Classifying convective and stratiform rain using multispectral infrared Meteosat Second Generation satellite data

This paper investigates the potential for developing schemes that classify convective and stratiform precipitation areas using the high infrared spectral resolution of the Meteosat Second Generation—Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI). Two different classification schemes were proposed that use the brightness temperature (BT) Τ _10.8 along with the brightness temperature differences (BTDs) Τ _10.8–Τ _12.1, Τ _8.7–Τ _10.8, and Τ _6.2–Τ _10.8 as spectral parameters, which provide information about cloud parameters. The first is a common multispectral thresholding scheme used to partition the space of the spectral cloud parameters and the second is an algorithm based on the probability of convective rain (PCR) for each pixel of the satellite data. Both schemes were calibrated using as a reference convective\stratiform rain classification fields derived from 87 stations in Greece for six rainy days with high convective activity. As a result, one single infrared technique (TB₁₀) and two multidimensional techniques (BTD_all and PCR) were constructed and evaluated against an independent sample of rain gauge data for four daily convective precipitation events. It was found that the introduction of BTDs as additional information to a technique works in improving the discrimination of convective from stratiform rainy pixels compared to the single infrared technique BT₁₀. During the training phase, BTD_all performed slightly better than BT₁₀ while PCR technique outperformed both threshold techniques. All techniques clearly overestimate the convective rain occurrences detected by the rain gauge network. When evaluating against the independent dataset, both threshold techniques exhibited the same performance with that of the dependent dataset whereas the PCR technique showed a notable skill degradation. As a result, BTD_all performed best followed at a short distance by PCR and BT₁₀. These findings showed that it is possible to apply a convective/stratiform rain classification algorithm based on the enhanced infrared spectral resolution of MSG-SEVIRI, for nowcasting or climate purposes, despite the highly variable nature of convective precipitation.