Spatial horizontal correlation characteristics in the land data assimilation of soil moisture

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Title:Main Title: Spatial horizontal correlation characteristics in the land data assimilation of soil moisture
Description:Abstract: Remote sensing images deliver important information about soil moisture, but often cover only part of an area, for example due to the presence of clouds or vegetation. This paper examines the potential of incorporating the spatial horizontal correlation characteristics of surface soil moisture observations in land data assimilation in order to obtain improved estimates of soil moisture at uncovered grid cells (i.e. grid cells without observations). Observing system simulation experiments were carried out to assimilate the synthetic surface soil moisture observations into the Community Land Model for the Babaohe River Basin in northwestern China. The estimation of soil moisture at the uncovered grid cells was improved when information about surrounding observations and their spatial correlation structure was included. Including an increasing number of observations for covered and uncovered grid cells in the assimilation procedure led to a better prediction of soil moisture with an upper limit of five observations. A further increase of the number of observations did not further improve the results for this specific case. High observational coverage resulted in a better assimilation performance, depending also on the spatial distribution of observation data. In summary, the spatial horizontal correlation structure of soil moisture was found to be helpful for improving the surface soil moisture data characterization, especially for uncovered grid cells.
Identifier:10.5194/hess-16-1349-2012 (DOI)
Responsible Party
Creators:Xujun Han (Author), Xin Li (Author), Harrie-Jan Hendricks-Franssen (Author), Harry Vereecken (Author), Carsten Montzka (Author)
Publisher:European Geosciences Union
Publication Year:2013
Topic
TR32 Topic:Soil
Related Subproject:C6
Subjects:Keywords: Soil Moisture, Data Assimilation, Remote Sensing
File Details
Filename:2012_Han_HESS.pdf
Data Type:Text - Article
Size:15 Pages
File Size:2.2 MB
Dates:Accepted: 27.04.2012
Issued: 10.05.2012
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Only Project Members
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:[TR32DB] Data policy agreement
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Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Hydrology and Earth System Sciences
Source Website:www.hydrol-earth-syst-sci.net
Volume:16
Number of Pages:15 (1349 - 1363)
Metadata Details
Metadata Creator:Harrie-Jan Hendricks-Franssen
Metadata Created:03.12.2013
Metadata Last Updated:03.12.2013
Subproject:C6
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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