Articles | Volume 18, issue 22
https://doi.org/10.5194/gmd-18-8723-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-8723-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
20 Nov 2025
Methods for assessment of models |
| 20 Nov 2025
| 20 Nov 2025
On the proper use of screen-level temperature measurements in weather forecasting models over mountains
Danaé Préaux
CORRESPONDING AUTHOR
Météo-France, CNRS, Univ. Toulouse, CNRM, Toulouse, France
Ingrid Dombrowski-Etchevers
Météo-France, CNRS, Univ. Toulouse, CNRM, Toulouse, France
Isabelle Gouttevin
Météo-France, CNRS, Univ. Grenoble Alpes, Univ. Toulouse, CNRM, Centre d’Études de la Neige, 38000 Grenoble, France
Yann Seity
Météo-France, DIRSO/CMP, Foix, France
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Thomas Pauze, Axel Bouchet, Isabelle Gouttevin, Aaron Boone, Mathieu Fructus, Matthieu Lafaysse, Erwan Le Gac, Agnès Rivière, and Yves Lejeune
EGUsphere, https://doi.org/10.5194/egusphere-2026-4137, https://doi.org/10.5194/egusphere-2026-4137, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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In mid-altitude mountainous areas, snow acts as a water reservoir and is impacted by forest: to represent it we use a model called MEB/Crocus. It has been developed in boreal forests. Its results at a mid-altitude alpine site (the Col de Porte) were not convincing. We modify parametrizations that govern the behavior of intercepted snow to have a more realistic representation. We improve results of simulated snowpack under forest at Col de Porte and do not change performance in boreal sites.
Olivier Champagne, Flora Branger, Anthony Lemoine, Jordi Bolibar, Louise Mimeau, Gilles Delaygue, Isabelle Gouttevin, Sophie Cauvy-Fraunié, and Thomas Condom
EGUsphere, https://doi.org/10.5194/egusphere-2026-3523, https://doi.org/10.5194/egusphere-2026-3523, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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This study using a hydrological model shows the projections of icemelt contribution to streamflow until the end of the century in many rivers in the Rhône basin. The results show a streamflow decrease in summer, due to the decrease of precipitations, snowmelt, and glacier melt. In many catchments, icemelt will completely disappear by the end of the century. In the Arve and highly glaciated catchments of the upper Rhône, icemelt will remains sufficiently large to sustain streamflow in summer.
Giulia Mazzotti, Félix Vaccaro, Antoine Courteaud, Mathieu Fructus, Jan Magnusson, Isabelle Gouttevin, Jari-Pekka Nousu, and Matthieu Lafaysse
EGUsphere, https://doi.org/10.5194/egusphere-2026-1464, https://doi.org/10.5194/egusphere-2026-1464, 2026
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This study evaluates spatial simulations with the new snow model MEB-Crocus over mountainous, forested terrain. In lack of forest snow observations over large areas, simulations are assessed against simulations with the state-of-the art model FSM2oshd. Results show that the data characterizing the vegetation is as important for model performance as the mathematical description of physical processes. These insights inform future improvements of MEB-Crocus for its application to alpine regions.
Oriol Pomarol Moya, Madlene Nussbaum, Siamak Mehrkanoon, Philip D. A. Kraaijenbrink, Isabelle Gouttevin, Derek Karssenberg, and Walter W. Immerzeel
The Cryosphere, 20, 1427–1444, https://doi.org/10.5194/tc-20-1427-2026, https://doi.org/10.5194/tc-20-1427-2026, 2026
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Two hybrid Machine Learning (ML) approaches predicting daily Snow Water Equivalent (SWE) were evaluated across ten Northern Hemisphere sites. By integrating meteorological data with Crocus snow model simulations, these hybrid models outperformed both standalone Crocus and traditional ML models. Notably, augmenting measured SWE data with Crocus simulations significantly improved performance at unseen locations, offering a promising new approach to long-term SWE prediction.
Louis Le Toumelin, Isabelle Gouttevin, Clovis Galiez, and Nora Helbig
Nonlin. Processes Geophys., 31, 75–97, https://doi.org/10.5194/npg-31-75-2024, https://doi.org/10.5194/npg-31-75-2024, 2024
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Forecasting wind fields over mountains is of high importance for several applications and particularly for understanding how wind erodes and disperses snow. Forecasters rely on operational wind forecasts over mountains, which are currently only available on kilometric scales. These forecasts can also be affected by errors of diverse origins. Here we introduce a new strategy based on artificial intelligence to correct large-scale wind forecasts in mountains and increase their spatial resolution.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Marie Dumont, Simon Gascoin, Marion Réveillet, Didier Voisin, François Tuzet, Laurent Arnaud, Mylène Bonnefoy, Montse Bacardit Peñarroya, Carlo Carmagnola, Alexandre Deguine, Aurélie Diacre, Lukas Dürr, Olivier Evrard, Firmin Fontaine, Amaury Frankl, Mathieu Fructus, Laure Gandois, Isabelle Gouttevin, Abdelfateh Gherab, Pascal Hagenmuller, Sophia Hansson, Hervé Herbin, Béatrice Josse, Bruno Jourdain, Irene Lefevre, Gaël Le Roux, Quentin Libois, Lucie Liger, Samuel Morin, Denis Petitprez, Alvaro Robledano, Martin Schneebeli, Pascal Salze, Delphine Six, Emmanuel Thibert, Jürg Trachsel, Matthieu Vernay, Léo Viallon-Galinier, and Céline Voiron
Earth Syst. Sci. Data, 15, 3075–3094, https://doi.org/10.5194/essd-15-3075-2023, https://doi.org/10.5194/essd-15-3075-2023, 2023
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Saharan dust outbreaks have profound effects on ecosystems, climate, health, and the cryosphere, but the spatial deposition pattern of Saharan dust is poorly known. Following the extreme dust deposition event of February 2021 across Europe, a citizen science campaign was launched to sample dust on snow over the Pyrenees and the European Alps. This campaign triggered wide interest and over 100 samples. The samples revealed the high variability of the dust properties within a single event.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
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Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
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Short summary
Air temperature is usually measured around 2 m above the ground following meteorological standards. However, in mountain regions, temperature sensors are often placed higher up to avoid being buried in snow in winter. We show that the measurement height is of high importance when quantifying the errors made by weather prediction models. Also, it should be accounted for when these observations are used to correct the models in real time, as doing otherwise degrades their forecasts at high altitudes.
Air temperature is usually measured around 2 m above the ground following meteorological...
