日本地球惑星科学連合2022年大会

講演情報

[J] ポスター発表

セッション記号 A (大気水圏科学) » A-OS 海洋科学・海洋環境

[A-OS21] 全球海洋観測システムの現状・成果と将来:ニーズへの適合と発展

2022年6月1日(水) 11:00 〜 13:00 オンラインポスターZoom会場 (10) (Ch.10)

コンビーナ:細田 滋毅(国立研究開発法人海洋研究開発機構)、コンビーナ:増田 周平(海洋研究開発機構)、藤井 陽介(気象庁気象研究所)、コンビーナ:藤木 徹一(国立研究開発法人 海洋研究開発機構)、座長:細田 滋毅(国立研究開発法人海洋研究開発機構)

11:00 〜 13:00

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

*桂 将太1木戸 晶一郎2、Sprintall Janet1谷本 陽一3,2野中 正見2 (1.カリフォルニア大学サンディエゴ校スクリプス海洋研究所、2.海洋研究開発機構アプリケーションラボ、3.北海道大学環境科学院)

キーワード:海面塩分、経年変動、全球海洋

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.