Variability of the deep South China Sea circulation derived from HYCOM reanalysis data

Yaohua Zhu Guojiao Cao Yonggang Wang Shujiang Li Tengfei Xu Dingqi Wang Fei Teng Zexun Wei

Yaohua Zhu, Guojiao Cao, Yonggang Wang, Shujiang Li, Tengfei Xu, Dingqi Wang, Fei Teng, Zexun Wei. Variability of the deep South China Sea circulation derived from HYCOM reanalysis data[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1952-6
Citation: Yaohua Zhu, Guojiao Cao, Yonggang Wang, Shujiang Li, Tengfei Xu, Dingqi Wang, Fei Teng, Zexun Wei. Variability of the deep South China Sea circulation derived from HYCOM reanalysis data[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1952-6

doi: 10.1007/s13131-021-1952-6

Variability of the deep South China Sea circulation derived from HYCOM reanalysis data

Funds: The National Key Research and Development Program of China under contract No. 2019YFC1408400; the National Natural Science Foundation of China under contract Nos 41876029 and 41821004.
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  • Figure  1.  Time-mean current velocity field at 3 000 m depth. The grey shading indicates water depths shallower than 3 000 m. Abbreviations NE, NW, SW, and SE denote the northeastern, northwestern, southwestern, and southeastern sub-basins, respectively. N central and S central indicate the northern and southern central sub-basins, respectively. Blue lines stand for transects through which monthly mean climatology of the deep boundary circulation is estimated.

    Figure  2.  Standard deviations of u (a), and v (b) components at 3 000 m, respectively. Stippled area denotes STDs greater than 3 cm/s.

    Figure  3.  Monthly mean circulation at 3 000 m in December (a), January (b), February (c), March (d), April (e), and May (f).

    Figure  4.  Monthly mean circulation at 3 000 m in June (a), July (b), August (c), September (d), October (e), and November (f).

    Figure  5.  Annual cycle of normalized fluxes through boundary transects. Transects 1, 2, 3, and 4 indicate the northern, western, southern, and eastern boundaries, respectively.

    Figure  6.  Spatial structure (a), temporal variation (b), associated power spectrum density (c) and wavelet analysis (d) of the first EOF mode.

    Figure  7.  Spatial structure (a), temporal variation (b), associated power spectrum density (c) and wavelet analysis (d) of the second EOF mode.

    Figure  8.  Spatial structure (a), temporal variation (b), associated power spectrum density (c) and wavelet analysis (d) of the third EOF mode.

    Figure  9.  Spatial structure (a), temporal variation (b), associated power spectrum density (c) and wavelet analysis (d) of the fourth EOF mode.

    Figure  10.  The linear trend of current velocity (a), and decadal change of deep circulation (b) (2006–2015 mean minus 1996–2005 mean). In a, only the trend above the 95% confidence level is presented.

    A1.  Monthly mean circulation averaged between 2 500 m and 4 000 m in December (a), January (b), February (c), March (d), April (e), and May (f).

    A2.  Monthly mean circulation averaged between 2 500 m and 4 000 m in June (a), July (b), August (c), September (d), October (e), and November (f).

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出版历程
  • 收稿日期:  2021-07-22
  • 录用日期:  2021-08-26
  • 网络出版日期:  2021-11-04

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