Articles | Volume 24, issue 7
https://doi.org/10.5194/hess-24-3775-2020
https://doi.org/10.5194/hess-24-3775-2020
Research article
 | 
24 Jul 2020
Research article |  | 24 Jul 2020

The influence of assimilating leaf area index in a land surface model on global water fluxes and storages

Xinxuan Zhang, Viviana Maggioni, Azbina Rahman, Paul Houser, Yuan Xue, Timothy Sauer, Sujay Kumar, and David Mocko

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (08 Mar 2020) by Stacey Archfield
AR by Xinxuan Zhang on behalf of the Authors (16 Mar 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (26 Mar 2020) by Stacey Archfield
RR by Anonymous Referee #2 (20 Apr 2020)
RR by Anonymous Referee #1 (30 Apr 2020)
ED: Publish subject to minor revisions (review by editor) (26 May 2020) by Stacey Archfield
AR by Xinxuan Zhang on behalf of the Authors (27 May 2020)  Author's response   Manuscript 
ED: Publish as is (18 Jun 2020) by Stacey Archfield
AR by Xinxuan Zhang on behalf of the Authors (24 Jun 2020)  Manuscript 
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Short summary
This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.