For the land products retrieved from the remotely sensed datasets better using in the land surface model and weather/climate model, the details on how to develop the Land Data Assimilation Systems (LDAS) based on EnKF, 3DVAR technology and Community Land Model, has been discussed in this study. The constructed LDAS can provide optimal estimates of land surface state initial conditions by integrating with an ensemble of land surface models, the available atmospheric forcing data, remotely sensed observations of precipitation, radiation and some land surface parameters such as land cover and leaf area index. The verification results from soil temperature and moisture assimilation at Yucheng comprehensive experiment site and from 19-year LAI assimilation indicate that the constructed LDAS takes its effect and shows agreement with some past researches. There are still many detailed work to do for the routine operation of LDAS, such as how to get dynamic P in 3dvar, how to select the spacing interpolation algorithm, etc.
['Qifeng Lu', 'Zhongdong Yang', 'Hu Yang', 'Zhaojun Zhen', 'Yan-Meng Bi', 'Xuebao Wu', 'Guicai Li']
Developing Land Data Assimilation System based on EnKF, 3DVAR technology and Community Land Model