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Projection-Based Assimilation of Satellite-Derived Surface Data in an Indian Ocean Circulation Model

机译：印度洋环流模型中基于投影的卫星衍生地面数据同化

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Usefulness of satellite-derived surface data for nowcasting of oceanic circulation features has been explored in the study. Two types of surface data, namely the sea surface temperature (SST) and the sea level anomaly (SLA), have been used in various data assimilation experiments to ascertain their utility when assimilated in a sigma coordinate ocean circulation model configured for the Indian Ocean. Surface information has been projected into the vertical using predetermined correlation functions in combination with optimal interpolation. Evaluation of the assimilation skill has been carried out by comparing the assimilated results with independent observations. Combined assimilation of satellite-derived SST and SLA shows improved subsurface temperature at all depths, barring the thermocline region. As regards other variables such as the model simulated SLA and sea surface current, there is a regional dependence of assimilation. It could be, however, concluded that the combined assimilation is optimal in an overall sense.
机译：在这项研究中，探索了卫星衍生的表面数据对于海洋环流特征临近预报的有用性。在为印度洋配置的sigma坐标海洋环流模型中进行了各种数据同化实验后，已经使用了两种类型的表面数据，即海面温度（SST）和海平面异常（SLA），以确定其效用。使用预定的相关函数结合最佳插值，已将表面信息投影到垂直方向。通过将同化结果与独立观察结果进行比较，对同化技能进行了评估。卫星衍生的SST和SLA的组合同化显示，在所有深度都改善了地下温度，但不包括温跃层区域。至于其他变量，例如模型模拟的SLA和海流，则存在同化的区域依赖性。但是，可以得出这样的结论：从整体上讲，组合同化是最佳的。

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