Properties of winter mixed layer variability on the shelf-slope region facing the Kuroshio—study of Tosa Bay, southern Japan

Autor: Hiroshi Kuroda, Tomowo Watanabe, Takashi Setou, Kazuhiro Aoki, Yuichi Hirota, Daisuke Takahashi
Rok vydání: 2013
Předmět:
Zdroj: Ocean Dynamics. 64:47-60
ISSN: 1616-7228
1616-7341
DOI: 10.1007/s10236-013-0670-9
Popis: To examine the properties of winter mixed layer (ML) variability in the shelf-slope waters facing the Kuroshio, we analyzed historical temperature records and the simulated results of a triply nested high-resolution numerical model. As a candidate of the shelf-slope waters, we focused on Tosa Bay, off the southern Japan. A time series of observed monthly mean ML temperatures and depths in the bay exhibits a remarkable seasonal variation. The period when the ML develops can be divided into two regimes: from September to November, when the sea surface cooling is gradually enhanced, the ML temperature and depth decreases and increases, respectively; from January to March, the ML temperature and depth are kept nearly constant, while the sea surface cooling in January reaches its annual maximum. In the latter regime, variance for the monthly mean ML depth is the largest of the year. To further study the ML properties in the latter regime corresponding to winter, we examined simulated results. It was found that the largest variance for ML depth is attributed to a dominant intramonthly variation. This is related to a submesoscale variation with typical spatial scales of 10–20 km, induced by the Kuroshio and its frontal disturbances. Simulated monthly mean heat balance within the ML showed that heat advection balances with heat flux at the sea surface and entrainment through the ML bottom. Moreover, the monthly mean heat advection is determined mainly by the intramonthly eddy heat advection, suggesting that the high-frequency intramonthly variation related to submesoscale variations contributes significantly to the low-frequency monthly variations of the ML in winter.
Databáze: OpenAIRE
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