Abstract
The South West Monsoon rainfall data of the meteorological subdivision number 6 of India enclosing Gangetic West Bengal is shown to be decomposable into eight empirical time series, namely Intrinsic Mode Functions. This leads one to identify the first empirical mode as a nonlinear part and the remaining modes as the linear part of the data. The nonlinear part is modeled with the technique Neural Network based Generalized Regression Neural Network model technique whereas the linear part is sensibly modeled through simple regression method. The different Intrinsic modes as verified are well connected with relevant atmospheric features, namely, El Nino, Quasi-biennial Oscillation, Sunspot cycle and others. It is observed that the proposed model explains around 75% of inter annual variability (IAV) of the rainfall series of Gangetic West Bengal. The model is efficient in statistical forecasting of South West Monsoon rainfall in the region as verified from independent part of the real data. The statistical forecasts of SWM rainfall for GWB for the years 2012 and 2013 are108.71 cm and 126.21 cm respectively, where as corresponding to the actual rainfall of 93.19 cm 115.20 cm respectively which are within one standard deviation of mean rainfall.
Highlights
The summer monsoon or so called the South West Monsoon (SWM) rainfall comprising of the rainfalls of the months of June, July, August and September, is the substantial component of annual rainfall in India as well as the meteorological sub division number 6 covering the region of Gangetic West Bengal (GWB)
With the help of antecedent IMF1 values, the Generalized Regression Neural Network (GRNN) model is capable of predicting IMF1 for the year
It is observed that GRNN is quite versatile in capturing the latent nonlinear structure evidenced by the high correlation (0.8062) between the actual and simulated IMF1 values
Summary
The summer monsoon or so called the South West Monsoon (SWM) rainfall comprising of the rainfalls of the months of June, July, August and September, is the substantial component of annual rainfall in India as well as the meteorological sub division number 6 covering the region of Gangetic West Bengal (GWB). Efforts are made from earlier times to understand the connections between SWM rainfall and other global and atmospheric phenomenon. As an example, [4] links between the Indian monsoonal rainfall data and the global Sea Surface Temperature (SST) data. The other approach leads to, modeling the past data a year ahead with an insignificant error band to achieve forecast without linking with the phenomenon
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