| DUAN Rui,YANG Kunde,MA Yuanliang,HU Tao. 2012. A study of the mixed layer of the South China Sea based on the multiple linear regression. Acta Oceanologica Sinica, (6):19－31 |
| A study of the mixed layer of the South China Sea based on the multiple linear regression |
| A study of the mixed layer of the South China Sea based on the multiple linear regression |
| Received:April 23, 2011 Revised:January 10, 2012 |
| DOI：10.1007/s13131-012-0250-8 |
| Key words:mixed layer multiple linear regression South China Sea vertical mixing model |
| 中文关键词: mixed layer multiple linear regression South China Sea vertical mixing model |
| 基金项目:The National Natural Science Foundation of China under contract No. 11174235; the Science and Technology Development Project of Shaanxi Province of China under contract No. 2010KJXX-02; the Program for New Century Excellent Talents in University of China under contract No. NCET-08-0455; the Science and Technology Innovation Foundation of Northwestern Polytechnical University of China; the Doctorate Foundation of Northwestern Polytechnical University of China under contract No. CX201226. |
| Author Name | Affiliation | E-mail | | DUAN Rui | College of Marine, Northwestern Polytechnical University, Xi'an 710072, China | | | YANG Kunde | College of Marine, Northwestern Polytechnical University, Xi'an 710072, China | ykdzym@nwpu.edu.cn | | MA Yuanliang | College of Marine, Northwestern Polytechnical University, Xi'an 710072, China | | | HU Tao | Key Laboratory of Underwater Acoustic Environment, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China | |
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| Abstract: |
| Multiple linear regression (MLR) method was applied to quantify the effects of the net heat flux (NHF), the net freshwater flux (NFF) and the wind stress on the mixed layer depth (MLD) of the South China Sea (SCS) based on the simple ocean data assimilation (SODA) dataset. The spatio-temporal distributions of the MLD, the buoyancy flux (combining the NHF and the NFF) and the wind stress of the SCS were presented. Then using an oceanic vertical mixing model, the MLD after a certain time under the same initial conditions but various pairs of boundary conditions (the three factors) was simulated. Applying the MLR method to the results, regression equations which modeling the relationship between the simulated MLD and the three factors were calculated. The equations indicate that when the NHF was negative, it was the primary driver of the mixed layer deepening; and when the NHF was positive, the wind stress played a more important role than that of the NHF while the NFF had the least effect. When the NHF was positive, the relative quantitative effects of the wind stress, the NHF, and the NFF were about 10, 6 and 2. The above conclusions were applied to explaining the spatio-temporal distributions of the MLD in the SCS and thus proved to be valid. |
| 中文摘要: |
| Multiple linear regression (MLR) method was applied to quantify the effects of the net heat flux (NHF), the net freshwater flux (NFF) and the wind stress on the mixed layer depth (MLD) of the South China Sea (SCS) based on the simple ocean data assimilation (SODA) dataset. The spatio-temporal distributions of the MLD, the buoyancy flux (combining the NHF and the NFF) and the wind stress of the SCS were presented. Then using an oceanic vertical mixing model, the MLD after a certain time under the same initial conditions but various pairs of boundary conditions (the three factors) was simulated. Applying the MLR method to the results, regression equations which modeling the relationship between the simulated MLD and the three factors were calculated. The equations indicate that when the NHF was negative, it was the primary driver of the mixed layer deepening; and when the NHF was positive, the wind stress played a more important role than that of the NHF while the NFF had the least effect. When the NHF was positive, the relative quantitative effects of the wind stress, the NHF, and the NFF were about 10, 6 and 2. The above conclusions were applied to explaining the spatio-temporal distributions of the MLD in the SCS and thus proved to be valid. |
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