A Modified Tracer Selection and Tracking Procedure to Derive Winds Using Water Vapor Imagers

Abstract

Abstract The remotely sensed upper-tropospheric water vapor wind information has been of increasing interest for operational meteorology. A new tracer selection based on a local image anomaly and tracking procedure, itself based on Nash–Sutcliffe model efficiency, is demonstrated here for the estimation of upper-tropospheric water vapor winds both for cloudy and cloud-free regions from water vapor images. The pressure height of the selected water vapor tracers is calculated empirically using a height assignment technique based on a genetic algorithm. The new technique shows encouraging results when compared with Meteosat-5 water vapor winds over the Indian Ocean region. The water vapor winds produced by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) from Meteosat-5 and the present algorithm are compared with collocated radiosonde observations according to Coordination Group for Meteorological Satellites guidelines. The proposed algorithm shows better accuracy in terms of mean vector difference, rms vector difference, standard deviation, speed bias, number of collocations, and mean speed and mean direction differences. Also it is found that the sensitivity of the spatial consistency check in the quality indicator is not so significant for the improvement of statistics.