Articles | Volume 19, issue 12
https://doi.org/10.5194/tc-19-6907-2025
© 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/tc-19-6907-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Dec 2025
Research article |
| 19 Dec 2025
| 19 Dec 2025
Recent and projected changes in rain-on-snow event characteristics across Svalbard
Hannah Vickers
CORRESPONDING AUTHOR
NORCE Norwegian Research Centre, Bergen, Norway
Priscilla Mooney
NORCE Norwegian Research Centre, Bergen, Norway
Oskar Landgren
Norwegian Meteorological Institute, Oslo, Norway
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Manuscript not accepted for further review
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Rain-on-snow (ROS) events are becoming more frequent as a result of a warming climate, and can have significant impacts on nature and society. Accurate representation of ROS events is need to identify where impacts are greatest both now and in the future. We compare rain-on-snow climatologies from a climate model, ground and satellite radar observations and show how different methods can lead to contrasting conclusions and interpretation of the results should take into account their limitations.
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Cited articles
Bartsch, A., Bergstedt, H., Pointner, G., Muri, X., Rautiainen, K., Leppänen, L., Joly, K., Sokolov, A., Orekhov, P., Ehrich, D., and Soininen, E. M.: Towards long-term records of rain-on-snow events across the Arctic from satellite data, The Cryosphere, 17, 889–915, https://doi.org/10.5194/tc-17-889-2023, 2023.
Belušić, D., de Vries, H., Dobler, A., Landgren, O., Lind, P., Lindstedt, D., Pedersen, R. A., Sánchez-Perrino, J. C., Toivonen, E., van Ulft, B., Wang, F., Andrae, U., Batrak, Y., Kjellström, E., Lenderink, G., Nikulin, G., Pietikäinen, J.-P., Rodríguez-Camino, E., Samuelsson, P., van Meijgaard, E., and Wu, M.: HCLIM38: a flexible regional climate model applicable for different climate zones from coarse to convection-permitting scales, Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, 2020.
Day, J. J., Bamber, J. L., Valdes, P. J., and Kohler, J.: The impact of a seasonally ice free Arctic Ocean on the temperature, precipitation and surface mass balance of Svalbard, The Cryosphere, 6, 35–50, https://doi.org/10.5194/tc-6-35-2012, 2012.
Dobler, A., Lutz, J., Landgren, O., and Haugen, J. E.: Circulation Specific Precipitation Patterns over Svalbard and Projected Future Changes, Atmosphere, 11, 1378, https://doi.org/10.3390/atmos11121378, 2020.
Forbes, B. C., Kumpula, T., Meschtyb, N., Laptander, R., Macias-Fauria, M., Zetterberg, P., Verdonen, M., Skarin, A., Kim, K. Y., Boisvert, L. N., Stroeve, J. C., and Bartsch, A.: Sea ice, rain-on-snow and tundra reindeer nomadism in Arctic Russia, Biology Letters, 12, 20160466, https://doi.org/10.1098/rsbl.2016.0466, 2016.
Førland, E. J., Benestad, R. E., Hanssen-Bauer, I., Haugen, J. E., and Skaugen, T. E.: Temperature and Precipitation Development at Svalbard 1900–2100, Adv. Meteor., 2011, 1–14, https://doi.org/10.1155/2011/893790, 2011.
Gutjahr, O., Putrasahan, D., Lohmann, K., Jungclaus, J. H., von Storch, J.-S., Brüggemann, N., Haak, H., and Stössel, A.: Max Planck Institute Earth System Model (MPI-ESM1.2) for the High-Resolution Model Intercomparison Project (HighResMIP), Geosci. Model Dev., 12, 3241–3281, https://doi.org/10.5194/gmd-12-3241-2019, 2019.
Hansen, B. B., Isaksen, K., Benestad, R. E., Kohler, J., Pedersen, Å. Ø., Loe, L. E., Coulson, S. J., Larsen, J. O., and Varpe, Ø.: Warmer and wetter winters: Characteristics and implications of an extreme weather event in the High Arctic, Environmental Research Letters, 9, 114021, https://doi.org/10.1088/1748-9326/9/11/114021, 2014.
Hanssen-Bauer, I., Førland, E. J., Hisdal, H., Mayer, S., Sandø, A. B., and Sorteberg, A.: Climate in Svalbard 2100, NCCS Rep. 1/2019, 205 pp., https://www.miljodirektoratet.no/globalassets/publikasjoner/M1242/M1242.pdf (last access: 17 December 2025), 2019.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Innanen, S., Hock, R., Schmidt, L. S., Schuler, T. V., Covi, F., and Moholdt, G.: Witnessing the transition from cold to temperate firn on Austfonna ice cap, Svalbard through observations and model simulations, J. Glaciology, 71, e101, https://doi.org/10.1017/jog.2025.10072, 2025.
