[A-OS21] Global ocean observation networks: Current status, results, re-assessments, and future perspectives

[AOS21-P08] Spatial Pattern of Interannual Sea Surface Salinity Variability in the Global Ocean as Revealed by Cluster Analysis

*Shota Katsura¹, Shoichiro Kido², Janet Sprintall¹, Youichi Tanimoto^3,2, Masami Nonaka² (1.Scripps Institution of Oceanography, University of California, San Diego, 2.Application Laboratory, Japan Agency for Marine-Earth Science and Technology, 3.Faculty of Environmental Earth Science and Graduate School of Environmental Science, Hokkaido University)

Keywords:Sea surface salinity, Interannual Variability, Global Ocean

Since spatial distribution and variation of salinity in the upper ocean mainly reflect freshwater flux at the sea surface, sea surface salinity (SSS) can be useful as a measure of intensity in the hydrological cycle. SSS variability also affects ocean circulation and stratification in the upper ocean by modifying seawater density. Thus, knowledge of SSS variability is important for better understanding of the global hydrological cycle and ocean and climate variability. Recent accumulation of salinity data from Argo profiling floats enables us to describe the features of the SSS interannual variability in the global ocean. To classify the interannual variability of the global SSS into dominant modes and provide a global map of their horizontal distributions, we applied cluster analysis to SSS anomalies from the gridded Argo SSS data during 2003–2020. SSS variability over the global ocean was classified into seven dominant modes (Clusters 1 to 7). Among the seven clusters, Cluster 1 and 3 were dominant in the subtropical Pacific and the eastern tropics in the South Pacific, respectively, and showed a decadal variability with fresh and salty SSS during positive phases of the Pacific Decadal Oscillation, respectively. Cluster 2 and 4 showed the SSS interannual variability related to the El Nino-Southern Oscillation, which decreased and increased during El Nino events, respectively, and they were dominant mainly in the equatorial Pacific and the western parts of the subtropics in each ocean basin, respectively. SSS variability of Cluster 5 was significantly correlated with the Antarctic Oscillation index and dominant mainly in the subantarctic region south of Australia. SSS variability of Cluster 6 was dominant in the subpolar North Atlantic and the southeast Indian Ocean and was characterized by decadal variability. Finally, Cluster 7 showed a salinification trend and was mainly dominant in the western boundary current region of each ocean basin except for the North Pacific. The global map of the dominant modes of the SSS interannual variability presented in this study will be useful for future design of salinity observations in the global ocean to better monitor signals of the climate variability and the hydrological cycle in SSS variability.