LONG-RANGE PREDICTION OF HAWAIIAN WINTER RAINFALL USING CANONICAL CORRELATION-ANALYSIS (VOL 14, PG 659, 1994)

Hawaiian rainfall is teleconnected to short-term climate variability i n the Pacific Ocean. The summer Southern Oscillation Index (SOI) and s ummer sea-level pressure (SLP) over the North Pacific are used as pred ictors, and the following winter rainfall indices from three islands o f Hawaii are used as predictands. To consolidate the large data array of the SLP field prior to prediction experiments, lagged correlation a nd empirical orthogonal function analyses are used. Canonical correlat ion analysis has been used for predicting Hawaiian winter rainfall. Am ong many schemes tested, the one that includes the summer SOI and the first four eigenmodes from summer SLP as predictors yields the best pr edictions. Cross-validation techniques have 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 a dvance using the summer SOI and the first four eigenmodes of summer SL P over the North Pacific as predictors.