Isaksen, K., Nordli, Ø., Førland, E. J., Łupikasza, E., Eastwood, S., and Niedźwiedź, T.: Recent warming on Spitsbergen – Influence of atmospheric circulation and sea ice cover, J. Geophys. Res. Atmos., 121, 11913–11931, https://doi.org/10.1002/2016JD025606, 2016.
Isaksen, K., Førland, E. J., Dobler, A., Benestad, R., Haugen, J. E., and Mezghani, A.: Klimascenarioer for Longyearbyen-området, Svalbard, MET Norway Report 15/2017, https://www.met.no/publikasjoner/met-report/met-report-2017/ (last access: 17 December 2025), 2017.
Isaksen, K., Nordli, Ø., Ivanov, B., Køltzow, M. A. Ø., Aaboe, S., Gjelten, H. M., Mezghani, A., Eastwood, S., Førland, E., Benestad, R.E., Hanssen-Bauer, I., Brækkan, R., Sviashchennikov, P., Demin, V., Revina, A., and Karandasheva, T.: Exceptional warming over the Barents area, Sci. Rep., 12, 9371, https://doi.org/10.1038/s41598-022-13568-5, 2022.
Køltzow, M., Casati, B., Bazile, E., Haiden, T., and Valkonen, T.: An NWP model intercomparison of surface weather parameters in the European Arctic during the year of polar prediction special observing period Northern Hemisphere 1, Weather Forecast., 34, 959–983, https://doi.org/10.1175/WAF-D-19-0003.1, 2019.
Køltzow, M., Schyberg, H., Støylen, E., and Yang, X.: Value of the Copernicus Arctic Regional Reanalysis (CARRA) in representing near-surface temperature and wind speed in the north-east European Arctic, Polar Res., 41, 8002, https://doi.org/10.33265/polar.v41.8002, 2022.
Landgren, O., Lutz, J., and Isaksen, K.: 2.5 km future climate projections for Svalbard under the high emission scenario SSP5-8.5, MET Report 1/2025, https://doi.org/10.5281/zenodo.17099386, 2025.
Levine, X. J., Williams, R. S., Marshall, G., Orr, A., Seland Graff, L., Handorf, D., Karpechko, A., Köhler, R., Wijngaard, R. R., Johnston, N., Lee, H., Nieradzik, L., and Mooney, P. A.: Storylines of summer Arctic climate change constrained by Barents–Kara seas and Arctic tropospheric warming for climate risk assessment, Earth Syst. Dynam., 15, 1161–1177, https://doi.org/10.5194/esd-15-1161-2024, 2024.
Łupikasza, E. B., Ignatiuk. D., Grabiec, M., Cielecka-Nowak, K., Laska, M., Jania, J., Luks, B., Uszczyk, A., and Budzik, T.: The Role of Winter Rain in the Glacial System on Svalbard, Water, 11, 334, https://doi.org/10.3390/w11020334, 2019.
Mooney, P. A. and Li, L.: Near future changes to rain-on-snow events in Norway, Environ. Res. Lett., 16, 064039, https://doi.org/10.1088/1748-9326/abfdeb, 2021.
Mooney, P. A., Sobolowski, S., and Lee, H.: Designing and evaluating regional climate simulations for high latitude land use land cover change studies, Tellus Dyn. Meteorol. Oceanogr., 72, 1–17, 2020.
Onarheim, I. H., Smedsrud, L. H., Ingvaldsen, R. B., and Nilsen, F.: Loss of sea ice during winter north of Svalbard, Tellus A: Dynamic Meteorology and Oceanography, 66, https://doi.org/10.3402/tellusa.v66.23933, 2014.
Pedersen Å. Ø., Beumer, L. T., Aanes, R., and Hansen, B. B.: Sea or summit? Wild reindeer spatial responses to changing hgh-arctic winters, Ecosphere, 12, e03883, https://doi.org/10.1002/ecs2.3883, 2021.
Peeters, B., Pedersen, Å. Ø., Loe, L. E., Isaksen, K., Veiberg, V., Stien, A., Kohler, J., Gallet, J. C., Aanes, R., and Hansen, B. B.: Spatiotemporal patterns of rain-on-snow and basal ice in high Arctic Svalbard: Detection of a climate-cryosphere regime shift, Environmental Research Letters, 14, 015002, https://doi.org/10.1088/1748-9326/aaefb3, 2019.
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S., Schmidli, J., van Lipzig, N. P .M., and Leung, R.: A review on regional convection-permitting climate modeling: demonstrations, prospects, and challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015.
Rantanen, M., Karpechko, A.Y., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., Vihma, T., and Laaksonen, A.: The Arctic has warmed nearly four times faster than the globe since 1979, Commun Earth Environ 3, 168, https://doi.org/10.1038/s43247-022-00498-3, 2022.
