1. RAINFALL ESTIMATION
USING SATELLITE DATA
MONTEREY - OCTOBER 2004

2. 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.

3. 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.

4. 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.

5. a) Auto-estimator
b) GMSRA

6. RESULTS

7. a) Auto-estimator
b) GMSRA

9. RIMAC RIVER BASIN - JAN, FEB, MAR 200110 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

10. 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.