SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

doi:https://doi.org/10.5194/essd-10-267-2018

Articles | Volume 10, issue 1

https://doi.org/10.5194/essd-10-267-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-10-267-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 10, issue 1

Peer-reviewed comment

|

08 Feb 2018

Peer-reviewed comment |

| 08 Feb 2018

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

Luca Ciabatta, Christian Massari, Luca Brocca, Alexander Gruber, Christoph Reimer, Sebastian Hahn, Christoph Paulik, Wouter Dorigo, Richard Kidd, and Wolfgang Wagner

Download

Final revised paper (published on 08 Feb 2018)
Preprint (discussion started on 21 Sep 2017)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review of Ciabatta et al.', Hylke Beck, 09 Oct 2017
- AC1: 'Reply to Interactive comment by H. Beck', Luca Ciabatta, 03 Nov 2017
RC2: 'Review of Ciabatta et al.', Anonymous Referee #2, 11 Oct 2017
- AC2: 'Reply to Interactive comment by Anonymous Referee #2', Luca Ciabatta, 03 Nov 2017

Short summary

In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.