Radar-based quantitative precipitation estimation over arid, semi- arid and Mediterranean climate regimes in Israel

1 Introduction Accurate quantitative precipitation estimation (QPE) is one of the most important elements in meteorological and hydrologic analyses. It has been long recognized, however, that rain gauge networks are usually inadequate because of their limited distribution. During the last decades intense scientific efforts have been devoted to utilize remote sensing information for the estimation of high resolution precipitation data over large areas. Ground meteorological radar systems are the most common source of this information. Radar-based QPE are subject to several sources of errors. Among them is the effect of topography causing ground clutter contamination and beam blockage, especially in mountainous regions, beam broadening and its increasing altitude above ground with distance, and gradients of vertical reflectivity profiles. Several methods were proposed how to combine radar and gauge data to generate precipitation estimates with reduced levels of error. The simplest approach adjusts radar estimates by removing the mean bias (e.g., Krajewski and Smith, 2000). For regions with complex terrain, Gabella et al. (2000) suggested radar-gauge adjustment using the weighted multiple regression (WMR) method. While a considerable number of papers deal with radar-based precipitation estimation in temperate climatic regimes, few have covered semi-arid and arid regions (e.g., Morin et al., 2005). In these dry regions rainstorms are often local and highly variable while rain gauge networks are very scarce. The objective of the current study is to examine methods for radar-based QPE of storm rain depth for Israel, where the climate ranges from Mediterranean to semi-arid and arid types. This goal is achieved using radar-gauge training and validation procedures applied to a five year data record.