Ensemble Precipitation Estimation Using a Fuzzy Rule-Based Model

In this study, a Takagi-Sugeno (TS) fuzzy rule-based (FRB) model is used for ensembling precipitation time series. The TS FRB takes predictions of grid-based regional climate models (RCMs) from the EUR11 domain, available CORDEX database, as inputs to generate ensembled series two meteorological stations (MSs) in Mediterranean region Turkey. For each MS, RCM data that are at closest grid corresponding MSs used. To rules model, subtractive clustering algorithm (SC) utilized. Together with FRB, simple ensemble mean approach also applied, and performances these results individual compared. show outperform RCMs, monthly precipitation, both MSs. On other hand, although capture general trend observations, they underestimate peak events.