Abstract
This study demonstrates techniques that lead to improved use of ocean thermal information and more useful and informative products for monitoring variability in the tropical oceans. The method is based on statistical interpolation and is illustrated using analyses for the 20°C isotherm depth over the Pacific and Indian Oceans. A new monthly climatology is derived by exploiting the statistical interpolation method to provide an improved weighted estimate. The new climatology is shown to better represent key aspects of the tropical ocean thermal structure.
A statistical forecast based on the previous analysis and climatology significantly improves the analysis product, both in a qualitative sense and as judged by quantitative measures of the skill of the forecast and of the estimated error of the analysis. Both the new climatology and the statistical forecasting scheme are interpreted as strategies for delivering enhanced information to the analysis system.
A series of 10-day analyses are presented. It is shown that these analyses retain all the information contained in longer period analyses, at least when used with statistical forecasts, and that in addition they resolve higher-frequency events in the equatorial waveguide. The 10-day analyses have around the same absolute estimated error as the longer period analyses but substantially higher accuracy due to the larger variance of the 10-day field. Some implications of these results are discussed.
