Satellite estimation of the tropical precipitation using the METEOSTAT and SSM/I data

Abstract

The purpose of this study is to test a satellite method for estimating precipitation using infrared and microwave data. The method is validated by comparing the rain estimates to the ground precipitation measurements, over continental tropical regions (West Africa). The rain estimation method used is based on an automatic classification algorithm combining infrared and microwave satellite data. The method takes advantage of both, the good time and space resolution of infrared satellite images and the rain related information retrieved from microwave images. This method of rain and cloud classification (RACC) gives homogeneous classes characterising the different types of clouds or rain-rates. A set of microwave images from the 86 GHz channel of the passive microwave radiometer SSM/I and of the coincident infrared images from Meteosat is used in the learning phase of the classification process, while the full set of half-hourly infrared images is needed for the application phase. The areal rain estimates are computed with the microwave-infrared combined RACC method for time periods ranging from one to twelve hours and for different areas up to 120 km × 120 km. The correlation with the ground rainfall data given by the raingauge network of a validation site in Niger are estimated and compared to the correlations obtained for the rain estimated derived from a method based on a single infrared threshold and using the Meteosat images only. The improvement brought by the RACC method is discussed.