A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor

Acharya, Nachiketa ; Chattopadhyay, Surajit ; Kulkarni, Makarand A. ; Mohanty, Uma C. (2012) A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor Acta Geophysica, 60 (1). pp. 260-279. ISSN 1895-6572

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Official URL: http://link.springer.com/article/10.2478%2Fs11600-...

Related URL: http://dx.doi.org/10.2478/s11600-011-0044-y

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.

Item Type:Article
Source:Copyright of this article belongs to Springer-Verlag.
Keywords:Monthly Rainfall Forecast; Sea Surface Temperature (SST); Artificial Neural Network (ANN)
ID Code:97075
Deposited On:29 Jan 2013 04:31
Last Modified:29 Jan 2013 04:31

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