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Titolo:
A cloud-patch technique for identification and removal of no-rain clouds from satellite infrared imagery
Autore:
Xu, LM; Sorooshian, S; Gao, XG; Gupta, HV;
Indirizzi:
Univ Arizona, Dept Hydrol & Water Resources, Tucson, AZ 85721 USA Univ Arizona Tucson AZ USA 85721 & Water Resources, Tucson, AZ 85721 USA
Titolo Testata:
JOURNAL OF APPLIED METEOROLOGY
fascicolo: 8, volume: 38, anno: 1999,
pagine: 1170 - 1181
SICI:
0894-8763(199908)38:8<1170:ACTFIA>2.0.ZU;2-D
Fonte:
ISI
Lingua:
ENG
Soggetto:
PRECIPITATION CLIMATOLOGY PROJECT; CLASSIFICATION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
22
Recensione:
Indirizzi per estratti:
Indirizzo: Sorooshian, S Univ Arizona, Dept Hydrol & Water Resources, Bldg 11,POB 210011, Tucson, AZ 85721 USA Univ Arizona Bldg 11,POB 210011 Tucson AZ USA 85721 5721 USA
Citazione:
L.M. Xu et al., "A cloud-patch technique for identification and removal of no-rain clouds from satellite infrared imagery", J APPL MET, 38(8), 1999, pp. 1170-1181

Abstract

A new cloud-patch method for the identification and removal of no-rain cold clouds from infrared (IR) imagery is presented. A cloud patch is defined as a cluster of connected IR imagery pixels that are colder than a given IRbrightness temperature threshold. The threshold is derived through a combination of the rainfall field estimated from microwave observations and the IR data closely coincident with microwave sensor satellite overpasses. Seven cloud-patch features are used to describe cloud-top properties, includingsix IR based and one VIS based. The ID3 algorithm is used to extract structural knowledge from a training dataset and to produce classification rulesexpressed explicitly on the values of various patch features; these rules can be used to explain the physical principles underlying the cloud classification The method was evaluated for the Japanese islands and surrounding oceans using AIP/1 data for June (training period) and July-August (evaluation period) 1989. The results of identifying no-rain cloud patches are very good for both periods in spite of the change in rainfall regime from frontal to subtropical convective. Nearly 20% of the total pixels and 60% of the no-rain cloud pixels were removed with negligible rain losses due to misclassification. Moreover, visible data were found to be useful for enhancing the no-rain cold patch identification and thereby reducing the rain loss.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 29/11/20 alle ore 10:36:55