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

doi:10.1117/12.727868

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

^*Corresponding author for this work

China Meteorological Administration
Colorado State University
Research for Sustainable Development in Arid and Semi-Arid Lands
CAS - Institute of Geographical Sciences and Natural Resources Research
National Center for Atmospheric Research
Nanjing University of Information Science & Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Remote Sensing and Modeling of Ecosystems for Sustainability IV
DOIs	https://doi.org/10.1117/12.727868
State	Published - 2007
Externally published	Yes
Event	Remote Sensing and Modeling of Ecosystems for Sustainability IV - San Diego, CA, United States Duration: 28 Aug 2007 → 29 Aug 2007

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	6679
ISSN (Print)	0277-786X

Conference

Conference	Remote Sensing and Modeling of Ecosystems for Sustainability IV
Country/Territory	United States
City	San Diego, CA
Period	28/08/07 → 29/08/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

Community land model
EnKF technology
Land data assimilation system

Access to Document

10.1117/12.727868

Cite this

Lu, Q., Gao, W., Gao, Z., Wu, W., Dong, C., Yang, Z., Zhang, P., Du, B., & Slusser, J. (2007). Construction of land data assimilation system based on EnKF technology and community land model. In Remote Sensing and Modeling of Ecosystems for Sustainability IV Article 667912 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6679). https://doi.org/10.1117/12.727868

@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",

}

Lu, Q, Gao, W, Gao, Z, Wu, W, Dong, C, Yang, Z, Zhang, P, Du, B & Slusser, J 2007, Construction of land data assimilation system based on EnKF technology and community land model. in Remote Sensing and Modeling of Ecosystems for Sustainability IV., 667912, Proceedings of SPIE - The International Society for Optical Engineering, vol. 6679, Remote Sensing and Modeling of Ecosystems for Sustainability IV, San Diego, CA, United States, 28/08/07. https://doi.org/10.1117/12.727868

Construction of land data assimilation system based on EnKF technology and community land model. / Lu, Qifeng; Gao, Wei; Gao, Zhiqiang et al.
Remote Sensing and Modeling of Ecosystems for Sustainability IV. 2007. 667912 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 6679).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Construction of land data assimilation system based on EnKF technology and community land model

AU - Lu, Qifeng

AU - Gao, Wei

AU - Gao, Zhiqiang

AU - Wu, Wanli

AU - Dong, Chaohua

AU - Yang, Zhongdong

AU - Zhang, Peng

AU - Du, Bingyu

AU - Slusser, James

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

KW - Community land model

KW - EnKF technology

KW - Land data assimilation system

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DO - 10.1117/12.727868

M3 - 会议稿件

AN - SCOPUS:42149136978

SN - 9780819468277

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Remote Sensing and Modeling of Ecosystems for Sustainability IV

T2 - Remote Sensing and Modeling of Ecosystems for Sustainability IV

Y2 - 28 August 2007 through 29 August 2007

ER -

Construction of land data assimilation system based on EnKF technology and community land model

Abstract

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UN SDGs

Keywords

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