Forecasting ENSO with a smooth transition autoregressive model
نویسندگان
چکیده
This study examines the benefits of nonlinear time series modelling to improve forecast accuracy of the El Niño Southern Oscillation (ENSO) phenomenon. The paper adopts a smooth transition autoregressive (STAR) modelling framework to assess the potentially regime-dependent dynamics of sea surface temperature anomaly. The results reveal STAR-type nonlinearities in ENSO dynamics, resulting in superior out-of-sample forecast performance of STAR over the linear autoregressive models. The advantage of nonlinear models is especially apparent in the shortand intermediate-term forecasts. These results are of interest to researchers and policy makers in the fields of climate dynamics, agricultural production, and environmental management.
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عنوان ژورنال:
- Environmental Modelling and Software
دوره 40 شماره
صفحات -
تاریخ انتشار 2013