Evaluation of PERSIANN system satellite-based estimates of tropical rainfall

Soroosh Sorooshian, Kuo Lin Hsu, Xiaogang Gao, Hoshin Vijai Gupta, Bisher Imam, Dan Braithwaite

Research output: Contribution to journalArticle

680 Citations (Scopus)

Abstract

PERSIANN, an automated system for Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, has been developed for the estimation of rainfall from geosynchronous satellite longwave infared imagery (GOES-IR) at a resolution of 0.25° × 0.25° every half-hour. The accuracy of the rainfall product is improved by adaptively adjusting the network parameters using the instantaneous rain-rate estimates from the Tropical Rainfall Measurement Mission (TRMM) microwave imager (TMI product 2A12), and the random errors are further reduced by accumulation to a resolution of 1° × 1° daily. The authors' current GOES-IR - TRMM TMI based product, named PERSIANN-GT, was evaluated over the region 30°S-30°N, 90°E-30°W, which includes the tropical Pacific Ocean and parts of Asia, Australia, and the Americas. The resulting rain-rate estimates agree well with the National Climatic Data Center radar-gauge composite data over Florida and Texas (correlation coefficient p > 0.7). The product also compares well (p ̃ 0.77-0.90) with the monthly World Meteorological Organization gauge measurements for 5° × 5° grid locations having high gauge densities. The PERSIANN-GT product was evaluated further by comparing it with current TRMM products (3A11, 3B31, 3B42, 3B43) over the entire study region. The estimates compare well with the TRMM 3B43 1° × 1° monthly product, but the PERSIANN-GT products indicate higher rainfall over the western Pacific Ocean when compared to the adjusted geosynchronous precipitation index-based TRMM 3B42 product.

Original languageEnglish (US)
Pages (from-to)2035-2046
Number of pages12
JournalBulletin of the American Meteorological Society
Volume81
Issue number9
StatePublished - Sep 2000

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rainfall
gauge
GOES
product
evaluation
ocean
artificial neural network
imagery
radar
rate
rain

ASJC Scopus subject areas

  • Atmospheric Science

Cite this

Sorooshian, S., Hsu, K. L., Gao, X., Gupta, H. V., Imam, B., & Braithwaite, D. (2000). Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bulletin of the American Meteorological Society, 81(9), 2035-2046.

Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. / Sorooshian, Soroosh; Hsu, Kuo Lin; Gao, Xiaogang; Gupta, Hoshin Vijai; Imam, Bisher; Braithwaite, Dan.

In: Bulletin of the American Meteorological Society, Vol. 81, No. 9, 09.2000, p. 2035-2046.

Research output: Contribution to journalArticle

Sorooshian, S, Hsu, KL, Gao, X, Gupta, HV, Imam, B & Braithwaite, D 2000, 'Evaluation of PERSIANN system satellite-based estimates of tropical rainfall', Bulletin of the American Meteorological Society, vol. 81, no. 9, pp. 2035-2046.
Sorooshian, Soroosh ; Hsu, Kuo Lin ; Gao, Xiaogang ; Gupta, Hoshin Vijai ; Imam, Bisher ; Braithwaite, Dan. / Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. In: Bulletin of the American Meteorological Society. 2000 ; Vol. 81, No. 9. pp. 2035-2046.
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