Schyberg, H., Yang, X., Køltzow, M. A. Ø., Amstrup, B., Bakketun, Å., Bazile, E., Bojarova, J., Box, J. E., Dahlgren, P., Hagelin, S., Homleid, M., Horányi, A., Høyer, J., Johansson, Å., Killie, M. A., Körnich, H., Le Moigne, P., Lindskog, M., Manninen, T., Nielsen Englyst, P., Nielsen K. P., Olsson, E., Palmason, B., Peralta Aros, C., Randriamampianina, R., Samuelsson, P., Stappers, R., Støylen, E., Thorsteinsson, S., Valkonen, T., and Wang, Z. Q.: Arctic regional reanalysis on single levels from 1991 to present, Copernicus Climate Change Service, https://doi.org/10.24381/cds.713858f6, 2020.
Screen, J. A. and Simmonds, I.: Increasing fall-winter energy loss from the Arctic Ocean and its role in Arctic temperature amplification, Geophys. Res. Lett., 37, L16707, https://doi.org/10.1029/2010GL044136, 2010.
Serreze, M., Gustafson, J., Barrett, A. P., Druckenmiller, M. L., Fox, S., Voveris, J., Stroeve, J., Sheffield, B., Forbes, B. C., Rasmus, S., Laptander, R., Brook, M., Brubaker, M., Temte, J., McCrystall, M. R., and Bartsch, A.: Arctic rain on snow events: bridging observations to understand environmental and livelihood impacts, Environmental Research Letters, 16, https://doi.org/10.1088/1748-9326/ac269b, 2021.
Sobota, I., Weckwerth, P., and Grajewski, T.: Rain-On-Snow (ROS) events and their relations to snowpack and ice layer changes on small glaciers in Svalbard, the high Arctic, Journal of Hydrology, 590, 125279, https://doi.org/10.1016/j.jhydrol.2020.125279, 2020.
Spolaor, A., Salzano, R., Scoto, F., Barbaro, E., Luks, B., Laska, M., Sobota, I., Maetze, R., Malnes, E., Vickers, H., Larose, C., Dahlke, S., and Maturilli, M.: Understanding and analysing recurrent warm events in Svalbard: a comprehensive review on land cryosphere (AWARE), SESS report 2024 – The State of Environmental Science in Svalbard – an annual report, 212–226, Svalbard Integrated Arctic Earth Observing System, https://doi.org/10.5281/zenodo.14425903, 2025.
Van Pelt, W. J. J., Kohler, J., Liston, G. E., Hagen, J. O., Luks, B., Reijmer, C. H., and Pohjola, V. A.: Multidecadal climate and seasonal snow conditions in Svalbard, J. Geophys. Res. Earth Surf., 121, 2100–2117, https://doi.org/10.1002/2016JF003999, 2016.
Vickers, H., Malnes, E., and Eckerstorfer, M.: A Synthetic Aperture Radar Based Method for Long Term Monitoring of Seasonal Snowmelt and Wintertime Rain-On-Snow Events in Svalbard, Front. Earth Sci., 10, 868945, https://doi.org/10.3389/feart.2022.868945, 2022.
Vickers, H., Saloranta, T., Køltzow, M., van Pelt Ward, J. J., and Malnes, E.: An analysis of winter rain-on-snow climatology in Svalbard, Front. Earth Sci., 12, https://doi.org/10.3389/feart.2024.1342731, 2024.
Vonnahme, T. R., Nowak, A., Hopwood, M. J., Meire, L., Søgaard, D. H., Krawczyk, D., Kalhagen, K., and Juul-Pedersen, T.: Impact of winter freshwater from tidewater glaciers on fjords in Svalbard and Greenland; A review, Progress in Oceanography, 219, 103144, https://doi.org/10.1016/j.pocean.2023.103144, 2023.
Wang, F.: An introduction to the HARMONIE-Climate (HCLIM) regional climate modeling system, Zenodo, https://doi.org/10.5281/zenodo.11424181, 2024.
Wickström, S., Jonassen, M. O., Cassano, J. J., and Vihma, T.: Present temperature, precipitation, and rain-on-snow climate in Svalbard, Journal of Geophysical Research: Atmospheres, 125, https://doi.org/10.1029/2019JD032155, 2020.
Würzer, S., Jonas, T., Wever, N., and Lehning, M.: Influence of initial snowpack properties on runoff formation during rain-on-snow events, J. Hydrometeor., 17, 1801–1815, https://doi.org/10.1175/JHM-D-15-0181.1, 2016.
Zhang, R., Wang, H., Fu, Q., Rasch, P. J., Wu, M., and Maslowski, W.: Understanding the cold season Arctic surface warming trend in recent decades, Geophysical Research Letters, 48, https://doi.org/10.1029/2021GL094878, 2021
Short summary
Rain-on-snow (ROS) events are becoming a common feature in winter in Svalbard due to climate warming. Understanding how ROS events are changing and how they will change in the coming decades is crucial to minimise their impacts. Using atmospheric reanalyses and climate projections we found contrasting trends between coastal and inland areas, and that the most dramatic future changes in ROS will occur in glaciated areas which will have considerable consequences for Svalbard's hydrology.
Rain-on-snow (ROS) events are becoming a common feature in winter in Svalbard due to climate...
