Estimation of rain parameters for microwave backscattering model using PSO

Abstract

The intention of the geophysical modelling of rain is to provide a better explanation for the effect of rainfall to the microwave backscattering and thus to interpret radar measurements. However, in the model, physical characteristic of raindrops should be estimated primarily and accurately by considering observation system, measurements and suitable rain rate retrieval algorithms to calculate backscattering coefficients from rainfall. In this study, a geophysical microwave backscattering model of rain type precipitation over sea surface is constructed by using Particle Swarm Optimization (PSO) algorithm in the multilayered Vector Radiative Transfer (VRT) model to estimate vertical profile of rain by using GPM DPR data. Rain column is partition into sublayers and for each sublayer, physical properties of raindrops such as drop radius, water volume fraction or layer thickness are estimated by using PSO to provide the best fit with measurements by searching within certain limits defined by rain rate. Backscattering coefficients from entire rain is provided by the solution of VRT equations via Matrix Doubling Method to consider multilayer effect. Results show that, vertical profile of rain parameters can be estimated accurately for moderate /high rain rates (up to 11–12 mm/h) by using presented model.