Gap-free global annual soil moisture: 15&thinsp;km grids for 1991–2018

Guevara, Mario; Taufer, Michela; Vargas, Rodrigo

doi:https://doi.org/10.5194/essd-13-1711-2021

Articles | Volume 13, issue 4

https://doi.org/10.5194/essd-13-1711-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-13-1711-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 4

Data description paper

|

27 Apr 2021

Data description paper |

| 27 Apr 2021

Gap-free global annual soil moisture: 15 km grids for 1991–2018

Mario Guevara, Michela Taufer, and Rodrigo Vargas

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Final revised paper (published on 27 Apr 2021)
Preprint (discussion started on 22 Sep 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of essd-2020-264', Anonymous Referee #1, 20 Oct 2020
- AC1: 'Responses to Anonymous Referee #1', Rodrigo Vargas, 22 Dec 2020
RC2: 'Gap-Free Global Annual Soil Moisture: 15 km Grids for 1991–2018', Anonymous Referee #2, 27 Nov 2020
- AC2: 'Responses to Anonymous Referee #2', Rodrigo Vargas, 22 Dec 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Rodrigo Vargas on behalf of the Authors (19 Jan 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (26 Jan 2021) by David Carlson

ED: Publish as is (05 Mar 2021) by David Carlson

AR by Rodrigo Vargas on behalf of the Authors (12 Mar 2021) Author's response Manuscript

Short summary

Soil moisture is key for understanding soil–plant–atmosphere interactions. We provide a machine learning approach to increase the spatial resolution of satellite-derived soil moisture information. The outcome is a dataset of gap-free global mean annual soil moisture predictions and associated uncertainty for 28 years (1991–2018) across 15 km grids. This dataset has higher agreement with in situ soil moisture and precipitation measurements. Results show a decline of global annual soil moisture.