Articles | Volume 20, issue 8
https://doi.org/10.5194/tc-20-4605-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-4605-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Aug 2026
Research article |
| 21 Aug 2026
| 21 Aug 2026
On the reliability of seasonal snow forecasts
NILU, Kjeller, Norway
Yvan Orsolini
NILU, Kjeller, Norway
Patricia de Rosnay
European Centre for Medium‐Range Weather Forecasts, Reading, UK
Jonathan Day
European Centre for Medium‐Range Weather Forecasts, Reading, UK
Retish Senan
European Centre for Medium‐Range Weather Forecasts, Reading, UK
Damien Decremer
European Centre for Medium‐Range Weather Forecasts, Reading, UK
Frederic Vitart
European Centre for Medium‐Range Weather Forecasts, Reading, UK
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Steve Delhaye, Thierry Fichefet, François Massonnet, David Docquier, Rym Msadek, Svenya Chripko, Christopher Roberts, Sarah Keeley, and Retish Senan
Weather Clim. Dynam., 3, 555–573, https://doi.org/10.5194/wcd-3-555-2022, https://doi.org/10.5194/wcd-3-555-2022, 2022
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It is unclear how the atmosphere will respond to a retreat of summer Arctic sea ice. Much attention has been paid so far to weather extremes at mid-latitude and in winter. Here we focus on the changes in extremes in surface air temperature and precipitation over the Arctic regions in summer during and following abrupt sea ice retreats. We find that Arctic sea ice loss clearly shifts the extremes in surface air temperature and precipitation over terrestrial regions surrounding the Arctic Ocean.
Eduardo Moreno-Chamarro, Louis-Philippe Caron, Saskia Loosveldt Tomas, Javier Vegas-Regidor, Oliver Gutjahr, Marie-Pierre Moine, Dian Putrasahan, Christopher D. Roberts, Malcolm J. Roberts, Retish Senan, Laurent Terray, Etienne Tourigny, and Pier Luigi Vidale
Geosci. Model Dev., 15, 269–289, https://doi.org/10.5194/gmd-15-269-2022, https://doi.org/10.5194/gmd-15-269-2022, 2022
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Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
Martin Wegmann, Yvan Orsolini, Antje Weisheimer, Bart van den Hurk, and Gerrit Lohmann
Weather Clim. Dynam., 2, 1245–1261, https://doi.org/10.5194/wcd-2-1245-2021, https://doi.org/10.5194/wcd-2-1245-2021, 2021
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Northern Hemisphere winter weather is influenced by the strength of westerly winds 30 km above the surface, the so-called polar vortex. Eurasian autumn snow cover is thought to modulate the polar vortex. So far, however, the modeled influence of snow on the polar vortex did not fit the observed influence. By analyzing a model experiment for the time span of 110 years, we could show that the causality of this impact is indeed sound and snow cover can weaken the polar vortex.
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Short summary
How reliable are probabilistic seasonal snow forecasts in winter? Although they are routinely issued by operational prediction centres, their reliability has never been evaluated. We close this gap by analyzing 30 years of seasonal snow re-forecasts and evaluating them against two snow datasets. Our results provide comprehensive assessment of seasonal snow forecast reliability and offer new insights into their performance in different parts of the Northern Hemisphere.
How reliable are probabilistic seasonal snow forecasts in winter? Although they are routinely...
