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We used principal component analysis (PCA) to derive climate indices that describe the main spatial features of the climate in the Baltic States (Estonia, Latvia and Lithuania). Monthly mean temperature and total precipitation values derived from the ensemble of bias-corrected regional climate models (RCM) were used. Principal components were derived for years 1961–1990. The first three components describe 92 % of the variance of the initial data and were chosen as climate indices in further analysis. Spatial patterns of these indices and their correlation with the initial variables were analyzed and it was observed that higher values of each index corresponded to: (1) less distinct seasonality, (2) warmer and (3) wetter climate. The loadings from the chosen principal components were then further used to calculate values of the climate indices for years 2071–2100. Overall increase was found for all three indices with minimal changes in their spatial pattern.