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At 00:00 UTC of 24 January 2009 (24Jan09) an explosive cyclogenesis placed atthe Gulf of Vizcaya, reached its maximum intensity with observed surfacepressures below 970 hPa on its center. During its path through the south ofFrance there were strong westerly and north-westerly winds over IberianPeninsula (above 150 km/h). These extreme winds leaved 8 casualties inCatalunya, the north-east region of Spain.  The aim of this work is validating the skill of the Spanish MeteorologicalAgency (AEMET) Short Range Ensemble Prediction System (SREPS) in forecastingthis event. Two probabilistic forecasts of wind are compared, anon-calibrated (or raw) and a calibrated one using the Bayesian ModelAveraging (BMA).  AEMET runs a daily experimental SREPS twice a day (00:00 and12:00 UTC). This system consists on 25 members that are constructed byintegrating five different Limited Area Models (LAMs) at 0.25 degrees ofhorizontal resolution. Each model uses five different initial and boundaryconditions from five Global Models (GMs). Thus it is obtained a probabilisticforecast that takes into account initial, contour and model uncertainties.  BMA is a statistical tool for combining predictive Probability DistributionFunctions (PDFs) from different sources. BMA predictive PDF is a weightedaverage of PDFs centered on the individual bias-corrected forecasts. Eachweight is a measure of the corresponding forecast skill. Here BMA is appliedto calibrate probabilistic forecasts of wind speed.  In this work two time forecast ranges (H+60 and H+36) of 10-m windspeed over Catalonia are verified subjectively at 12:00 UTC of 24Jan09 validtime. We focus on the location and intensity of 10-m wind speed maximumvalues. Observations at 29 automatic ground stations of AEMET are used forthe verification.  On one hand results indicate that raw AEMET-SREPS is able to forecast 60 hahead mean winds higher than 36 and 54 km/h and that it correctlylocates them in three different areas. On the other hand, predictedprobability loses its skill after BMA calibration of the ensemble. This isdue to the fact that BMA bias correction underestimates the intensity ofwind

Probabilistic prediction of raw and BMA calibrated AEMET-SREPS: the 24 of January 2009 extreme wind event in Catalunya