 |
| Titel |
A statistical approach for rain intensity differentiation using Meteosat Second Generation–Spinning Enhanced Visible and InfraRed Imager observations |
| VerfasserIn |
E. Ricciardelli, D. Cimini, F. Di Paola, F. Romano, M. Viggiano |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 7 ; Nr. 18, no. 7 (2014-07-10), S.2559-2576 |
| Datensatznummer |
250120407
|
| Publikation (Nr.) |
 copernicus.org/hess-18-2559-2014.pdf |
|
|
|
|
|
| Zusammenfassung |
This study exploits the Meteosat Second Generation (MSG)–Spinning Enhanced
Visible and Infrared Imager (SEVIRI) observations to evaluate the rain class
at high spatial and temporal resolutions and, to this aim, proposes the Rain
Class Evaluation from Infrared and Visible observation (RainCEIV) technique.
RainCEIV is composed of two modules: a cloud classification algorithm which
individuates and characterizes the cloudy pixels, and a supervised classifier
that delineates the rainy areas according to the three rainfall intensity
classes, the non-rainy (rain rate value < 0.5 mm h-1)
class, the light-to-moderate rainy class
(0.5 mm h−1 ≤ rain rate value < 4 mm h-1), and the
heavy–to-very-heavy-rainy class (rain rate
value ≥ 4 mm h-1). The second module considers as input the
spectral and textural features of the infrared and visible SEVIRI
observations for the cloudy pixels detected by the first module. It also
takes the temporal differences of the brightness temperatures linked to the
SEVIRI water vapour channels as indicative of the atmospheric instability
strongly related to the occurrence of rainfall events.
The rainfall rates used in the training phase are obtained through the
Precipitation Estimation at Microwave frequencies, PEMW (an algorithm for
rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B
observations). RainCEIV's principal aim is that of supplying preliminary
qualitative information on the rainy areas within the Mediterranean Basin
where there is no radar network coverage. The results of RainCEIV have been
validated against radar-derived rainfall measurements from the Italian
Operational Weather Radar Network for some case studies limited to the
Mediterranean area. The dichotomous assessment related to daytime (nighttime)
validation shows that RainCEIV is able to detect rainy/non-rainy areas with
an accuracy of about 97% (96%), and when all the rainy classes are
considered, it shows a Heidke skill score of 67% (62%), a bias
score of 1.36 (1.58), and a probability of detection of rainy areas of
81% (81%). |
| |
|
| Teil von |
|
|
|
|
|
|
|
|