Infrared (IR) imagery collected by geostationary satellites provides useful information
about the dirunal evolution of cloud systems. These IR images can be analyzed to indicate
the location of clouds as well as the pattern of cloud top temperatures (Tbs). During the past
several decades, a number of different approaches for estimation of rainfall rate (RR) from
Tb have been explored and concluded that the Tb-RR relationship is (1) highly nonlinear,
and (2) seasonally and regionally dependent. Therefore, to properly model the relationship,
the model must be able to:
(1) detect and identify a non-linear mapping of the Tb-RR relationship;
(2) Incorporate information about various cloud properties extracted from IR image;
(3) Use feedback obtained from RR observations to adaptively adjust to seasonal and
regional variations; and
(4) Effectively and efficiently process large amounts of satellite image data in real -time.
In this study, a kind of artificial neural network (ANN), called Modified Counter
Propagation Network (MCPN), that incorporates these features, has been developed. The
model was calibrated using the data around the Japanese Islands provided by the Global
Precipitation Climatology Project (GPCP) First Algorithm Intercomparison Project (AIP-I).
Validation results over the Japanese Islands and Florida peninsula show that by providing
limited ground-truth observation, the MCPN model is effective in monthly and hourly
rainfall estimation. Comparison of results from MCPN model and GOES Precipitation Index
(GPI) approach is also provided in the study.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/615703 |
| Date | January 1997 |
| Creators | Hsu, Kuo-Lin, Sorooshian, Soroosh, Gao, Xiaogang, Gupta, Hoshin Vijai |
| Contributors | Department of Hydrology & Water Resources, The University of Arizona |
| Publisher | Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ) |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Technical Report |
| Source | Provided by the Department of Hydrology and Water Resources. |
| Rights | Copyright © Arizona Board of Regents |
| Relation | Technical Reports on Hydrology and Water Resources, No. 97-010 |
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