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Assimilation of sea surface temperature into CECOM by flux correction

机译：通过通量校正将海面温度吸收到CECOM中

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摘要

Sea surface temperature (SST) from a near realtime data set produced from satellites data has been assimilated into a coupled ice-ocean forecasting model (Canadian East Coast Ocean Model) using an efficient data assimilation method. The method is based on an optimal interpolation scheme by which SST is melded into the model through the adjustment of surface heat flux. The magnitude and space-time variation of the adjustment depend on the depth of heat diffusion into the water column in response to changes in surface flux, the correlation time scale of the data, and model and data errors. The diffusion depth is scaled by the eddy diffusivity for temperature. The ratio of the model and data errors is treated as an adjustable parameter. To evaluate the quality of the assimilation, the results from the model with and without assimilation are compared to independent ship data from the Atlantic Zone Monitoring Program and the World Ocean Circulation Experiment. It is shown that the assimilation has a significant impact on the modeled SST, reducing the root mean square difference (RMSD) between the model SST and the ship SST by 0.63℃ or 37%. The RMSD of the assimilated SST is smaller than that of the satellite SST by 0.23℃. This suggests that model simulations or predictions with data assimilation can provide the best estimate of the true SST. A sensitivity study is performed to examine the change of the model RMSD with the adjustable parameter in the assimilation equation. The results show that there is an optimal value of the parameter and the model SST is not very sensitive to the parameter.
机译：来自卫星数据的近实时数据集的海表温度（SST）已使用有效的数据同化方法同化为耦合的冰洋预报模型（加拿大东海岸海洋模型）。该方法基于最佳插值方案，通过调整表面热通量将SST融合到模型中。调整的幅度和时空变化取决于响应于表面通量变化的热扩散到水柱中的深度，数据的相关时间尺度以及模型和数据误差。扩散深度由温度的涡流扩散率决定。模型和数据误差的比率被视为可调参数。为了评估同化的质量，将有无同化模型的结果与来自大西洋区域监视计划和世界海洋环流实验的独立船舶数据进行比较。结果表明，同化对建模的SST有显着影响，使模型SST与船舶SST之间的均方根差（RMSD）降低了0.63℃或37％。同化SST的RMSD比卫星SST的RMSD小0.23℃。这表明带有数据同化的模型模拟或预测可以提供对真实SST的最佳估计。进行敏感性研究，以研究同化方程中具有可调参数的RMSD模型的变化。结果表明，该参数存在最优值，并且模型SST对参数不是很敏感。

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  • 来源
    《Ocean Dynamics》 |2010年第2期|p.403-412|共10页
  • 作者

    Yongsheng Wu; Charles Tang; Ewa Dunlap;

  • 作者单位

    Ocean Sciences Division, Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia B2Y 4A2, Canada;

    Ocean Sciences Division, Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia B2Y 4A2, Canada;

    Ocean Sciences Division, Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia B2Y 4A2, Canada;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    data assimilation; forecast model; sea surface temperature; heat flux correction; heat diffusion depth;

    机译：数据同化预测模型;海面温度热通量校正;散热深度;

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