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

Abstract

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 10.8Τ 12.1, Τ 8.7Τ 10.8, and Τ 6.2Τ 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 (BTDall 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, BTDall 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, BTDall 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.

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Acknowledgments

The research has been co-financed by the European Union (European Social Fund—E.S.F) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program Heracleitous II. Investing in knowledge society through the European Social Fund. The authors wish to thank the National Observatory of Athens for providing the precipitation data from their network of ground stations.

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Correspondence to Haralambos Feidas.

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Feidas, H., Giannakos, A. Classifying convective and stratiform rain using multispectral infrared Meteosat Second Generation satellite data. Theor Appl Climatol 108, 613–630 (2012). https://doi.org/10.1007/s00704-011-0557-y

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Keywords

  • Brightness Temperature
  • Rain Rate
  • Equitable Threat Score
  • Rain Gauge Data
  • Convective Rain