Rainfall estimation using spaceborne microwave radar and radiometric measurements

Abstract

The present paper deals with some of the recent remote sensing techniques for the estimation of rainfall, mainly from passive and active microwave measurements from space. The sensitivity analysis based on forward approach following the radiative transfer modelling using data from ECMWF and mesoscale models is presented. The inverse methods of retrieving rainfall from satellite microwave measurements mainly from the multiple regression and neural networks are presented based on the sensitivity analysis. The simulations are carried out for the multichannel measurements from TRMM-TMI, DMSP-SSM/I and Indian IRS-P4-MSMR radiometric channels and are assessed with the actual observations thereof.  A few examples of the rainfall patterns are described and compared with some of the standard products from TRMM radiometer and radar. The examples of monthly rain rates derived from MSMR, are also shown qualitatively and quantitatively, for a typical monsoon month of August for brevity out of three consecutive years of analysis. Though the status of rainfall estimation presented is not exhaustive one, it is presented in view of the preparedness for the future missions like, Megha-Tropiques and Global Precipitation Mission.