A multiscale approach for precipitation verification applied to the FORALPS case studies

Abstract

Abstract. Multiscale methods, such as the power spectrum, are suitable diagnostic tools for studying the second order statistics of a gridded field. For instance, in the case of Numerical Weather Prediction models, a drop in the power spectrum for a given scale indicates the inability of the model to reproduce the variance of the phenomenon below the correspondent spatial scale. Hence, these statistics provide an insight into the real resolution of a gridded field and must be accurately known for interpolation and downscaling purposes. In this work, belonging to the EU INTERREG IIIB Alpine Space FORALPS project, the power spectra of the precipitation fields for two intense rain events, which occurred over the north-eastern alpine region, have been studied in detail. A drop in the power spectrum at the shortest scales (about 30 km) has been found, as well as a strong matching between the precipitation spectrum and the spectrum of the orography. Furthermore, it has also been shown how the spectra help understand the behavior of the skill scores traditionally used in Quantitative Precipitation Forecast verification, as these are sensitive to the amount of small scale detail present in the fields.