Time-dependent spatial wavenumber spectra derived from merged sea surface temperature data

Monthly wavenumber spectra of sea surface temperatures (SST) have been estimated in two regions near the Kuroshio, in the recirculation and the Kuroshio Extension regions, using the merged SST product to determine the statistical parameter (spatial decorrelation scale) required for optimal interpolation of a high-resolution SST dataset. The two-dimensional wavelet transform was used for analysis. Estimates were made of daily mean and daily minimum SSTs. These do not significantly differ, which suggests that the same covariance matrix can be used for the daily mean and minimum in the merging procedure. The seasonality of wavenumber spectra is significant. There are also large differences between those in the recirculation region and in the Kuroshio Extension region. Therefore, it is recommended that the covariance matrix in the merging process for high-resolution SST dataset be defined as a function of time and space. Improvements of the merging methodology are discussed.