WRRCSR No.1:05:93 Long-Range Prediction of Hawaii Winter Rainfall: A Canonical Correlation Analysis

Abstract

Hawaii rainfall is teleconnected to short-term climate variability in the Pacific Ocean. The summer Southern Oscillation Index (SOI) and summer sea-level pressure (SLP) over the North Pacific are used as predictors, and winter rainfall indices from three islands of Hawaii as predictands. To consolidate the large data array of the SLP field prior to prediction experiments, lagged correlation and empirical orthogonal function analyses are used. Canonical correlation analysis has been used for predicting Hawaii winter rainfall. Among many schemes tested, the one that includes the summer SOI and the first four eigenmodes from summer SLP as predictors yields the best predictions. The cross validation technique has also been used to estimate the overall forecast skill of various schemes and the results are consistent with those from prediction experiments. Winter rainfall in Hawaii can be predicted with a good degree of success two seasons in advance by using the summer SOI and the first four eigenmodes of summer SLP over the North Pacific as predictors.