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This work presents the variation in the spatial distribution of atmospheric precipitation determined by means of multidimensional analyses. Precipitation data observed at nine stations of the Institute of Meteorology and Water Management (IMGW) located in central-eastern Poland in the period 1971–2005 are analyzed. Precipitation periodicity index was calculated for each station (measurement point). The index was subjected to descriptive analysis by calculating the average value for the long-term period and the average rate of change. Multidimensional analyses were used to examine the spatial differentiation of precipitation variation. Periodicity indexes in months associated with the first and second principal component were found to account for over 70% variation between the measurement points. The months were as follows: April, May, July, and October. Cluster analysis was performed based on principal components, and it yielded three groups of measurement points with different distribution of precipitation periodicity indexes. The first group consisted of localities characterized by a low precipitation periodicity index in July and October. The second cluster included measurement points which had the lowest precipitation periodicity in May, June, August, and September. The third cluster was formed by only one locality (Białowieża), whose precipitation periodicity index was the highest in every month of the growing season. Both principal component analysis and cluster analysis may be used for an assessment of spatial variation of precipitation periodicity. Their results agree with findings based on the method of isoline interpolation. Key-words: precipitation periodicity index, multidimensional analysis, variation, spatial distribution

Statistical and geostatistical analysis of spatial variation of precipitation periodicity in the growing season