[700] - Joint Assimilation of Surface Temperature and L-band Microwave Brightness Temperature in Land Data Assimilation

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Han, X., Hendricks-Franssen, H., Li, X., Zhang, Y., Montzka, C., Vereecken, H., 2013. Joint Assimilation of Surface Temperature and L-band Microwave Brightness Temperature in Land Data Assimilation. Vadose Zone Journal, 12 (3), 1 - 16. DOI: 10.2136/vzj2012.0072.
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Title(s):Main Title: Joint Assimilation of Surface Temperature and L-band Microwave Brightness Temperature in Land Data Assimilation
Description(s):Abstract: Soil moisture and soil temperature are tightly coupled variables in land surface models. The objective of this study was to evaluate the impact of the joint assimilation of soil moisture and land surface temperature data in a land surface model on soil moisture and soil temperature characterization. Three synthetic tests evaluated the joint assimilation of surface temperature (measured by MODIS) and brightness temperature (from L-band) into the Community Land Model using the local ensemble transform Kalman filter (LETKF). The following three tests were performed for dry and wet conditions: (i) assimilating surface temperature observations only; (ii) assimilating brightness temperature observations only; and (iii) assimilating both surface temperature and brightness temperature observations. The results show that the joint assimilation of surface temperature and brightness temperature results in the best characterization of soil moisture and soil temperature profiles under dry conditions. The assimilation of surface temperature contributed to an improved characterization of soil moisture profiles under dry conditions. For the dry period, brightness temperature assimilation resulted in improved prediction of sensible and latent heat fluxes, whereas surface temperature assimilation improved only the prediction of latent heat flux. Under wet conditions, the joint assimilation scheme cannot outperform the single brightness temperature assimilation. Neither the estimation of soil moisture and soil temperature profiles nor the estimates of the turbulent fluxes were improved by joint assimilation (compared with assimilation of brightness temperature only) under wet conditions.
Identifier(s):DOI: 10.2136/vzj2012.0072
Responsible Party
Creator(s):Author: Xujun Han
Author: Harrie-Jan Hendricks-Franssen
Author: Xin Li
Author: Yanlin Zhang
Author: Carsten Montzka
Author: Harry Vereecken
Publisher:Soil Science Society of America
TR32 Topic:Remote Sensing
Subject(s):CRC/TR32 Keywords: LAI, Data Assimilation, Ensemble Kalman Filter, MODIS
File Details
File Name:2013_Han_VZJ.pdf
Data Type:Text
Size(s):16 Pages
File Size:6918 kB (6.756 MB)
Date(s):Issued: 2013-01-28
Mime Type:application/pdf
Data Format:PDF
Download Permission:OnlyTR32
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:TR32DB Data policy agreement
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Publication
Article Type:Journal
Source:Vadose Zone Journal
Number Of Pages:16
Page Range:1 - 16
Metadata Details
Metadata Creator:Harrie-Jan Hendricks-Franssen
Metadata Created:2013-12-03
Metadata Last Updated:2013-12-03
Funding Phase:2
Metadata Language:English
Metadata Version:V40
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Dataset Downloads:4
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