A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor |
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| Authors: | Nachiketa Acharya Surajit Chattopadhyay Makarand A Kulkarni Uma C Mohanty |
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| Institution: | (1) Centre for Atmospheric Sciences, IIT, New Delhi, India;(2) National Centre for Medium Range Weather Forecasting, A-50, Sector-62, Noida, India; |
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| Abstract: | A relationship between summer monsoon rainfall and sea surface temperature anomalies was investigated with the aim of predicting
the monthly scale rainfall during the summer monsoon period over a section (80°–90°E, 14°–24°N) of eastern India that depends
heavily upon the rainfall during the summer monsoon months for its agricultural practices. The association between area-averaged
rainfall of June over the study zone and global sea surface temperature (SST) anomalies for the period 1982–2008 was examined
and the variability of rainfall in monthly scale was calculated. With a view to significant variability in the rainfall in
the monthly scale, it was decided to implement the artificial neural network (ANN) for forecasting the monthly scale rainfall
using the SST anomalies as a predictor. Finally, the potential of ANN in this prediction has been assessed. |
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