A 1/8° coupled biochemical-physical Indian Ocean Regional Model: Physical results and validation

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• 作者：Ke Huang ; Sergio Derada ; Huijie Xue ; Peng Xiu ; Fei Chai ; Qiang Xie…
• 关键词：Monsoon ; Seasonal and interannual variability ; Indian Ocean ; Arabian Sea ; Surface and subsurface variability ; Wave propagation
• 刊名：Ocean Dynamics
• 出版年：2015
• 出版时间：August 2015
• 年：2015
• 卷：65
• 期：8
• 页码：1121-1142
• 全文大小：18,615 KB
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• 作者单位：Ke Huang (1) (2)
  Sergio Derada (3)
  Huijie Xue (1) (4)
  Peng Xiu (1)
  Fei Chai (4)
  Qiang Xie (1) (5)
  Dongxiao Wang (1)
  
  1. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, Guangdong, China
  2. Graduate University of Chinese Academy of Sciences, Beijing, China
  3. Naval Research Laboratory, Stennis Space Center, Hancock, MS, 39529, USA
  4. School of Marine Sciences, University of Maine, 5706 Aubert Hall, Orono, ME, 04469-5706, USA
  5. Sanya Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan, China
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Oceanography
  Geophysics and Geodesy
  Meteorology and Climatology
  Fluids
  Structural Foundations and Hydraulic Engineering
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1616-7228

文摘

A coupled physical-biochemical Indian Ocean Regional Model (IORM), based on the Navy Coastal Ocean Model (NCOM) and the Carbon Silicate Nitrogen Ecosystem (CoSiNE) model was configured with the primary objective of providing an accurate estimate of the oceanic physical state along with the biochemical processes simulated by CoSiNE to understand the variability in the Indian Ocean (IO). The model did not assimilate any data; instead, weak relaxation of temperature and salinity was implemented to keep the model stable in the long-term simulations. In this study, the skill of the IORM in simulating physical states in the IO was evaluated. Basin-scale surface circulation and cross-sectional transports were compared to observations, which demonstrated that the model replicated most of the observed features with reasonably good accuracy. Consistency and biases in the?upper ocean temperature, salinity, and mixed layer depth were also analyzed. Lastly, the seasonality in the IO, its response to monsoonal forcing, and the evolution and dynamics of surface and subsurface dipole events were examined. The IORM reproduced most of the dynamic features including Ekman pumping, wave propagation, and climate variability at both annual and interannual time scales. The internal ocean dynamics and behavior of the modeled sea surface temperature anomaly (SSTA) suggest a coupled ocean/atmosphere instability that will require further research, including sensitivity experiments to realize improvements in model parameterization.