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As communication services using higher frequencies are growing rapidly in the tropics, there is an increasing need for a finer model to predict the attenuation due to rain. The raindrop size distribution (DSD) is one of the major sources of error in any prediction model, mainly because of its variability in both space and time. The DSD parameters are computed from distrometer data that are classified into stratiform and convective types using S-band radar data. The method of moments is employed to estimate the parameters of lognormal DSD. The modeled DSD parameters are optimized by examining the root mean square (RMS) error and the average probability ratio (APR) in estimation of the rain rate, rain attenuation, and radar reflectivity factor simultaneously. The proposed model gives maximum (close to unity) APR and minimum RMS error when compared to any other set of DSD parameters.