Articles | Volume 22, issue 4
https://doi.org/10.5194/hess-22-2575-2018
https://doi.org/10.5194/hess-22-2575-2018
Research article
 | 
26 Apr 2018
Research article |  | 26 Apr 2018

Impact of remotely sensed soil moisture and precipitation on soil moisture prediction in a data assimilation system with the JULES land surface model

Ewan Pinnington, Tristan Quaife, and Emily Black

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish as is (29 Mar 2018) by Louise Slater
AR by Ewan Pinnington on behalf of the Authors (06 Apr 2018)  Author's response    Manuscript
Download
Short summary
This paper combines satellite observations of precipitation and soil moisture to understand what key information they offer to improve land surface model estimates of soil moisture over Ghana. When both observations are combined with the chosen land surface model we reduce the unbiased root-mean-squared error in a 5-year model hindcast by 27 %; this bodes well for the production of improved soil moisture estimates over sub-Saharan Africa where subsistence farming remains prevalent.