Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
2.
Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
3.
Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China
4.
Navigation College, Jiangsu Maritime Institute, Nanjing 211100, China
5.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266061, China
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.
This study aims to investigate variability of the deep South China Sea (SCS) circulation using the Hybrid Coordinate Ocean Model (HYCOM) global reanalysis product. The results reveal that annual cycle is a dominant component in the deep SCS circulation. Meanwhile, the boundary circulation strength is the weakest in January and peaks between June and September. The eastern and southern boundary currents strengthen and weaken one to three months earlier than that of the western and northern boundaries. Vector Empirical Orthogonal Functions (VEOF) analysis results reveal that semiannual and intraseasonal fluctuations are significant components, of which the spatial patterns are mainly confined in the northern and western boundary areas as well as the southwestern sub-basin. Wavelet analysis results show the strength of significant fluctuation varies year to year. Trend analysis results indicate a decadal weakening in the deep SCS circulation. An anomalous anticyclonic circulation, 50–70 km apart from the slope break, tends to weaken the cyclonic boundary circulation in the western and northern boundaries as well as the southwestern sub-basin. This trend is similar to the observed decadal weakening in the Northern Atlantic deep circulation. Thus, the findings of this study reveal that the variability of the deep SCS circulation has a remarkable response to the climate change. The mechanisms responsible for the variability are worth pursuing if more observations are available.
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.
Figure 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).
Figure 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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