Contribution of personal weather stations to the observation  of deep-convection features near the ground

Mandement, Marc; Caumont, Olivier

doi:https://doi.org/10.5194/nhess-20-299-2020

Articles | Volume 20, issue 1

https://doi.org/10.5194/nhess-20-299-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-20-299-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 1

Research article

|

24 Jan 2020

Research article |

| 24 Jan 2020

Contribution of personal weather stations to the observation of deep-convection features near the ground

Marc Mandement and Olivier Caumont

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Final revised paper (published on 24 Jan 2020)
Preprint (discussion started on 17 Jul 2019)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review_nhess-2019-229', Anonymous Referee #1, 09 Aug 2019
- AC1: 'Author response to RC1: 'Review_nhess-2019-229'', Marc Mandement, 15 Nov 2019
RC2: 'Review', Anonymous Referee #2, 24 Aug 2019
- AC2: 'Author response to RC2: 'Review'', Marc Mandement, 15 Nov 2019

Peer-review completion

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

ED: Publish subject to minor revisions (review by editor) (01 Dec 2019) by Vassiliki Kotroni

AR by Marc Mandement on behalf of the Authors (02 Dec 2019) Author's response Manuscript

ED: Publish as is (12 Dec 2019) by Vassiliki Kotroni

AR by Marc Mandement on behalf of the Authors (13 Dec 2019)

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Short summary

The number of connected personal weather stations has dramatically increased in the last years. These weather stations produce a high number of data that need a thorough quality control to unleash their potential. A novel quality-control algorithm now allows us to take full advantage of these data and observe thunderstorms with fine-scale details that cannot be caught by standard networks. These results pave the way for tremendous advances in both understanding and forecasting thunderstorms.