How Variable Is the Uncertainty in ENSO Sea Surface Temperature Prediction?

The magnitude of seasonal predictability for a variable depends on departure of its probability density function (PDF) for a particular season from the corresponding climatological PDF. Differences in the PDF can be due to differences in various moments of the PDF (e.g., mean or the spread) from their corresponding values for the climatological PDF. Year-to-year changes in which moments of the PDF systematically contribute to seasonal predictability are an area of particular interest. Previous analyses for seasonal atmospheric variability have indicated that most of atmospheric predictability is (i) due to El Nino-Southern Oscillation (ENSO) sea surface temperatures (SSTs) and (ii) primarily due to change in the mean of the PDF for the atmospheric variability with changes in the spread of the PDF playing a secondary role. Present analysis extends to the assessment of seasonal predictability of ENSO SSTs themselves. Based on analysis of seasonal hindcasts, the results indicate that the spread (or the uncertainty) in the prediction of ENSO SSTs does not have a systematic dependence on the mean of the amplitude of predicted ENSO SST anomalies, and further, year-to-year changes in uncertainty are small. Therefore, similar to the atmospheric predictability, predictability of ENSO SSTs may also reside in the prediction of its mean amplitude; spread being almost constant does not have a systematic impact on the predictability.