Identification of raining clouds using a method based on optical and microphysical cloud properties from Meteosat second generation daytime and nighttime data

Abstract

A new scheme for the delineation of raining and non-raining cloud areas applicable to mid-latitudes from daytime and nighttime multispectral satellite data is developed. The technique is based on optical and microphysical cloud properties using an artificial neural network. The tests have been conducted during the rainy season of 2006/2007. The proposed algorithm uses the spectral parameters of SEVIRI (Spinning Enhanced Visible and Infrared): brightness temperature TIR10. 8 and brightness temperature differences ΔTIR10. 8-IR12. 1, ΔTIR8. 7-IR10. 8, ΔTIR3. 9-IR10. 8 and ΔTIR3. 9-WV7. 3 during the nighttime and reflectances RVIS0. 6, RNIR1. 6, brightness temperature TIR10. 8, brightness temperature difference ΔTIR8. 7-IR10. 8 and ΔTIR10. 8-IR12. 0 during the daytime. The algorithm is calibrated by instantaneous meteorological radar using multilayer perceptron. Radar provided the "ground precipitation truth" for training and validation. The application shows interesting and encouraging results. © 2013 The Author(s).