Paper
22 October 2007 Construction of land data assimilation system based on EnKF technology and community land model
Qifeng Lu, Wei Gao, Zhiqiang Gao, Wanli Wu, Chaohua Dong, Zhongdong Yang, Peng Zhang, Bingyu Du, James Slusser
Author Affiliations +
Abstract
For the land products retrieved from the remotely sensed datasets better using in the land surface model and weather/climate model, 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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qifeng Lu, Wei Gao, Zhiqiang Gao, Wanli Wu, Chaohua Dong, Zhongdong Yang, Peng Zhang, Bingyu Du, and James Slusser "Construction of land data assimilation system based on EnKF technology and community land model", Proc. SPIE 6679, Remote Sensing and Modeling of Ecosystems for Sustainability IV, 667912 (22 October 2007); https://doi.org/10.1117/12.727868
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KEYWORDS
Data modeling

Soil science

Atmospheric modeling

Climatology

Systems modeling

Error analysis

Meteorological satellites

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