A climatic dataset of ocean vertical turbulent mixing coefficient based on real energy sources

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• 作者：Yu Zhang (1)
  YiHua Lin (2)
  RuiXin Huang (3)
  
• 关键词：energy conservation ; spectrum analysis ; turbulent mixing parameterization ; vertical turbulent mixing coefficient
• 刊名：Science China Earth Sciences
• 出版年：2014
• 出版时间：October 2014
• 年：2014
• 卷：57
• 期：10
• 页码：2435-2446
• 全文大小：2,546 KB
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• 作者单位：Yu Zhang (1)
  YiHua Lin (2)
  RuiXin Huang (3)
  
  1. National Marine Environmental Forecasting Center, Beijing, 100081, China
  2. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
  3. Department of Physical Oceanography, Woods Hole Oceanographic Institution, Woods Hole, MA, 02543, USA
  
• ISSN：1869-1897

文摘

Using data on wind stress, significant height of combined wind waves and swell, potential temperature, salinity and seawater velocity, as well as objectively-analyzed in situ temperature and salinity, we established a global ocean dataset of calculated wind- and tide-induced vertical turbulent mixing coefficients. We then examined energy conservation of ocean vertical mixing from the point of view of ocean wind energy inputs, gravitational potential energy change due to mixing (with and without artificially limiting themixing coefficient), and K-theory vertical turbulent parameterization schemes regardless of energy inputs. Our research showed that calculating the mixing coefficient with average data and artificial limiting the mixing coefficient can cause a remarkable lack of energy conservation, with energy losses of up to 90% and changes in the energy oscillation period. The data also show that wind can introduce a huge amount of energy into the upper layers of the Southern Ocean, and that tidesdo so in regions around underwater mountains. We argue that it is necessary to take wind and tidal energy inputs into account forlong-term ocean climate numerical simulations. We believe that using this ocean vertical turbulent mixing coefficient climatic dataset is a fast and efficient method to maintain the ocean energy balance in ocean modeling research.