Rainfall Estimation from Combined Observations Using KALPANA-IR and TRMM- Precipitation Radar Measurements over Indian Region

Abstract

In the present study an attempt has been made to improve the rainfall estimation technique developed recently by Mishra et al. (2009a, 2009b) based on KALPANA and Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR) data over the Indian land and oceanic region. The algorithm for rainfall estimation was basically based on synergistically analyzing the thermal infra-red radiances from Kalpana/INSAT data along with the high resolution, horizontal and vertical rainfall estimates from PR. Presently the augmentation is based on the data base of precipitable water and relative humidity from National Centre for Environmental Prediction-Global forecast System (NCEP-GFS) data as a background field to correct for the biases in earlier algorithm. The algorithm is tested for many case studies of monsoon rainfall over India and adjoining oceanic regions. The rainfall from the present scheme is compared with the standard TRMM-3B42 rain product. The validation with the Automatic Weather Station (AWS) rain gauge and the Global Precipitation and Climatology Project (GPCP) version 2 rain products shows that the present scheme is able to retrieve the rainfall with a very good accuracy. These studies are aimed at the rainfall retrievals in near future from both INSAT-3D and Megha-Tropiques, IR and MW imagers respectively.