The article describes a method of mapping climatic parameters (i. e. frequency and intensity) of severe weather events, based on the interpolation of weather station data. We applied regression-based interpolation, using some geographical variables (altitude, slope angle and curvature) for modeling their spatial distribution. Statistically significant correlations between geographical and climatic variables were selected based on regression analysis. They have been used to create a maps of frequency, average and maximum intensity of severe weather events for Perm region (160 600 km2). The proposed method allows to create more accurate and detailed maps of spatial distribution of severe weather events than traditional deterministic and geostatistical interpolation methods. The reliability of the results confirmed by a weather station observations and comparisons with MODIS satellite images thematic products. Significant advantage of proposed method is also its applicability to the risk assessment of severe weather events in ungauged site, or in ungauged areas.