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This paper examines some of the physical mechanisms and remote linkages associated with extreme wintertime precipitation in the Balkans. The analysis is assessed on daily timescales to determine the role of the circulation and atmospheric moisture on extreme events, and also at intraseasonal and interannual timescales to find possible linkages with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) patterns. A nonlinear classification known as the self-organizing map (SOM) is employed to obtain the climate modes and anomalies that dominated during the 1980–93 period. An artificial neural network (ANN) is also used to derive daily precipitation at gridpoint scale and at local scale in Bucharest, Romania. Of the predictors used, 500–1000-hPa thickness, 700-hPa geopotential heights, and 700-hPa moisture are the most important controls of daily precipitation. These results are substantiated with the climate states from the SOM classification, which show strong meridional flow over c...

Using Self-Organizing Maps to Investigate Extreme Climate Events: An Application to Wintertime Precipitation in the Balkans