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      Linkage Between Winter Temperatures in the Yellow Sea and Atmospheric Circulation Indices

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          Abstract

          This study investigated the linkage between winter temperature in the Yellow Sea (YS), China, and atmospheric indices and established this linkage through statistical models. The water temperature was obtained through hindcast simulation using a global–regional nested ocean model for the period of 1958–2007. The interannual variations of the simulated temperature were validated using satellite and in-situ observations. In the YS, the winter sea surface temperature (SST) had obvious interannual variations, with the maximum SST exceeding 2˚C, and a significant shift from the cold to warm phase during 1988–1989. Based on the mechanism study, statistical models for the variations of water temperature in the YS were established using suitable atmospheric indices as predictors. For the northern YS (NYS) and the coastal region of the southern YS (SYS), statistical models of SST were established using linear regression based on the December–January–February mean Arctic oscillation index (AOI), representing the dominant large-scale atmospheric variability in boreal winter. For the YS warm current (YSWC) region, statistical models were established using both the AOI and the first principal component of the local wind stress curl (PC1-Curl), derived from the empirical orthogonal functions analysis. The PC1-Curl represents the influence of the local wind stress curl on the west-to-east shifts of the YSWC pathway. The applications proved that the models presented in this study have the ability to estimate winter temperatures in the YS within the recent years.

          Author and article information

          Journal
          JOUC
          Journal of Ocean University of China
          Science Press and Springer (China )
          1672-5182
          07 May 2019
          01 April 2019
          : 18
          : 2
          : 261-270
          Affiliations
          [1] 1 College of Marine and Environmental Sciences, Tianjin University of Science and Technology, Tianjin 300457, China
          [2] 2 School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
          [3] 3 National Marine Environmental Forecasting Center, Beijing 100081, China
          Author notes
          *Corresponding author: WEI Hao
          Article
          s11802-019-3821-x
          10.1007/s11802-019-3821-x
          4d2b7bfe-4ac9-411e-9261-13711d53db55
          Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2019.

          The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

          History
          : 05 February 2018
          : 20 April 2018
          : 11 August 2018

          Earth & Environmental sciences,Geology & Mineralogy,Oceanography & Hydrology,Aquaculture & Fisheries,Ecology,Animal science & Zoology
          atmospheric variability,interannual variations,water temperature,empirical orthogonal function analysis,statistical model

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