A cluster space calibration scheme for synthetic wind statistics calculated with a mesoscale model and its application to regional wind climate studies

A scheme for calibrating an ensemble of wind fields computed by a mesoscale model in order to generate synthetic wind statistics is described. It is b ased on two main points. The first is to exploit the power of a mesoscale m odel to determine wind fields over complex terrain for different weather si tuations classified by cluster analysis. The second is to use all the infor mation in the cluster analysis, i.e., the centroid values as well as the in fernal standard deviations of the clusters, to determine a cluster space di stribution at each grid point in the model domain. The latter makes calibra tion possible if reliable measurements are available at the position of one of the grid points. The accuracy of the calibration is increased by splitt ing the cluster spaces into several parts. Combining both the modelled meso scale wind fields and the method of split cluster spaces leads to a spatial transformation of the calibration from the calibration point to each grid point in the model domain. A validation of the scheme is carried out with m easurements at grid points other than the calibration point and reveals rem arkable improvements in the accuracy of the model wind statistics, especial ly with regard to wind speed distributions.