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Detailed long-term hydrometeorological dataset for Russian Arctic seas was created using hydrodynamic modelling via regional nonhydrostatic atmospheric model COSMO-CLM for 1980 – 2016. Article presents the long-term experiments evaluation techniques and primary analysis of obtained dataset. Experiments were conducted for model domain including Barents, Kara and Laptev seas, with ~12 km grid. Many test experiments were evaluated to determine the best model configuration, which included the new model version 5.06, “spectral nudging” technique and ERA-Interim reanalysis as forcing data. Reinitialization scheme of an additional “assimilation” of soil properties reanalysis data was suggested to avoid possible errors increment, particularly due to soil draining in the model. Primary assessment has shown that wind speed climatology based on COSMO-CLM experiments is very close to the ERA-Interim pattern, besides many details of wind speed distribution at different Arctic regions. At the same time, high wind speed frequencies based on COSMO-CLM data were increased compared to ERA-Interim, especially over Barents Sea, Arctic islands (Novaya Zemlya) and some seacoasts and mainland areas. Regional details are manifested in wind speed increase and marked well for large lakes, orography, as well over polar region (up to 0.5 – 1 m/s). At the same time, there are mesoscale wind speed decreasing compared to ERA-Interim data over Pechora and Laptev Sea coasts, New Siberian islands. Comparison of two periods (1980 ¬¬– 1990 and 2010 – 2016) has shown that spatial distributions of high wind speed frequencies are very similar, but there are some detailed differences. Wind speed frequencies above 17.2 and 20.8 m/s has been decreased in the last decade over the Novaya Zemlya, southwest from Svalbard and northern Atlantic, middle Siberia continent; at the same time, it has been increased over between Franz Josef Land and Severnaya Zemlya, and in polar regions. Preliminary assessment of modeling results revealed that it is promising for analysis of regional wind speed regime and severe wind speed risks estimations. The next step of this work is to run simulations at 3 km grid and collaborate with scientific community to use this dataset sufficiently.