4.7 Article

Forced vs. Intrinsic Wintertime Submonthly Variability of Sea Surface Temperature in the Midlatitude Western North Pacific

期刊

FRONTIERS IN MARINE SCIENCE
卷 9, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fmars.2022.847144

关键词

midlatitude; submonthly variability; air-sea interaction; stochastic climate model; GOTM model

资金

  1. National Natural Science Foundation of China [41906001]
  2. Natural Science Foundation of Jiangsu Province [BK20190501]
  3. Fundamental Research Funds for the Central Universities [B210202137]

向作者/读者索取更多资源

This study evaluates the relative importance of forced and intrinsic SST variability in the Kuroshio-Oyashio Extension (KOE) region on submonthly timescales. The results show that forced SST variability accounts for a very small fraction of the total variability in the KOE region, indicating the dominance of intrinsic oceanic processes.
The relative importance of wintertime forced and intrinsic SST variability in the Kuroshio-Oyashio Extension (KOE) region on submonthly timescales (2-10 and 10-30 days) is evaluated based on theoretical, observational, and modeling analysis. It is shown that the theoretical framework extended from the stochastic climate model has difficulties in representing observed SST variability on such short scales. We then employ the single-column General Ocean Turbulence Model (GOTM) to explicitly evaluate the SST variability forced by atmospheric disturbances. Results show that in the KOE region forced SST variability is responsible for a very small fraction of the total variability (<10%) on the submonthly scales, indicating the dominance of intrinsic oceanic processes. Outside the KOE forced variability dominates. By means of sensitivity experiments, the key physical factors are identified: upper ocean vertical mixing, wind stress forcing (mainly for outside KOE), and latent heat flux, the former two of which are not considered in the theoretical framework. The above results are robust against different levels of submonthly SST variability.

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