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

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Pinnington, E., Quaife, T. orcid id iconORCID: https://orcid.org/0000-0001-6896-4613 and Black, E. orcid id iconORCID: https://orcid.org/0000-0003-1344-6186 (2018) Impact of remotely sensed soil moisture and precipitation on soil moisture prediction in a data assimilation system with the JULES land surface model. Hydrology and Earth System Sciences, 22 (4). pp. 2575-2588. ISSN 1027-5606 doi: 10.5194/hess-22-2575-2018

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/76710
Identification Number/DOI 10.5194/hess-22-2575-2018
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher Copernicus
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Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.
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Available under license: Creative Commons Attribution
[thumbnail of hess-2017-705-manuscript-version3 (1).pdf]
Text - Accepted Version
· Restricted to Repository staff only
Restricted to Repository staff only
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Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

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