Prediction of Active and Break Spells of Indian Summer Monsoon Using Linear Discriminant Analysis

India being an agricultural land, the monsoon governs the pulse of life for its mankind along with the flora-fauna existing in the subcontinent. Active and break spells are two important phases of monsoon which determine the overall quality and quantity of monsoon for a year. Prediction of active and break spells of monsoon is of high significance owing to planning of proper strategy for best utilization of monsoon phases, which assists in economic development of the country. In this article we propose a classification based scheme for the prediction of spells of the Indian summer monsoon. We have used linear discriminant analysis based classifier to classify the monsoon days into into dry, normal, or wet days. Classifying monsoon at daily scale makes it more challenging as uncertainty and variability are more higher as compared to monthly or yearly monsoon prediction. Climatic variables are selected of meteorology importance as input features to the classifier for obtaining higher accuracy of classification. Proposed method initiates with greedy feature selection, followed by linear discriminant analysis based classification of daily monsoon. Assembling the classified monsoon days lead to the determination of active or break spells during the period. Classification results are observed to be close to an acceptable performance, owing to the complexity of the phenomenon. The spells are predicted with comparable accuracy. The accuracy of prediction of the break spells are observed to be superior to that of the active spells.