Analysis of the Distribution and Seasonal Variability of the South China Sea Water Masses Based on the K-means Cluster Method
Abstract
:1. Introduction
2. Data and Methods
2.1. Data
2.2. Methods
3. Results
3.1. Water Masses Division
3.2. Seasonal Variation of Kuroshio Intrusion into the SCS
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Name | Symbol | Source | Depth/m | Temperature/°C | Salinity |
---|---|---|---|---|---|
Coastal Diluted Water | F | Continental runoff | <20 | About 19.5 | <31.0 |
27.0–32.1 | |||||
Nearshore Mixed Water | M | Coastal diluted water mixed with external seawater | <75 | 22.4–22.9 | 31.90–32.30 |
22.5–30.3 | 31.70–32.10 | ||||
South China Sea Surface Water | S | Western Pacific surface water | 0–100 | 21.5–29.0 | 32.70–34.60 |
0–120 | 22.0–30.5 | 32.50–34.65 | |||
South China Sea Southern Shelf water | SS | The Java Sea water mixed with the Gulf of Thailand water | 0–120 | About 28.0 | 31.90–33.20 |
Kuroshio Surface Water | KS | Kuroshio surface water | 0–100 | 25.0–30.9 | 34.45–34.70 |
34.45–34.65 | |||||
Kuroshio Subsurface Water | KU | Kuroshio subsurface water | 100–250 | 16.0–24.6 | 34.70–34.90 |
34.65–34.85 | |||||
South China Sea Subsurface Water | U | Western Pacific subsurface water | 100–200 | 15.0–21.5 | 34.00–34.70 |
120–200 | 16.0–22.0 | 34.00–34.65 | |||
South China Sea Subsurface–Intermediate Mixed Water | UI | Subtropical thermocline water in the WPO | 200–350 | 9.8–15.0 | 34.40–34.70 |
200–350 | 11.0–16.0 | 34.35–34.65 | |||
South China Sea Intermediate Water | I | Western Pacific intermediate water | 350–900 | 4.5–10.0 | 34.40–34.50 |
350–800 | 5.5–11.0 | 34.39–34.55 | |||
South China Sea Deep Water | D | Deep water in the WPO | >900 | <5.0 | 34.35–34.62 |
>800 | <5.5 | 34.30–34.70 |
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Jin, S.; Nie, X.; Wang, G.; Teng, F.; Xu, T. Analysis of the Distribution and Seasonal Variability of the South China Sea Water Masses Based on the K-means Cluster Method. J. Mar. Sci. Eng. 2023, 11, 485. https://doi.org/10.3390/jmse11030485
Jin S, Nie X, Wang G, Teng F, Xu T. Analysis of the Distribution and Seasonal Variability of the South China Sea Water Masses Based on the K-means Cluster Method. Journal of Marine Science and Engineering. 2023; 11(3):485. https://doi.org/10.3390/jmse11030485
Chicago/Turabian StyleJin, Shanshan, Xunwei Nie, Guanlin Wang, Fei Teng, and Tengfei Xu. 2023. "Analysis of the Distribution and Seasonal Variability of the South China Sea Water Masses Based on the K-means Cluster Method" Journal of Marine Science and Engineering 11, no. 3: 485. https://doi.org/10.3390/jmse11030485
APA StyleJin, S., Nie, X., Wang, G., Teng, F., & Xu, T. (2023). Analysis of the Distribution and Seasonal Variability of the South China Sea Water Masses Based on the K-means Cluster Method. Journal of Marine Science and Engineering, 11(3), 485. https://doi.org/10.3390/jmse11030485