Articles | Volume 13, issue 1
Earth Syst. Sci. Data, 13, 1–31, 2021
https://doi.org/10.5194/essd-13-1-2021
Earth Syst. Sci. Data, 13, 1–31, 2021
https://doi.org/10.5194/essd-13-1-2021

Data description paper 05 Jan 2021

Data description paper | 05 Jan 2021

An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003–2018

Yongzhe Chen et al.

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Interactive discussion

Status: closed
Status: closed
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
AR by Yongzhe Chen on behalf of the Authors (10 Sep 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (22 Sep 2020) by Giulio G.R. Iovine
RR by Anonymous Referee #4 (07 Oct 2020)
RR by Anonymous Referee #1 (11 Oct 2020)
ED: Reconsider after major revisions (16 Oct 2020) by Giulio G.R. Iovine
AR by Yongzhe Chen on behalf of the Authors (13 Nov 2020)  Author's response
ED: Publish as is (18 Nov 2020) by Giulio G.R. Iovine
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Short summary
Soil moisture can greatly influence the ecosystem but is hard to monitor at the global scale. By calibrating and combining 11 different products derived from satellite observation, we developed a new global surface soil moisture dataset spanning from 2003 to 2018 with high accuracy. Using this new dataset, not only can the global long-term trends be derived, but also the seasonal variation and spatial distribution of surface soil moisture at different latitudes can be better studied.