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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-705
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
22 Dec 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).
Using satellite observations of precipitation and soil moisture to constrain the water budget of a land surface model
Ewan Pinnington1,2, Tristan Quaife1,2, and Emily Black1,3 1Department of Meteorology, University of Reading, Reading, UK
2National Centre for Earth Observation, University of Reading, Reading, UK
3National Centre for Atmospheric Science, University of Reading, Reading, UK
Abstract. Early warning of agricultural drought can enable decision makers to act to improve food security. Land-surface models are useful tools to inform such monitoring systems, but model errors are problematic. We show that satellite-derived estimates of shallow soil moisture can be used to calibrate a land-surface model at the regional scale in Ghana, using data assimilation techniques. The modified calibration significantly improves model estimation of soil moisture. Specifically, we find a 44 % reduction in root-mean-squared error for a 5-year hindcast after assimilating a single year of soil moisture observations to update model parameters. The use of an improved remotely-sensed rainfall dataset contributes to 10 % of this reduction in error. Improved rainfall data has the greatest impact on model estimates during the seasonal wetting-up of soil, with the assimilation of remotely sensed soil moisture having greatest impact during drying down. The significant reduction in root-mean-squared error we find after assimilating a single year of observations bodes well for the production of improved soil moisture forecasts over sub-Saharan Africa where subsistence farming remains prevalent.

Citation: Pinnington, E., Quaife, T., and Black, E.: Using satellite observations of precipitation and soil moisture to constrain the water budget of a land surface model, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-705, in review, 2017.
Ewan Pinnington et al.
Ewan Pinnington et al.
Ewan Pinnington et al.

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Short summary
This paper combines satellite observations of precipitation and soil moisture to understand what key information they offer to improving land surface model estimates of soil moisture over Ghana. When both observations are combined with the chosen land surface model we reduce the error in a 5-year model hindcast by 44 %, this bodes well for the production of improved soil moisture forecasts over subsaharan Africa where subsistence farming remains prevalent.
This paper combines satellite observations of precipitation and soil moisture to understand what...
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