Evaluation of an air pressure based proxy for storm activity

Abstract

Yearly percentiles of geostrophic wind speeds serve as a widely used proxy for assessing past storm activity. Here, daily geostrophic wind speeds are derived from a geographical triangle of surface air pressure measurements and are used to build yearly frequency distributions. It is commonly believed, however unproven, that the variation of the statistics of strong geostrophic wind speeds describes the variation of statistics of ground level wind speeds. The study evaluates this approach by examining the correlation between specific annual (seasonal) percentiles of geostrophic and of area-maximum surface wind speeds to determine whether the two distributions are linearly linked in general. The analyses rely on bootstrap and binomial hypothesis testing, as well as on analysis of variance. Such investigations require long, homogeneous, and physically consistent data. As such data are barely existent, regional climate model generated wind and surface air pressure fields in a fine spatial and temporal resolution are made use of. The chosen regional climate model is the spectrally nudged and NCEP driven REMO that covers Europe and the North Atlantic. Required distributions are determined from diagnostic 10m and geostrophic wind speed, which is calculated from model air pressure at sea level. Obtained results show that the variation of strong geostrophic wind speed statistics describes the variation of ground level wind speed statistics. Annual and seasonal quantiles of geostrophic wind speed and ground level wind speed are positively linearly related. The influence of lowpass filtering is also considered and found to decrease the quality of the linear link. Moreover, several factors are examined that affect the description of storminess through geostrophic wind speed statistics. Geostrophic wind from sea triangles reflects storm activity better than geostrophic wind from land triangles. Smaller triangles lead to a better description of storminess than bigger triangles.