Interannual variability and predictability of summertime significant wave heights in the western north pacific
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We propose and validate a linear regression model which enables us to predict the summer (June–August) mean of the monthly 90th percentile of significant wave heights (H90) in the western North Pacific (WNP). The most prevailing interannual variability of H90 is identified by applying an Empirical Orthogonal Function analysis to H90 obtained from the ERA-40 wave reanalysis as well as from the optimally interpolated TOPEX/Poseidon (OITP) wave data. It is found that the increase of H90 is correlated with cyclonic circulation in the WNP which links with warm SST anomalies in the Niño-3.4 region. We adopt zonal wind anomaly averaged over the region 5°N–15°N, 130°E–160°E (U10N) as a predictor of the first principal component (PC1) of H90, since U10N is closely correlated with the PC1 of H90. It is revealed that regression models obtained from two different wave datasets are nearly identical. The predictability of the regression model is assessed in terms of the reduction of the root-mean-square (rms) errors between H90 and the reconstructed data. The predictor is found to be successful in reducing the rms errors by up to 40% for the ERA-40 wave reanalysis and by up to 70% for the OITP wave data within the latitudinal band 10°N–25°N, though rms errors exceeding 0.3 m still remain, particularly in the East China Sea.
KeywordsWave climate predictability significant wave height Western North Pacific tropical cyclone
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