorol. Appl., 15, 51–64, 2008.
Fischer C., Montmerle, T., Berre, L., Auger, L., and Stefanescu, S. E.: An overview of the variational assimilation in the ALADIN/FRANCE NWP system. Q. J. Roy. Meteorol. Soc., 613, 3477–3492, 2006.
Guidard, V., Fourrié, N., Brousseau, P., and Rabier, F.: Impact of IASI assimilation at global and convective scales and challenges for the assimilation of cloudy scenes, Q. J. Roy. Meteorol. Soc., 137, 1975–1987, https://doi.org/10.1002/qj.928, 2011.
Lebeaupin-Brossier, C., Arsouze, T., Béranger, K., Bouin, M.-N., Bresson, E., Ducrocq, V., Giordani, H., Nuret, M., Rainaud, M., and Taupier-Letage, I.: Ocean mixed layer responses to intense meteorological events during HyMeX-SOP1 from a high resolution ocean simulation, Ocean Model., 84, 84–103, 2014.
Lothon, M., Lohou, F., Pino, D., Couvreux, F., Pardyjak, E. R., Reuder, J., Vilà-Guerau de Arellano, J., Durand, P, Hartogensis, O., Legain, D., Augustin, P., Gioli, B., Lenschow, D. H., Faloona, I., Yagüe, C., Alexander, D. C., Angevine, W. M., Bargain, E, Barrié, J., Bazile, E., Bezombes, Y., Blay-Carreras, E., van de Boer, A., Boichard, J. L., Bourdon, A., Butet, A., Campistron, B., de Coster, O., Cuxart, J., Dabas, A., Darbieu, C., Deboudt, K., Delbarre, H., Derrien, S., Flament, P., Fourmentin, M., Garai, A., Gibert, F., Graf, A., Groebner, J., Guichard, F., Jiménez, M. A., Jonassen, M., van den Kroonenberg, A., Magliulo, V., Martin, S., Martinez, D., Mastrorillo, L., Moene, A. F., Molinos, F., Moulin, E., Pietersen, H. P., Piguet, B., Pique, E., Román-Cascón, C., Rufin-Soler, C., Sa\"id, F., Sastre-Marugán, M., Seity, Y., Steeneveld, G. J., Toscano, P., Traullé, O., Tzanos, D., Wacker, S., Wildmann, N., and Zaldei, A.: The BLLAST field experiment: Boundary-Layer Late Afternoon and Sunset Turbulence, Atmos. Chem. Phys., 14, 10931–10960, https://doi.org/10.5194/acp-14-10931-2014, 2014.
Marshall, J. and Schott, F.: Open-ocean convection: observations, theory, and models, Rev. Geophys., 37, 1–64, 1999.
Masson, V. and Seity, Y.: Including atmospheric layers in vegetation and urban offline surface schemes, J. Appl. Meteorol. Clim., 48, 1377–1397, 2009.
Masson, V., Champeaux, J.-L., Chauvin, F., Meriguet, C., and Lacaze, R.: A global database of land surface parameters at 1 km resolution in meteorological and climate models, J. Climate, 16, 1261–1282, 2003.
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.
Michel, Y., Auligné, T., and Montmerle, T.: Heterogeneous convective-scale background error covariances with the inclusion of hydrometeor variables, Mon. Weather Rev., 139, 2994–3015, 2011.
Montmerle, T. and Faccani, C.: Mesoscale assimilation of radial velocities from Doppler radars in a preoperational framework, Mon. Weather Rev., 137, 1939–1953, 2009.
Pergaud, J., Masson, V., Malardel, S., and Couvreux, F.: A parameterization of dry thermals and shallow cumuli for mesoscale numerical weather prediction, Bound.-Lay. Meteorol., 132, 83–106, 2009.
Pinty, J.-P. and Jabouille, P.: A mixed-phased cloud parameterization for use in a mesoscale non-hydrostatic model: simulations of a squall line and of orographic precipitation, in: Proceeding, Conference on Cloud Physics, Everett, WA, Amer. Meteor. Soc., pp. 217–220, 1998.
Prates, C., Richardson, D., and Sahin, C.: Final report of the PREVIEW observation Data Targeting System (DTS), ECMWF Tech Memo, p. 581, 2009.
Rainaud, R., Lebeaupin-Brossier, C., Ducrocq, V., Giordani, H., Nuret, M., Fourrié, N., Bouin, M.-N., Taupier-Letage, I., and Legain, D.: Characterization of air-sea exchanges over the Western Mediterranean Sea during the HyMeX SOP1 using the AROME-WMED model, Q. J. Roy. Meteorol. Soc., online first, https://doi.org/10.1002/qj.2480, 2015.
Ricard, D., Ducrocq, V., and Auger, L.: A Climatology of the Mesoscale Environment Associated with Heavily Precipitating Events over a Northwestern Mediterranean Area, J. Appl. Meteor. Clim., 51, 468–488, 2012.
Rotach, M., Ambrosetti, P., Ament, F., Appenzeller, C., Arpagaus, M., Bauer, H. S., Bouttier, F., Buzzi, A., Corazza, M., Davolio, S., Denhard, M., Dorninger, M., Fontannaz, L., Frick, J., Fundel, F., Germann, U., Gorgas, T., Hegg, C., Hering, A., Keil, C., Liniger, M., Marsigli, C., McTaggart-Cowan, R., Montani, A., Mylne, K., Ranzi, R., Richard, E., Rossa, A., Santos-Muoz, D., Schar, C., Seity, Y., Staudinger, M., Stoll, M., Volkert, H., Walser, A., Wang, Y., Werhahn, J., Wulfmeyer, V., and Zappa, M.: MAP-D-PHASE: real-time demonstration of weather forecast quality in the Alpine region, B. Am. Meteorol. Soc. 90, 1321–1336, 2009.
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier, F., Lac, C., and Masson, V.: The AROME-France convective scale operational model, Mon. Weather Rev., 139, 976–991, 2011.
Wattrelot, E., Caumont, O., and Mahfouf, J.-F.: Operational implementation of the 1D+3DVar assimilation method of radar reflectivity data in the AROME model, Mon. Weather Rev., 142, 1852–1873, https://doi.org/10.1175/MWR-D-13-00230.1, 2014.
Wulfmeyer, V., Behrendt, A., Bauer, H. S., Kottmeier, C., Corsmeier, U., Blyth, A., Craig, G., Schumann, U., Hagen, M., Crewell, S., DiGirolamo, P., Flamant, C., Miller, M., Montani, A., Mobbs, S., Richard, E., Rotach, M., Arpagaus, M., Russchenberg, H., Schlussel, P., Konig, M., Gartner, V., Steinacker, R., Dorninger, M., Turner, D., Weckwerth, T., Hense, A., and Simmer, C.: The convective and orographically-induced precipitation study (COPS): a research project for improving quantitative precipitation forecasting in low-mountain regions, B. Am. Meteorol. Soc., 89, 1477–1486, 2008.
Short summary
To support the instrument deployment during HyMeX, aiming at studying the high precipitation in the Mediterranean area, a dedicated version of the operational convective-scale AROME-France model was developed: the AROME-WMED model. This paper presents the main features of this numerical weather prediction system in terms of data assimilation and forecast. The forecast skill of the model is then assessed during the HyMeX special observation periods and compared to the operational AROME-France.
To support the instrument deployment during HyMeX, aiming at studying the high precipitation in...
