Uncertainties in tropical rain parameters and climate change

Abstract

Successful assessment of climate change induced uncertainties in precipitation cycle is extremely crucial, especially in an agriculturally dependent economy like India. However, given the enormous inhomogeneity of rainfall process over different parts of the country, proper identification of different rain climatologies is crucial. Remote sensing measurements of rain fall can provide a large spatial coverage, however, limited to last few decades. Moreover, rain microphysical behavior under different rain conditions can vary largely which, in turn can affect the accuracy of radar rain meteorology as the accuracy of radar retrieved rainfall relies on relations dependent on rain microphysical structure. This thesis has first attempted to identify homogeneous monsoon rain regions over India based on multiple rain features including rain types, frequency and recent rain extremes by assimilating satellite and ground data using machine learning techniques. The precipitation cycle over the seven of nine different rain climatologies identified, showed different susceptibility to climate change in recent past. Five of the regions showed statistically significant decreasing trend of monsoon rain whereas; two of them had clearly increasing trend of precipitation. A machine learning based regression model has been developed further to predict lightning density over Indian region based on simple atmospheric feature and cloud microphysical structure. The model has showed an R 2 score of 0.81 during monsoon and 0.71 during pre-monsoon. This thesis also investigated two less explored uncertainties associated with rain microphysics which can modulate the precipitation structure significantly and thereby cause notable errors in radar based QPE. The current work reports notable differences in rain and cloud microphysics during lightning. The relations linking radar retrieved parameters with rain estimates were observed to vary largely under lighting condition. The current work also has carried out a thorough comparative analysis of drop velocity-diameter relation between a tropical and a mid-latitude location and presented the evidences of non-terminal velocities in natural rain of these regions. The results point towards the need of correction in radar retrieved rain data using ground based measurements. Besides, it also indicates notable variation of non-terminal drops in two different rain types and climate regimes.