2020
DOI: 10.1002/joc.6774
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Spatial distribution of spectral SST oscillations over the equatorial pacific in the period 1888–2014

Abstract: This study identified and analysed the spatial and temporal patterns of spectral oscillation ranges of the monthly sea surface temperature, SST, over the tropical Pacific region, from 1888 to 2014, through wavelet analysis. The strategic steps considered the variance analysis, obtained from the wavelet computation, for each single grid point instead of the analysis of a spatial mean variance, as is commonly done, allowing us to visualize the spatial distribution of SST variance during different time periods. T… Show more

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“…Additionally, a longer time scale of 9 to 12 years (quasi-decadal) appears after the 1990s. The quasi-decadal signal reported in this study is consistent with the long SST time series analysis results reported by Silva et al [83,84], showing that the signal becomes stronger after the 1970s, consistent with our XWT analysis results, where a more significant relationship in terms of energy is demonstrated between the PC1-SPI and ONI series on the quasi-decadal scale in the 1994-2012 period. Furthermore, two minima of the quasi-decadal oscillation (1999 and 2010) in the ONI series (Figure 6) are in- Our analysis was based on the wavelet technique, which has the advantage of finding the variability scales with maximum local variances in time.…”
Section: Discussionsupporting
confidence: 93%
“…Additionally, a longer time scale of 9 to 12 years (quasi-decadal) appears after the 1990s. The quasi-decadal signal reported in this study is consistent with the long SST time series analysis results reported by Silva et al [83,84], showing that the signal becomes stronger after the 1970s, consistent with our XWT analysis results, where a more significant relationship in terms of energy is demonstrated between the PC1-SPI and ONI series on the quasi-decadal scale in the 1994-2012 period. Furthermore, two minima of the quasi-decadal oscillation (1999 and 2010) in the ONI series (Figure 6) are in- Our analysis was based on the wavelet technique, which has the advantage of finding the variability scales with maximum local variances in time.…”
Section: Discussionsupporting
confidence: 93%