Can the Drought/Flood Monsoon Conditions over the Indian subcontinent be forecasted using Artificial Neural Networks?

Abstract

The Indian summer monsoon rainfall during the months June, July, August and September (JJAS) has been classified into seven climatic zones, according to standard precipitation index. Prediction of rainfall within the six hydrological zones of India was attempted with the oceanic predictors, which highly influence the terrestrial precipitation, such as Sea Surface Temperature (SST), Sea Level Pressure (SLP), Humidity and zonal and meridional components of Surface Wind (u and v) to quantify the rainfall amounts by clustering based artificial neural networks for the distinguishable dry and wet years. In the present analysis, we have used data for the period 1960 - 2012, which incidentally had several extreme events (of drought and flood conditions) over the Indian subcontinent. Next, the results indicate that the predicted values are well comparable with the actual measured values proving the usefulness of this approach. In addition, this approach has improved upon the past and recent attempts to model rainfall (including extreme cases) which in turn will have a significant impact on farmers and agriculturists.