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Intercomparison of Global Sea Surface Salinity from Multiple Datasets over 2011–2018

Hao Liu, Zexun Wei

2021Remote Sensing15 citationsDOIOpen Access PDF

Abstract

The variability in sea surface salinity (SSS) on different time scales plays an important role in associated oceanic or climate processes. In this study, we compare the SSS on sub-annual, annual, and interannual time scales among ten datasets, including in situ-based and satellite-based SSS products over 2011–2018. Furthermore, the dominant mode on different time scales is compared using the empirical orthogonal function (EOF). Our results show that the largest spread of ten products occurs on the sub-annual time scale. High correlation coefficients (0.6~0.95) are found in the global mean annual and interannual SSSs between individual products and the ensemble mean. Furthermore, this study shows good agreement among the ten datasets in representing the dominant mode of SSS on the annual and interannual time scales. This analysis provides information on the consistency and discrepancy of datasets to guide future use, such as improvements to ocean data assimilation and the quality of satellite-based data.

Topics & Concepts

Empirical orthogonal functionsEnvironmental scienceSSS*ClimatologySatelliteMode (computer interface)Scale (ratio)Data assimilationConsistency (knowledge bases)MeteorologyComputer scienceGeologyGeographyAerospace engineeringArtificial intelligenceOperating systemCartographyEngineeringOceanographic and Atmospheric ProcessesClimate variability and modelsArctic and Antarctic ice dynamics
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