RAINFALL ESTIMATION USING SATELLITE DATA MONTEREY - OCTOBER 2004.

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Presentation transcript:

RAINFALL ESTIMATION USING SATELLITE DATA MONTEREY - OCTOBER 2004

INTRODUCTION Considerable advances in techniques of remote sensing to rainfall estimates. Great advantages to obtain information from away places. Permanent monitoring in vulnerable zones to the floods.

OBJECTIVES To evaluate methods of rainfall estimation, and to adapt them to the characteristics of the Peruvian territory. Monitoring of rains in basins like method of prevention of floods.

METHODOLOGY Gray scale in GVAR between 0 and 256 (8 bits) of image infrared. Calculation of brightness temperature in the top of clouds. Rainfall estimation in base of brightness temperature, using two techniques. a) Auto-Estimator, developed in NOAA. b) GOES Multispectral Rainfall Algorithm (GMSRA). Corrections in function of growth or decrease of the cloud, filtration of cirrus and precipitable water.

a) Auto-estimator b) GMSRA

RESULTS

a) Auto-estimator b) GMSRA

RIMAC RIVER BASIN - JAN, FEB, MAR 2001 10 20 30 40 50 60 70 80 90 100 110 120 Estimated Rainfall 30 40 50 60 70 80 90 100 110 120 Observed Rainfall

CONCLUSIONS algorithm. Over evaluation of Auto-Estimator algorithm. Better results were obtained over Peru with GMSRA algorithm. Over evaluation of Auto-Estimator algorithm. Corrections to the algorithms, such as: - Combination of different channels. - Filtrate of cirrus. - Calculation of the precipitable water.