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

Viewed

Total article views: 4,844 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,361 1,384 99 4,844 90 104
  • HTML: 3,361
  • PDF: 1,384
  • XML: 99
  • Total: 4,844
  • BibTeX: 90
  • EndNote: 104
Views and downloads (calculated since 22 Dec 2017)
Cumulative views and downloads (calculated since 22 Dec 2017)

Viewed (geographical distribution)

Total article views: 4,844 (including HTML, PDF, and XML) Thereof 4,500 with geography defined and 344 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Dec 2024
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.