CLOUD GROWTH BASED PRECIPITATION ESTIMATION ALGORITHM FOR KALPANA-1 SATELLITE DATA
Keywords:
precipitation, TIR measurements, WV measurements,corelation coefficient, root mean square error, Kalpana-1Abstract
In the present study,a novel algorithm is developed for precipitation estimation using Kalpana-1 data based
on Thermal Infrared (TIR) and Watervapor(WV) measurements. Infrared (IR) rain rates are based on cloud top
temperature which is indirectly related to surface rainfall whereas microwave (MW) measurements that sense
precipitation in clouds are directly related to precipitation rates. For the few decades, estimation of precipation has
been done utilizing hybrid algorithms, which uses both TIR and MW measurements. In this paper, TIR and WV
measurements from Kalpana-1 geostationary satellite are used for determination of convective and non convective
clouds. Rain rate is assigned for every rainy pixel using non linear power relationship. Brightness temperature(BT) of
both TIR band and WV band are used for the determination of rainy and non rainy pixel. The obtained rainfall in this
method is compared with high resolution multisatellite precipitation product namely TMPA 3B42v7 and IMD gridded
rain guage dataset. Performance of the present technique is improved in terms of Correlation coefficients and RMSE
values when compared with other rainfall products and IMD rain guage dataset.
