caa a22 4500 445800097 CHVBK 20180317145138.0 cr unu---uuuuu 170323e20110501xx s 000 0 eng 10.1007/s00704-010-0316-5 doi (NATIONALLICENCE)springer-10.1007/s00704-010-0316-5 Identifying precipitating clouds in Greece using multispectral infrared Meteosat Second Generation satellite data [Elektronische Daten] [Haralambos Feidas, Apostolos Giannakos] The present study aimed to investigate the potential of possible rain area delineation schemes based on the enhanced infrared spectral resolution of the Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager. The proposed schemes 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 cloud parameters. Two different methods were used to develop the rain area delineation models. The first is a common threshold technique in the multispectral space of the spectral cloud parameters, and the second is an algorithm based on the probability of rain (PoR) for each pixel of the satellite data. Both schemes were trained using as rain information gauge data from 41 stations in Greece for 107 rainy days, covering a period of 1year. As a result, one single-infrared model (TB10), three two-dimensional (BTD10-12, BTD8-10, and BTD6-10), and two multidimensional models (BTDall and PoR) were constructed and verified against an independent sample of rain gauge data for four daily precipitation events. It was found that the introduction of BTDs as additional information to a model works in improving the discrimination of rain from no-rain events compared with the single-infrared model BT10. During the training phase, BTDall exhibited the best performance among the threshold techniques, while the PoR model outperformed all the threshold techniques, producing scores slightly better than those of BTDall model. When verifying against the independent dataset, all models exhibited the same performance with that of the dependent dataset according to the ETS score but less skill according to the HK score. The proposed techniques, however, still perform better than the single-infrared technique but with different ranking; BTall performs best followed by PoR and BTD10-12. Finally, two case studies are presented to gain a visual impression of the performance of the new developed rain area delineation schemes, showing the effectiveness of BTDall in delineating the thicker part of cirrus clouds and of PoR in detecting rain from the low-level thick clouds. Springer-Verlag, 2010 Feidas Haralambos Department of Meteorology and Climatology, Aristotle University of Thessaloniki, School of Geology, 54124, Thessaloniki, Greece aut Giannakos Apostolos Department of Meteorology and Climatology, Aristotle University of Thessaloniki, School of Geology, 54124, Thessaloniki, Greece aut Theoretical and Applied Climatology Springer Vienna 104/1-2(2011-05-01), 25-42 0177-798X 104:1-2<25 2011 104 704 https://doi.org/10.1007/s00704-010-0316-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00704-010-0316-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Feidas Haralambos Department of Meteorology and Climatology, Aristotle University of Thessaloniki, School of Geology, 54124, Thessaloniki, Greece aut NATIONALLICENCE 700 1- Giannakos Apostolos Department of Meteorology and Climatology, Aristotle University of Thessaloniki, School of Geology, 54124, Thessaloniki, Greece aut NATIONALLICENCE 773 0- Theoretical and Applied Climatology Springer Vienna 104/1-2(2011-05-01), 25-42 0177-798X 104:1-2<25 2011 104 704 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer