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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationRemote Sensing and Modeling of Ecosystems for Sustainability IV
DOIs
StatePublished - 2007
Externally publishedYes
EventRemote Sensing and Modeling of Ecosystems for Sustainability IV - San Diego, CA, United States
Duration: 28 Aug 200729 Aug 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6679
ISSN (Print)0277-786X

Conference

ConferenceRemote Sensing and Modeling of Ecosystems for Sustainability IV
Country/TerritoryUnited States
CitySan Diego, CA
Period28/08/0729/08/07

Keywords

  • Community land model
  • EnKF technology
  • Land data assimilation system

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