@inproceedings{8f9b72d1a60e41ed8f7088ced064cf30,
title = "Construction of land data assimilation system based on EnKF technology and community land model",
abstract = "In order to better use the land products retrieved from the remotely sensed datasets in the land surface model and weather/climate model, the Land Data Assimilation Systems (LDAS) based on EnKF Technology and Community Land Model has been developed at NSMC/CMA. In the context of numerical weather prediction applications, 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 validation from Yucheng comprehensive experiment site indicates that the preliminary results obtained are still inspiring. 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.",
keywords = "Community land model, EnKF technology, Land data assimilation system",
author = "Qifeng Lu and Wei Gao and Zhiqiang Gao and Wanli Wu and Chaohua Dong and Zhongdong Yang and Peng Zhang and Bingyu Du and James Slusser",
year = "2007",
doi = "10.1117/12.727868",
language = "英语",
isbn = "9780819468277",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Remote Sensing and Modeling of Ecosystems for Sustainability IV",
note = "Remote Sensing and Modeling of Ecosystems for Sustainability IV ; Conference date: 28-08-2007 Through 29-08-2007",
}