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Strongly Coupled Data Assimilation Using Leading Averaged Coupled Covariance (LACC). Part II: CGCM Experiments*



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  • Journal Title:
    Monthly Weather Review
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    This paper uses a fully coupled general circulation model (CGCM) to study the leading averaged coupled covariance (LACC) method in a strongly coupled data assimilation (SCDA) system. The previous study in a simple coupled climate model has shown that, by calculating the coupled covariance using the leading averaged atmospheric states, the LACC method enhances the signal-to-noise ratio and improves the analysis quality of the slow model component compared to both the traditional weakly coupled data assimilation without cross-component adjustments (WCDA) and the regular SCDA using the simultaneous coupled covariance (SimCC). Here in Part II, the LACC method is tested with a CGCM in a perfect-model framework. By adding the observational adjustments from the low-level atmosphere temperature to the sea surface temperature (SST), the SCDA using LACC significantly reduces the SST error compared to WCDA over the globe; it also improves from the SCDA using SimCC, which performs better than the WCDA only in the deep tropics. The improvement in SST analysis is a result of the enhanced signal-to-noise ratio in the LACC method, especially in the extratropical regions. The improved SST analysis also benefits the subsurface ocean temperature and low-level atmosphere temperature analyses through dynamic and statistical processes.
  • Keywords:
  • Source:
    Monthly Weather Review, 143(11), 4645-4659
  • DOI:
  • ISSN:
    0027-0644 ; 1520-0493
  • Format:
    PDF
  • Publisher:
    American Meteorological Society
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Library
  • Main Document Checksum:
    urn:sha-512:8e0ebb099f5508f423f299ae80587744492e679814a805ec94c5543f43c30cc4dc1f661178db020b07fd6f944ec8d7fb925d5908c3415d566f5e83031d645eaa
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  • File Type:
    Filetype[PDF - 2.67 MB ]
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