A study of the mixed layer of the South China Sea based on the multiple linear regression
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A study of the mixed layer of the South China Sea based on the multiple linear regression DUAN Rui1 , YANG Kunde1∗ , MA Yuanliang1 , HU Tao2 1 2
College of Marine, Northwestern Polytechnical University, Xi’an 710072, China Key Laboratory of Underwater Acoustic Environment, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
Received 23 April 2011; accepted 10 January 2012 ©The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2012
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. Key words: mixed layer, multiple linear regression, South China Sea, vertical mixing model
and heat flux were primarily responsible for the annual variation while a large part of the semiannual variation was attributed to the local Ekman pumping. The similar conclusions were presented by Shi et al. (2001) and Sun et al. (2007) using different dataset. Although the factors influencing the MLD can be found by data analysis, the relative quantitative effect of the MLD change caused by each factor cannot be given by this method. It is because these factors are always coupled. For example, enhanced evaporation associated with the development of the southwest monsoon causes significant latent heat loss to the atmosphere (Qu, 2001). To understand the influence of a single factor on the MLD, numerical simulations were performed. Fan et al. (2010) analyzed the sensitivity of the MLD with the sea surface wind stress, the net heat flux and the net freshwater flux by ignoring the impact of one factor in a simulation. In their study, the effe-
1 Introduction The South China Sea (SCS) is a large semienclosed marginal sea connected with the Pacific Ocean, the Indian Ocean, etc. Its prosperities have been studied by many researches (Qu et al., 2007; Zhuang et al., 2010). The spatio-temporal variation of the mixed layer is an
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