Abstract: Ice cover is one of the main parameters describing the state of various water areas. The simplicity of calculation determines the frequency of using the indicator in research both for reading the seasonal course and interannual changes in the state of the ice cover and for verifying model data or reanalysis data. In this paper, ice cover is calculated based on five data sources. The comparison is based on satellite data from the NSIDC DAAC archives (October 26, 1978, to March 31, 2023; spatial resolution is 25 × 25 km, temporal resolution is 1 day; the data were collected by SMMR, SSM/I, and SSMI/S sensors on the DMSP program satellites, as well as the Nimbus-7 satellite and OSISAF (product code OSI-401-d; March 1, 2005, to present; spatial resolution is 10 × 10 km and temporal resolution is 1 day; the data were collected by the SSMI/S sensor on the DMSP program satellites). Model data from the international CMIP (Coupled Model Intercomparison Project) project are used for comparison and verification. Of the more than 40 models of the sixth phase of the project, two were selected that provided the necessary data and were suitable in terms of spatial and temporal resolution: MPI-ESM1-2-HR and AWI-CM-1-1-MR of the Max Planck Institute and the Alfred Wegener Institute, respectively. For all obtained coverage series, the mean, standard deviation, range, correlation intervals, trend coefficients, and standard error were estimated relative to the NSIDC series for the data intersection period of September 19, 2016 to June 31, 2023, in each of the Russian Arctic seas, as well as for the water area as a whole. Using the statistical characteristics, satellite data on ice cover were compared with the results of modeling in accordance with different socioeconomic trajectories (Shared Socioeconomic Pathways (SSPs)) for both models, the quality of ice cover modeling was assessed, and scenarios were selected that most closely matched the satellite data for both the entire Russian Arctic water area and for individual seas. Based on the optimal scenarios, possible changes in ice content were predicted. © Pleiades Publishing, Ltd. 2025.