Regression-Based Approach to Analyze Tropical Cyclone Genesis

This paper attempts to explore regression approach for the prediction of tropical cyclone genesis in North Indian Ocean. The cyclonic storms from the Bay of Bengal are the usual phenomenon in east coast of India. The present study mainly focuses on two such very severe cyclonic storms, PHAILIN and HUDHUD in 2013 and 2014, respectively. Various meteorological parameters that clearly explain the favorable situation for the occurrence of cyclonic storm are investigated and analyzed. The study emphasizes on selection of the potential predictor variables using stepwise regression method to analyze the efficiency of model. Regression analysis yields a predicted value resulting from a linear combination of the predictors. For the regression model, the predictor set consists of sea level pressure (SLP) and wind speed parameters. Different types of the regression methods have been used in the study and compared to find the efficient regression model for cyclone genesis prediction. The threshold-based anomaly detection algorithm is proposed for the potential predictors obtained using stepwise regression which is capable of successfully identifying the situation that led to the very severe cyclonic storm.