Assessment of Satellite Based Precipitation Products

Abstract

Precipitation event will impact on the economy of the countries in the world the environment and the society, mostly in the countries where rainfall is more. With the help of satellite precipitation data with high resolution and worldwide coverage of the data which gave us the new source of precipitation products, the data collected from satellite is not considered most of the times due to its uncertainty.
In the present study the goal was, evaluate performance of satellite products after gathering the data, this is used to know the difference between rainfall data and satellite products data using an extensive selections of validation metric. The results obtained are similar to the likelihood of knowing rainfall volume and amount of correctly recognized rainfall. In the few years, satellite datasets of rainfall believed to be a source for input in the hydrological models, which are used in areas where it is difficult to get the gauge.
The study goal is to assess satellite products of, CPC morphing technique, PERSIANN-CDR (precipitation estimation from remotely sensed information using artificial neural networks-climate data) against Ground based rainfall datasets and to know the effect on the hydrological process. The intention is to know data of two satellites such as RFE (rainfall estimate) and TRMM (tropical rainfall measuring) in the Western Ghats region. the discontinuity of the ground data due to difficulties such as inaccessibility of the ground, where gauges data is not so correct, so determining the amount of rain from satellite is more helpful to get the rainfall pattern to know the forecast about the floods and discharges, to examine the satellite datasets ME (mean error) and CC (correlation coefficient) are used.