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

Pinnington, Ewan; Quaife, Tristan; Black, Emily

doi:https://doi.org/10.5194/hess-22-2575-2018

Articles | Volume 22, issue 4

https://doi.org/10.5194/hess-22-2575-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-22-2575-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 4

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

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Final revised paper (published on 26 Apr 2018)
Preprint (discussion started on 22 Dec 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Minor revisions', Anonymous Referee #1, 30 Dec 2017
- AC1: 'Response to Reviewer 1', Ewan Pinnington, 28 Mar 2018
SC1: 'ESA CCI soil moisture has the same cumulative distribution function as GLDAS-NOAH model', Imtiaz Dharssi, 03 Jan 2018
- AC2: 'Response to Short Comment 1', Ewan Pinnington, 28 Mar 2018
RC2: 'Review of Pinnington et al. 2018', Georgy Ayzel, 12 Jan 2018
- AC3: 'Response to Reviewer 2', Ewan Pinnington, 28 Mar 2018
RC3: 'Review of the paper: Using satellite observations of precipitation and soil moisture to constrain the water budget of a land surface model by Ewan Pinnington et al.', Christian Massari, 30 Jan 2018
- AC4: 'Response to Reviewer 3', Ewan Pinnington, 28 Mar 2018
RC4: 'review', Wouter Dorigo, 04 Feb 2018
- AC5: 'Response to Reviewer 4', Ewan Pinnington, 28 Mar 2018

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

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.