Soil moisture and soil properties estimation in the Community Land Model with synthetic brightness temperature observations

This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.

Feature
A download is not possibleDownload
Citation
Citation Options
Identification
Title:Main Title: Soil moisture and soil properties estimation in the Community Land Model with synthetic brightness temperature observations
Description:Abstract: The Community Land Model (CLM) includes a large variety of parameterizations, also for flow in the unsaturated zone and soil properties. Soil properties introduce uncertainties into land surface model predictions. In this paper, soil moisture and soil properties are updated for the coupled CLM and Community Microwave Emission Model (CMEM) by the Local Ensemble Transform Kalman Filter (LETKF) and the state augmentation method. Soil properties are estimated through the update of soil textural properties and soil organic matter density. These variables are used in CLM for predicting the soil moisture retention characteristic and the unsaturated hydraulic conductivity, and the soil texture is used in CMEM to calculate the soil dielectric constant. The following scenarios were evaluated for the joint state and parameter estimation with help of synthetic L-band brightness temperature data assimilation: (i) the impact of joint state and parameter estimation; (ii) updating of soil properties in CLM alone, CMEM alone or both CLM and CMEM; (iii) updating of soil properties without soil moisture update; (iv) the observation localization of LETKF. The results show that the characterization of soil properties through the update of textural properties and soil organic matter density can strongly improve with assimilation of brightness temperature data. The optimized soil properties also improve the characterization of soil moisture, soil temperature, actual evapotranspiration, sensible heat flux, and soil heat flux. The best results are obtained if the soil properties are updated only. The coupled CLM and CMEM model is helpful for the parameter estimation. If soil properties are biased, assimilation of soil moisture data with only state updates increases the root mean square error for evapotranspiration, sensible heat flux, and soil heat flux.
Identifier:10.1002/2013WR014586 (DOI)
Citation Advice:Han, X., Hendricks-Franssen, H., Montzka, C., Vereecken, H., 2014. Soil moisture and soil properties estimation in the Community Land Model with synthetic brightness temperature observations. Water Resources Research, 50 (7), 6081 - 6105. DOI: 10.1002/2013WR014586
Responsible Party
Creators:Xujun Han (Author), Harrie-Jan Hendricks-Franssen (Author), Carsten Montzka (Author), Harry Vereecken (Author)
Publisher:AGU Publications
Publication Year:2014
Topic
TR32 Topic:Soil
Related Subproject:C6
Subjects:Keywords: Soil Moisture, Surface Fluxes, Data Assimilation
File Details
Filename:Han_2014_WRR.pdf
Data Type:Text - Article
Size:25 Pages
File Size:4.9 MB
Dates:Accepted: 02.07.2014
Available: 23.07.2014
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:Only Project Members
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:[TR32DB] Data policy agreement
Geographic
Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Water Resources Research
Issue:7
Volume:50
Number of Pages:25 (6081 - 6105)
Metadata Details
Metadata Creator:Tanja Kramm
Metadata Created:11.09.2014
Metadata Last Updated:11.09.2014
Subproject:C6
Funding Phase:2
Metadata Language:English
Metadata Version:V50
Metadata Export
Metadata Schema:
Dataset Statistics
Page Visits:667
Metadata Downloads:0
Dataset Downloads:1
Dataset Activity
Feature
A download is not possibleDownload