期刊
JOURNAL OF OCEANOLOGY AND LIMNOLOGY
卷 39, 期 2, 页码 447-457出版社
SCIENCE PRESS
DOI: 10.1007/s00343-020-9121-x
关键词
chlorophyll (CHL); mixed layer depth; multiple linear regression; sea surface temperature
资金
- National Key Research and Development Program [2016YFC1401004, 2016YFC1401008]
- National Natural Science Foundation for Young Scientists of China [41606200]
- Qingdao Pilot National Laboratory for Marine Science and Technology [2018ASKJ01]
- Key R&D Program of Shandong Province, China [2019GHY112055]
- National Natural Science Foundation of China [41676168, 41376028]
- NSFC-Innovation Research Group of Sciences Fund [41421005]
- NSFC-Shandong Joint Fund for Marine Science Research Centers [U1406401]
This study quantified the relationship between chlorophyll (CHL) and environmental factors (SST, MLD, and WS) in the subtropical gyres, and found that mixed-layer depth (MLD) was positively correlated with CHL, sea surface temperature (SST) was negatively correlated with CHL, and the correlation between CHL and wind stress (WS) could be either positive or negative. Models established through regression analysis showed that SST and MLD were major determinants of CHL change in the open ocean.
Many previous studies of the impact of oceanic environmental factors on chlorophyll (CHL) in a specific region focused on sea surface temperature (SST), mixed-layer depth (MLD), or wind stress (WS) alone. In this study, relationship between CHL and all those environmental factors (SST, MLD, and WS) in the open ocean was quantified for five regions within the subtropical gyres and the variation trend of 13-year (2003-2015) was analyzed using satellite observations and Argo measurements. The correlation analysis results show that MLD was correlated positively with CHL, SST was correlated negatively with CHL, and the correlation between CHL and WS was either positive or negative. Based on the significance of the correlations, models representing the relationships were established using the multiple linear regression and analyzed, showing that the environmental factors were the major determinants of CHL change. The regression coefficients show that both SST and MLD have remarkable effect on CHL. Our derived models could be used to diagnose the past changes, understand present variability, and predict the future state of CHL changes based on environmental factors, and help us understand the dynamics of CHL variation in the open ocean.
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