Meteorology and Atmospheric Physics

, Volume 107, Issue 3–4, pp 81–89 | Cite as

Weather type dependent quality assessment of a satellite-based rainfall detection scheme for the mid-latitudes

  • Boris Thies
  • Andreas Turek
  • Thomas Nauss
  • Jörg Bendix
Original Paper


The sensitivity of a recently published satellite-based rainfall detection scheme with differing frontal weather regimes is investigated for 676 precipitation scenes between January and August 2004. For this purpose, the rain area classified by the recent Rain Area Delineation Scheme during Night time (RADS-N) was compared to the rain area detected by the radar network of the German Weather Service. The validation results indicate that the rain area detected by RADS-N is highly consistent with the radar network (mean POD: 0.62; mean FAR: 0.52; mean ETS: 0.22). However, the bias indicates a mean overestimation of 42%. The classification results show that the satellite technique performs better in cold frontal situations and thunderstorms. Therefore, further investigations are needed to address the overall performance as well as the dependency on different weather situations and in order to allow reliable rain area detection during night-time, independent of the prevailing weather situation.


Weather Situation Equitable Threat Score Radar Network False Alarm Ratio Rain Area 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors are grateful to the German Weather Service (DWD) for providing the ground-based precipitation dataset. The current study was funded by the German Ministry of Research and Education (BMBF) in the framework of GLOWA-Danube project (G-D/2004/TP-10, precipitation/remote sensing), as well as by the German Research Council DFG (BE 1780/18-1) within the SORT project. Furthermore, the authors would like to thank the anonymous reviewers for valuable remarks and comments which helped to improve the manuscript.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Boris Thies
    • 1
  • Andreas Turek
    • 1
  • Thomas Nauss
    • 2
  • Jörg Bendix
    • 1
  1. 1.Laboratory for Climatology and Remote Sensing, Faculty of GeographyPhilipps-University MarburgMarburgGermany
  2. 2.KlimatologieUniversität BayreuthBayreuthGermany

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