Threshold autoregression models for forecasting El Nino events

In this paper, monthly mean SST data in a large area are used.After the spacial average of the data is carried out and the secular monthly means are substracted, a time series (Jan.1951-Dec.1985) of SST anomalies of the cold tongue water area in the eastern tropical Pacific Ocean is obtained.On the basis of the time series, an autoregression model, a self-exciting threshold autoregression model and an open loop autoregression model are developed respectively.The interannual variations are simulated by means of those models.The simulation results show that all the three models have made very good hindcasting for the nine El Nino events since 1951.In order to test the reliability of the open loop threshold model, extrapolated forecast was made for the period of Jan.1986-Feb.1987.It can be seen from the forecasting that the model could forecast well the beginning and strengthening stages of the recent El Nino event (1986-1987).Correlation coefficients of the estimations to observations are respectively 0.89,0.88 and 0.89. It is obvious that all the models work well and the open loop threshold one is the best.So the open loop threshold autoregression model is a useful tool for monitoring the SST interannual variation of the cold tongue water area in the Eastern Equatorial Pacific Ocean and for estimating the El Nino strength.