Abstract
[1] Ensemble predictions are performed using the LDEO5 model for the period from 1856 to 2003 based on a well developed El Niño–Southern Oscillation (ENSO) ensemble system. Information-based and ensemble-based potential predictability measures of ENSO are explored using ensemble predictions and the recently developed framework of predictability. Relationships of these potential predictability measures and actual predictability measures are investigated on multiple time scales from interannual to decadal. Results show that among three information-based potential predictability measures, relative entropy (RE) is better than predictive information (PI) and predictive power (PP) in quantifying correlation-based prediction skill, whereas PI and PP are better indicators in estimating mean square error (MSE)-based prediction skill. The primary reason for these relationships is analyzed and the control factors of the potential predictability measures are identified. It is found that RE is dominated by the signal component, but the dispersion component has a comparable contribution during weak ENSO periods.
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