Estimating surface precipitation over Mexico by calibrating satellite infrared imagery and airborne radar

Persistent Link:
http://hdl.handle.net/10150/278163
Title:
Estimating surface precipitation over Mexico by calibrating satellite infrared imagery and airborne radar
Author:
Schmitz, Jeffrey Todd, 1962-
Issue Date:
1992
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:
An algorithm for estimating daily surface rain volumes from hourly GOES infrared images has been developed using data obtained during the Southwest Area Monsoon Project(SWAMP). Daily surface rain volumes will be estimated using derived positive linear relationships between digital infrared counts and cloud radar reflectivities. These relations provide estimates of radar reflectivities corresponding to hourly infrared images, which in term, using an assumed reflectivity-rainrate(ZR) relation(Z = 55R1.6), will are to generate hourly precipitation fields from which daily rain volumes are computed. The linear relations employed are determined through a regression analysis on digital IR counts of GOES imagery and airborne internal radar reflectivity samples. This study also explores the existence of an average linear relation between infrared pixel values and radar reflectivities.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Physics, Atmospheric Science.; Remote Sensing.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College
Degree Grantor:
University of Arizona
Advisor:
Dickinson, Robert E.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleEstimating surface precipitation over Mexico by calibrating satellite infrared imagery and airborne radaren_US
dc.creatorSchmitz, Jeffrey Todd, 1962-en_US
dc.contributor.authorSchmitz, Jeffrey Todd, 1962-en_US
dc.date.issued1992en_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.abstractAn algorithm for estimating daily surface rain volumes from hourly GOES infrared images has been developed using data obtained during the Southwest Area Monsoon Project(SWAMP). Daily surface rain volumes will be estimated using derived positive linear relationships between digital infrared counts and cloud radar reflectivities. These relations provide estimates of radar reflectivities corresponding to hourly infrared images, which in term, using an assumed reflectivity-rainrate(ZR) relation(Z = 55R1.6), will are to generate hourly precipitation fields from which daily rain volumes are computed. The linear relations employed are determined through a regression analysis on digital IR counts of GOES imagery and airborne internal radar reflectivity samples. This study also explores the existence of an average linear relation between infrared pixel values and radar reflectivities.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectPhysics, Atmospheric Science.en_US
dc.subjectRemote Sensing.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorDickinson, Robert E.en_US
dc.identifier.proquest1349135en_US
dc.identifier.bibrecord.b27636598en_US
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