Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Hydrol. Earth Syst. Sci., 21, 2483-2495, 2017
http://www.hydrol-earth-syst-sci.net/21/2483/2017/
doi:10.5194/hess-21-2483-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
11 May 2017
Advancing land surface model development with satellite-based Earth observations
Rene Orth et al.
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'review', Anonymous Referee #1, 20 Dec 2016 Printer-friendly Version Supplement 
 
RC2: 'hess-2016-628', Anonymous Referee #2, 15 Feb 2017 Printer-friendly Version 
 
RC3: 'Reviewer's comments to HESS-2016-628 article', Anonymous Referee #3, 28 Feb 2017 Printer-friendly Version 
 
AC1: 'Response to Reviewers', Rene Orth, 28 Mar 2017 Printer-friendly Version Supplement 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (further review by Editor) (07 Apr 2017) by Shraddhanand Shukla  
AR by Anna Wenzel on behalf of the Authors (07 Apr 2017)  Author's response
ED: Publish subject to minor revisions (further review by Editor) (13 Apr 2017) by Shraddhanand Shukla  
AR by Anna Wenzel on behalf of the Authors (13 Apr 2017)  Author's response
ED: Publish as is (13 Apr 2017) by Shraddhanand Shukla  
Publications Copernicus
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Short summary
State-of-the-art land surface models (LSMs) rely on poorly constrained parameters. To enhance LSM configuration, new satellite-based Earth observations are essential. This is because multiple observational datasets allow us to assess and validate the representation of coupled processes in LSMs. The resulting improved LSM configuration is beneficial for coupled weather forecasts, and hence valuable to society.
State-of-the-art land surface models (LSMs) rely on poorly constrained parameters. To enhance...
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