Investigation of summertime convective rainfall in Western Europe based ona synergy of remote sensing data and numerical models

The present paper describes two model-coupled approaches for the determinat ion of rain rates from remote sensing data. The idea of both approaches for retrieving precipitation is to account for realistic and actual Vertical p rofiles of temperature and relative humidity, which are taken from meso-sca le model data. The original Convective Stratiform Technique (CST) method of Adler and Negri (1988) for estimating precipitation rates from infrared ge ostationary satellite data was improved with respect to regional adjustment s to summertime mid-latitude situations and the use of the water vapour cha nnel of Meteosat to detect mid-latitude convective clouds. In our enhanced CST (ECST) numerical model data (1D cloud model and mesoscale model) are us ed for a better adjustment to the actual atmospheric situation. The ECST is applied to a case with strong rain events over Germany, and it shows encou raging results in comparison with radar data, particularly for rain area de tection. A second issue of the paper is to present a methodology for the im provement of rain retrievals from radar data. A spectral cloud model driven by profiles of a meso-scale model is used to generate actual Z/R relations for the radar retrieval. Using a high-resolution raingauge network as a va lidation data set, the first results show an improvement compared to standa rd Z/R relations.