The exploitation of Meteosat Second Generation data for convective storms over the Czech Republic

The aim of the paper is to study the validation and correction of the Convective Rainfall Rate (CRR) algorithm, which utilises three channels from Meteosat Second Generation to estimate rainfalls: IR 10.8 μm, WV 6.2 μm and VIS 0.6 μm. The original CRR algorithm was applied to data from Central Europe (the Czech Republic) but since the calibration matrices (which are the core of CRR) were previously derived using data from Spain and Norway, we recalculated these matrices using data from the Czech Republic. We found that the original and the new matrices were significantly different in absolute values and in the values of IR 10.8 μm, WV 6.2 μm and VIS 0.6 μm under which rainfalls were observed. We subjectively modified these calculated calibration matrices and used them within the CRR algorithm. We also complemented the algorithm with the correction of the distribution of estimated rainfalls. All three methods, the original and our two algorithms, were compared according to various categorical measures and other statistical measures (like Root Mean Square Error). The results showed that the new calibration matrices, complemented by the distribution correction, yielded more accurate rainfall estimates than the other two methods.

Research highlights
► Matrices calibrated by Czech radar data improved resulting SPE in the area of the CR.
► SPE underestimates heavy rainfalls and overestimates precipitation areas.
► Radar-derived precipitation estimates are preferable.