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集合Kalman滤波以其简单有效的特点在陆面数据同化中广泛应用,通常作为预报模型的陆面过程模式往往要考虑模式次网格变异性和土壤冻融过程,若对此不加考虑而直接对土壤湿度进行同化可能会使得同化结果发生偏差.将双集合Kalman滤波应用于土壤湿度的同化,基于NCAR/CLM陆面过程模式建立了一个考虑次网格变异性和土壤冻融过程的土壤湿度同化方案:在同一个时间步内用状态滤波对模式网格内某片上液态水分含量进行优化,用参数滤波对该片上的固态水分含量和其他片上的液态/固态水分含量进行优化,由此考虑模式次网格变异性和土壤冻融过程的影响,从而实现对整个模式网格上土壤湿度的同化.初步的同化试验表明:其同化效果在有、无土壤冻融阶段都优于一般的不考虑次网格变异性和土壤冻融变化的同化方案;该同化方案不仅能够提高那些有直接观测信息的土壤层的土壤湿度模拟精度,还能在一定程度上改善那些没有任何观测信息的土壤层的模拟效果;另外,土壤湿度同化结果的改善还能在一定程度上提高陆面模式对于土壤温度的模拟精度.
The set Kalman filter is widely used in land surface data assimilation because of its simple and effective features. Usually the land surface process model as a forecasting model often takes into account the sub-grid variability of the model and the soil freezing and thawing process, if this is not taken into consideration directly The assimilation of soil moisture may be biased by assimilating soil moisture.The double set Kalman filter is applied to the assimilation of soil moisture and a soil moisture model is established based on the NCAR / CLM land-surface process model considering sub-grid variability and soil freezing and thawing processes Assimilation scheme: State filter is used to optimize the liquid moisture content of a slice of the model grid in the same time step, and the solid-state moisture content of the slice and the liquid / solid moisture content of other slices are optimized by parametric filtering, thus considering Mode sub-grid variability and soil freezing and thawing process, so as to achieve the assimilation of soil moisture on the entire model grid.The preliminary assimilation test shows that the assimilation effect is superior to the general one in the period of freezing and thawing with or without soil Assimilation programs that consider sub-grid variability and soil freeze-thaw changes; this assimilation program can not only improve those with direct observations Of the soil layer soil moisture simulation accuracy, but also to some extent, to improve those without any observation information of the soil layer simulation effect; In addition, the improvement of soil moisture assimilation results can also improve the land surface to some extent, the soil temperature Simulation accuracy.