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.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/278163 |
| Date | January 1992 |
| Creators | Schmitz, Jeffrey Todd, 1962- |
| Contributors | Dickinson, Robert E. |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Thesis-Reproduction (electronic) |
| 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. |
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