Development of a rainfall model to study rainfall over South Africa using satellite microwave remote sensing

Anoop Kumar Mishra; Kishan Singh Rawat

doi:10.1117/1.JRS.9.096091

29 January 2015 Development of a rainfall model to study rainfall over South Africa using satellite microwave remote sensing

Anoop Kumar Mishra, Kishan Singh Rawat

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 096091 (January 2015). https://doi.org/10.1117/1.JRS.9.096091

Abstract

In this study, a rainfall model is developed to study rainfall over South Africa (10° to 40°E, 35° to 20°S) using a set of rainfall signatures derived from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations at 0.25 deg×0.25 deg spatial grid. Based on measurements at 19-, 21-, and 85-GHz channels of TMI, the scattering index (SI) is derived. Polarization corrected temperature (PCT) is calculated using measurements at the 85-GHz channel. SI, PCT, and their combinations are tested as rain signatures over South Africa. These rain signatures (i.e., PCT and SI and their combinations) are collocated against precipitation radar (PR) onboard TRMM to derive a relationship between rain rate and rain signatures. Rainfall retrieval is attempted using linear as well as nonlinear regressions. The results have been validated using an independent dataset of PR. It is reported that a nonlinear regression outperforms a linear algorithm. Statistical validation with an independent dataset of PR exhibits the correlation coefficients (CCs) of 0.60, 0.64, and 0.66, and root mean square errors (RMSEs) of 5.82, 6.42, and 5.76 mm/h from observations of SI, PCT, and a combination of SI and PCT, respectively, using linear regressions. When nonlinear regression is used, the CC of 0.69, 0.68, and 0.70 and RMSE of 4.75, 4.89, and 4.38 mm/h are observed from the SI, PCT, and the combination of SI and PCT, respectively.

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Anoop Kumar Mishra and Kishan Singh Rawat "Development of a rainfall model to study rainfall over South Africa using satellite microwave remote sensing," Journal of Applied Remote Sensing 9(1), 096091 (29 January 2015). https://doi.org/10.1117/1.JRS.9.096091

Published: 29 January 2015

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