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| Titel |
Artificial neural-network technique for precipitation nowcasting from satellite imagery |
| VerfasserIn |
G. Rivolta, F. S. Marzano, E. Coppola, M. Verdecchia |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: 7th Plinius Conference on Mediterranean Storms (2005) ; Nr. 7 (2006-02-02), S.97-103 |
| Datensatznummer |
250004275
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| Publikation (Nr.) |
 copernicus.org/adgeo-7-97-2006.pdf |
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| Zusammenfassung |
| The term nowcasting reflects the need of timely and
accurate predictions of risky situations related to the development of
severe meteorological events. In this work the objective is the very short
term prediction of the rainfall field from geostationary satellite imagery
entirely based on neural network approach. The very short-time prediction
(or nowcasting) process consists of two steps: first, the infrared radiance
field measured from geostationary satellite (Meteosat 7) is projected ahead
in time (30 min or 1 h); secondly, the projected radiances are used to
estimate the rainfall field by means of a calibrated microwave-based
combined algorithm. The methodology is discussed and its accuracy is
quantified by means of error indicators. An application to a satellite
observation of a rainfall event over Central Italy is finally shown and
evaluated. |
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