Analysing seasonal snow cover trends and patterns on Svalbard

Sammanfattning: Rapid warming in the Arctic is highly impacting the cryosphere in the region, causing melting of the sea ice, retreat of glaciers and reduction in the snow cover. If suffering further temperature increase, the albedo of the region would reduce due to higher absorption of the solar radiation in snow-free areas. The variations in seasonal snow cover in Arctic regions can impact a lot of things including the ecosystem, biodiversity, hydrological cycle, and many other physical processes. Therefore, it is beneficial to have the knowledge of processes determining the snow distribution and to understand the trends and patterns of the seasonal snowcover.In this project, seasonal snow cover trends and patterns have been studied for a 30-year period from 1991 to 2020 using a newly developed reanalysis dataset called Copernicus Arctic Regional Reanalysis (CARRA). A validation of the CARRA data set has been done for the snow depth using point observation data from the Norwegian weather stations and a visual snow cover comparison using Sentinel-2 remote sensing data. Thereafter, interannual variability in day of snow disappearance, day of snow onset, duration of snow-free period, and maximum snow depth have been analysed and these trends are then discussed in detail.The results show that for the most non-glaciated regions in Svalbard, the snow onset is happening later in the winter season while the day of snow disappearance is arriving earlier in the spring. Consequently, the duration of snow-free period has increased in almost all regions of Svalbard except a few sites where the duration of the snow free-period has decreased most likely due to local climatic factors. These factors can be better understood by incorporating meteorological elements like precipitation, air temperature and wind speed. Overall, the CARRA reanalysis dataset is very good in determining snow cover trends in non- glaciated regions of Svalbard and with some updates and modifications, it might be able to determine snowcover for the glaciated regions in future.