Statistical prediction of ENSO (Nino 3) using sub-surface temperature data

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Oceanography: General: Ocean Predictability And Prediction (3238), Oceanography: General: Equatorial Oceanography, Oceanography: General: Climate And Interannual Variability (1616, 1635, 3305, 3309, 4513), Oceanography: Physical: Enso (4922)

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A number of statistical schemes for predicting the evolution of the El Niño-Southern Oscillation (ENSO) have been developed in recent years. These tend to show some skill out to 9 to 12 months from late in the southern autumn, but only limited skill for a few months from late summer through the so-called ``predictability barrier''. More recently statistical models utilizing sub-surface temperature data have shown improvement of skill over persistence through this autumn period. Empirical Orthogonal Function analysis is used to extract the dominant signals in the sub-surface variability. The resulting statistical model shows similar skill to that obtained using other simple indices of sub-surface temperature, such as the warm water volume or average depth of the 20°C isotherm, or from coupled ocean - atmosphere models. These statistical models can therefore be used as a more stringent benchmark against which the complex coupled dynamical models are assessed.

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