An assessment of oceanic variability for 1960-010 from the GFDL ensemble coupled data assimilation

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• 作者：You-Soon Chang (1) (2)
  Shaoqing Zhang (1)
  Anthony Rosati (1)
  Thomas L. Delworth (1)
  William F. Stern (1)
  
• 关键词：Ensemble coupled data assimilation ; Reanalysis ; Assessment ; Oceanic variability
• 刊名：Climate Dynamics
• 出版年：2013
• 出版时间：4 - February 2013
• 年：2013
• 卷：40
• 期：3
• 页码：775-803
• 全文大小：5594KB
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• 作者单位：You-Soon Chang (1) (2)
  Shaoqing Zhang (1)
  Anthony Rosati (1)
  Thomas L. Delworth (1)
  William F. Stern (1)
  
  1. Geophysical Fluid Dynamics Laboratory, Princeton University Forrestal Campus, 201 Forrestal Road, Princeton, NJ, 08540, USA
  2. University Corporation for Atmospheric Research, Boulder, CO, USA
  
• ISSN：1432-0894

文摘

The Geophysical Fluid Dynamics Laboratory has developed an ensemble coupled data assimilation (ECDA) system based on the fully coupled climate model, CM2.1, in order to provide reanalyzed coupled initial conditions that are balanced with the climate prediction model. Here, we conduct a comprehensive assessment for the oceanic variability from the latest version of the ECDA analyzed for 51?years, 1960-010. Meridional oceanic heat transport, net ocean surface heat flux, wind stress, sea surface height, top 300?m heat content, tropical temperature, salinity and currents are compared with various in situ observations and reanalyses by employing similar configurations with the assessment of the NCEP’s climate forecast system reanalysis (Xue et al. in Clim Dyn 37(11):2511-539, 2011). Results show that the ECDA agrees well with observations in both climatology and variability for 51?years. For the simulation of the Tropical Atlantic Ocean and global salinity variability, the ECDA shows a good performance compared to existing reanalyses. The ECDA also shows no significant drift in the deep ocean temperature and salinity. While systematic model biases are mostly corrected with the coupled data assimilation, some biases (e.g., strong trade winds, weak westerly winds and warm SST in the southern oceans, subsurface temperature and salinity biases along the equatorial western Pacific boundary, overestimating the mixed layer depth around the subpolar Atlantic and high-latitude southern oceans in the winter seasons) are not completely eliminated. Mean biases such as strong South Equatorial Current, weak Equatorial Under Current, and weak Atlantic overturning transport are generated during the assimilation procedure, but their variabilities are well simulated. In terms of climate variability, the ECDA provides good simulations of the dominant oceanic signals associated with El Nino and Southern Oscillation, Indian Ocean Dipole, Pacific Decadal Oscillation, and Atlantic Meridional Overturning Circulation during the whole analyzed period, 1960-010.