Daily wind gust speed probabilities over Switzerland according to three types of synoptic circulation

The nowcasting and prediction of strong winds are still far from adequate, using either statistical or numerical modelling 7 17 approaches. During the last decade, Switzerland has been struck by two extratropical storms, namely the February 1990 storm 'Vivian'. and the December 1999 storm 'Lothar', that caused severe damage to infrastructure and to forests, Although numerical weather prediction models captured in both cases the cyclone tracks on the synoptic scale, the severity of local crusts was not properly predicted over the Swiss territory. To help predicting such phenomena, a combined approach to diagnose the wind gust speed,., over Switzerland is described. The diagnostics aim at computing the probability of exceeding a gust speed based on the mean wind in relation to the prevailing synoptic weather type for a limited number of groups of climatological stations distributed throughout Switzerland. Based on 10 years of Swiss station observations. the computation of this probability uses an empirical gust factor that is a function of the daily gust speed. itself a function of the daily mean wind speed. For this period. each day has been categorized into three weather types according to the Schuepp classification. Principal component analysis and cluster analysis are performed in order to group climatological stations having similar characteristics in daily wind gust velocities. The results show that the oust factor provides an accurate method to compute the daily wind oust speeds at each Swiss climatological station for the Given period. When combined with the three weather type,, and group of stations, the proposed diagnostics are an efficient method to predict the distribution of wind gust speeds. The gusts associated with the 'Vivian' and 'Lothar' storms are then diagnosed for each specific group where more than 85% of the stations responded similarly to their specific group members, which is highly satisfactory in this case. Copyright (C) 2002 Royal Meteorological Society.