Interannual Variations in the Summer Coastal Upwelling in the Northeastern South China Sea

Author:

Chen Wuyang12,Tong Yifeng13,Li Wei13,Ding Yang4ORCID,Li Junmin15ORCID,Wang Wenhua2,Shi Ping1

Affiliation:

1. State Key Laboratory of Tropical Oceanography, Guangdong Provincial Observation and Research Station for Marine Ecosystem in the Typical Upwelling Area, Key Laboratory of Science and Technology on Operational Oceanography, Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 511458, China

2. School of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang 524088, China

3. University of Chinese Academy of Sciences, Beijing 100049, China

4. Key Laboratory of Physical Oceanography, MOE, Ocean University of China, Qingdao 266100, China

5. Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572000, China

Abstract

This study scrutinizes interannual (2003–2023) variations in coastal upwelling along the Guangdong Province during summers (June–August) in the northeastern South China Sea (NESCS) by comprehensively applying the moderate-resolution imaging spectroradiometer (MODIS) remote sensing sea surface temperature (SST) and chlorophyll concentration (CHL) data and the model reanalysis product. The results show that SST and upwelling intensity in the sea area have significant (p < 0.05) rising trends in the last 21 years. The CHL shows an upward but insignificant trend, which is affected simultaneously by the rise in SST and the enhancement of upwelling. Further analysis reveals that the interannual variations in upwelling are robustly related to the wind fields’ variations in the coastal region. A clockwise/counter-clockwise anomaly in the wind field centered on the NESCS facilitates alongshore/onshore winds near the Guangdong coast, which can strengthen/weaken coastal upwelling. Based on the correlation between wind field variations and large-scale climate factors, long-term variations in the upwelling intensity can be primarily predicted by the Oceanic Niño Index.

Funder

Science and Technology Projects of Guangdong Province

Guangdong Basic and Applied Basic Research Foundation

Guangdong Provincial Observation and Research Station for Coastal Upwelling Ecosystem

Hainan Provincial Natural Science Foundation of China

South China Sea Institute of Oceanology of the Chinese Academy of Sciences

Publisher

MDPI AG

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