Estimating rainfall from satellite infrared imagery: Cloud patch analysis

Persistent Link:
http://hdl.handle.net/10150/282573
Title:
Estimating rainfall from satellite infrared imagery: Cloud patch analysis
Author:
Xu, Liming, 1958-
Issue Date:
1997
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Most infrared-based techniques of satellite rainfall estimation contain substantial uncertainties due to the indirect relationship between precipitation particles and space-borne infrared observations of clouds. Generally, these uncertainties include (1) IR temperature threshold defining cold clouds; (2) inclusion of no-rain clouds; (3) exclusion of warm rain clouds; and (4) the coefficients between rain rate and cloud-top properties. To address these uncertainties, a methodology, Cloud Patch Analysis, was developed to estimate rainfall by removing large portion of no-rain clouds from IR cloud imagery. Seven cloud features, including physical, geometric and textural, were defined, and ID3, an inductive decision tree, was used to identify no-rain clouds. Particularly, textural characteristics were extended from square images to irregular cloud patches to extract cloud features related to rainfall. In addition, the method adopted a mechanism to adjust IR temperature threshold according to locations and seasons, and this adjustment can be made by the combination of microwave observations by polar-orbiting satellites with infrared observations by geostationary satellites. The application of the adjusted IR threshold to GPI algorithm showed significant improvement for monthly rainfall estimation. The method was applied to the Japanese Islands and surrounding oceanic regions in June and July/August 1989 and to the Florida region in June and August 1996. The monthly rainfall estimates by the proposed method showed significant and consistent improvements over those by GPI.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Hydrology.; Physics, Atmospheric Science.; Remote Sensing.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Hydrology
Degree Grantor:
University of Arizona
Advisor:
Sorooshian, Soroosh

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleEstimating rainfall from satellite infrared imagery: Cloud patch analysisen_US
dc.creatorXu, Liming, 1958-en_US
dc.contributor.authorXu, Liming, 1958-en_US
dc.date.issued1997en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractMost infrared-based techniques of satellite rainfall estimation contain substantial uncertainties due to the indirect relationship between precipitation particles and space-borne infrared observations of clouds. Generally, these uncertainties include (1) IR temperature threshold defining cold clouds; (2) inclusion of no-rain clouds; (3) exclusion of warm rain clouds; and (4) the coefficients between rain rate and cloud-top properties. To address these uncertainties, a methodology, Cloud Patch Analysis, was developed to estimate rainfall by removing large portion of no-rain clouds from IR cloud imagery. Seven cloud features, including physical, geometric and textural, were defined, and ID3, an inductive decision tree, was used to identify no-rain clouds. Particularly, textural characteristics were extended from square images to irregular cloud patches to extract cloud features related to rainfall. In addition, the method adopted a mechanism to adjust IR temperature threshold according to locations and seasons, and this adjustment can be made by the combination of microwave observations by polar-orbiting satellites with infrared observations by geostationary satellites. The application of the adjusted IR threshold to GPI algorithm showed significant improvement for monthly rainfall estimation. The method was applied to the Japanese Islands and surrounding oceanic regions in June and July/August 1989 and to the Florida region in June and August 1996. The monthly rainfall estimates by the proposed method showed significant and consistent improvements over those by GPI.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectHydrology.en_US
dc.subjectPhysics, Atmospheric Science.en_US
dc.subjectRemote Sensing.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineHydrologyen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorSorooshian, Sorooshen_US
dc.identifier.proquest9817349en_US
dc.identifier.bibrecord.b3826917xen_US
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