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Evaluation of a Satellite-Based Rain Estimation Algorithm Using a Network of Meteorological Stations. Preliminary Results in a Region with Complex Terrain

The present study was a first attempt to quantitatively evaluate an existing satellite-based rain estimation algorithm using measurements from a network of ground-based meteorological stations. The study domain was the Epirus region (the rainiest region in Greece) where the Laboratory of Meteorology and Climatology of Ioannina University operates eight meteorological stations distributed across the study domain. The utilized version of the rain estimation algorithm used the Meteosat-11 brightness temperature in the 10.8 μm channel (BT10.8μm) to estimate the rain intensity on a 4 km pixel basis, after discriminating the rain/non-rain pixels with a simple thresholding method. The rain recordings of the meteorological stations’ network were spatiotemporally correlated with the Meteosat-11 data. These correlations led to a dataset with 1323 pairs of rain recordings and their relative rain estimations from the satellite-based algorithm. A statistical analysis of these pairs of values was conducted revealing a mean error (ME) of 0.22 mm/hour (14% error with respect to the mean value of the recordings). The computed probability of false detection (POFD), probability of detection (POD), and the bias score were equal to 0.22, 0.69, and 0.88, respectively. The evaluation statistics are promising for operationally using this algorithm for rain estimation on a real-time basis.