Journal : Acta Geophysica
Article : A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor

Authors :
Yamasaki, K.
Department of Earth and Planetary Sciences, Faculty of Science, Kobe University, Nada, Kobe, Japan,,
Teisseyre, R.
Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland,,
Li, C.
School of Computer Engineering and Science, Shanghai University, Shanghai, China,,
Majdański, M.
Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland,,
Trojanowski, J.
Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland,,
Öztürk, S.
Gümüşhane University, Department of Geophysics, Gümüşhane, Turkey,,
Chattopadhyay, A.
Department of Applied Mathematics, Indian School of Mines, Dhanbad, India,,
Beziuk, G.
Wroclaw University of Technology, Institute of Telecommunications and Acoustics, Wrocław, Poland,,
Giang, N.V.
Institute of Geophysics, VAST, Hanoi, Vietnam,,
Di Cristo, C.
Dipartimento di Meccanica, Strutture, Ambiente e Territorio, Universita` di Cassino, Cassino, Italy,,
Radice, A.
Dipartimento di Meccanica, Strutture, Ambiente e Territorio, Universita` di Cassino, Cassino, Italy,,
Kalinowska, M.B.
Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland,,
Nie, R.-S.
State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan Province, China,,
Acharya, N.A.
Centre for Atmospheric Sciences, Indian Institute of Technology, New Delhi, India,,
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.

Keywords : monthly rainfall forecast, sea surface temperature (SST),
Publishing house : Instytut Geofizyki PAN
Publication date : 2012
Number : Vol. 60, no. 1
Page : 260 – 279

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Qute : Yamasaki, K. ,Teisseyre, R. ,Li, C. ,Majdański, M. ,Trojanowski, J. ,Öztürk, S. ,Chattopadhyay, A. ,Beziuk, G. ,Giang, N.V. ,Di Cristo, C. ,Radice, A. ,Kalinowska, M.B. ,Nie, R.-S. ,Acharya, N.A. ,Acharya, N.A. , A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor. Acta Geophysica Vol. 60, no. 1/2012