中文摘要：

采用了顺序同化方法，利用集合卡尔曼滤波（EnKF）耦合一个简单陆面过程模型，从而完成了改善地表水热通量估算精度的研究工作。在建立同化系统的过程中，对同化系统的模型误差进行了探讨和设定，并通过已建立的同化系统对EnKF中的集合大小设定进行了试验。利用山东禹城试验站提供的站点实测数据与MOD16产品数据，进行同化系统的驱动和通量结果的验证。结果表明，以EnKF方法的数据同化系统能较好地完成对地表水热通量的估算，通过与MODIS ET（MOD16A2）产品的对比试验，证明该方法具有一定的稳定性和适用性，能较准确地对地表水热通量进行估算。

英文摘要：

Nowadays, more attention has been focused on the estimation of the land surface turbulent fluxes （sensible and latent heat fluxes） with data assimilation method. In this study, a sequential data assimilation scheme is developed based on the concept of the Ensemble Kalman filter （EnKF）. It assimilates land surface temperature into a simple land surface model which based on the energy balance theory for the estimation of surface turbulent fluxes. Moreover, from the perspective of error estimation, the simple schemes for estimating model errors and ensemble size are discussed. After construction of the assimilation system, the several numerical experiments tested by Yucheng cropland site in the province of Shandong. Results show that the land surface turbulent fluxes can be retrieved with satisfactory accuracy by using our method（compared to MODIS ET products（MOD16A2）, the RMSE of ET results are dropped from 4.18 mm to 2.99 mm）, which indicate the availability of our method in the prediction of surface turbulent fluxes.