Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4473-2018
https://doi.org/10.5194/hess-22-4473-2018
Research article
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22 Aug 2018
Research article | Highlight paper |  | 22 Aug 2018

Estimating time-dependent vegetation biases in the SMAP soil moisture product

Simon Zwieback, Andreas Colliander, Michael H. Cosh, José Martínez-Fernández, Heather McNairn, Patrick J. Starks, Marc Thibeault, and Aaron Berg

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (01 May 2018) by Graham Jewitt
AR by Simon Zwieback on behalf of the Authors (16 May 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (18 May 2018) by Graham Jewitt
RR by Alexandra Konings (14 Jun 2018)
RR by Wade Crow (26 Jul 2018)
ED: Publish subject to technical corrections (02 Aug 2018) by Graham Jewitt
AR by Simon Zwieback on behalf of the Authors (02 Aug 2018)  Author's response    Manuscript
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Short summary
Satellite soil moisture products can provide critical information on incipient droughts and the interplay between vegetation and water availability. However, time-variant systematic errors in the soil moisture products may impede their usefulness. Using a novel statistical approach, we detect such errors (associated with changing vegetation) in the SMAP soil moisture product. The vegetation-associated biases impede drought detection and the quantification of vegetation–water interactions.