Comparison of Rainfall Time Series to Identify Predictors for Summer Monsoon Rainfall

Abstract

India receives rainfall due to monsoons. The main contribution of India's total rain comes from the monsoon observed in summer, called the Summer Monsoon Rainfall. The distribution of rainfall across India is significantly variable. Precipitation and its prediction are crucial, especially for states like Maharashtra, which has approximately 70% rainfed land. This paper presents a comparative analysis of two summer monsoon rainfall time series, namely the Marathwada and Maharashtra summer monsoon rainfall series. Continuous Wavelet Transform is used to examine the level of similarity between the two-time sequences, revealing the features of both. Further, both time series are studied for correlations with the main global index, the El Nino Southern Oscillation (ENSO). For the probable identification of seasonal rainfall predictors, the ENSO indices considered here are the Southern Oscillation Index, Multivariate ENSO Index, and Oceanic Nino Index. The effect of warm El Nino phases on these time series is also compared. The study attempts to determine if the prediction model for the Marathwada region can be the same used for the state of Maharashtra or if there is a need to identify a different set of predictors specifically for this region.