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• W2754114494 abstract "The skill of the statistical as well as physics-based coupled climate models in predicting the El Ni~no-Southern Oscillation (ENSO) is limited by their inability to represent the observed ENSO nonlinearity. A promising alternative, namely a deterministic nonlinear dynamical model derived from an observed ENSO timeseries, however, has remained elusive. Here we discover such a phenomenological nonlinear dynamical model that embodies known physical processes responsible for the self-sustained quasi-oscillatory character of the ENSO and its observed spectrum of variability. High predictive potential of the model is demonstrated and the intrinsic nonlinearity of the ENSO is shown to be critical for overcoming the Spring Predictability Barrier to a large extent. The unique methodology presented here has the potential for constructing similar models for other geophysical systems." @default.
• W2754114494 created "2017-09-25" @default.
• W2754114494 creator A5066395508 @default.
• W2754114494 creator A5090677791 @default.
• W2754114494 date "2017-09-08" @default.
• W2754114494 modified "2023-09-27" @default.
• W2754114494 title "Discovery of a Phenomenological Dynamical Model for Predicting the El Niño-Southern Oscillation" @default.
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• W2754114494 hasPublicationYear "2017" @default.
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