Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements

Jeanneret, Fanny; Martucci, Giovanni; Pinnock, Simon; Berne, Alexis

doi:https://doi.org/10.5194/amt-11-4153-2018

Articles | Volume 11, issue 7

https://doi.org/10.5194/amt-11-4153-2018

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

https://doi.org/10.5194/amt-11-4153-2018

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

Articles | Volume 11, issue 7

Research article

|

17 Jul 2018

Research article |

| 17 Jul 2018

Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements

Fanny Jeanneret, Giovanni Martucci, Simon Pinnock, and Alexis Berne

Download

Final revised paper (published on 17 Jul 2018)
Preprint (discussion started on 31 Jan 2018)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'article review', Anonymous Referee #1, 20 Mar 2018
- AC1: 'Response to comments by anonymous reviewer #1', Fanny Jeanneret, 25 May 2018
RC2: 'Comments on: Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements', Anonymous Referee #2, 16 Apr 2018
- AC2: 'Response to comments by anonymous reviewer #2', Fanny Jeanneret, 25 May 2018

Peer-review completion

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

AR by Fanny Jeanneret on behalf of the Authors (25 May 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (30 May 2018) by Mark Kulie

RR by Anonymous Referee #1 (28 Jun 2018)

ED: Publish as is (29 Jun 2018) by Mark Kulie

Short summary

Above mountainous regions, satellites may have difficulty in discriminating snow from clouds: this study proposes a new method that combines different ground-based measurements to assess the sky cloudiness with high temporal resolution. The method's output is used as input to a model capable of identifying false satellite cloud detections. Results show that 62 ± 13 % of these false detections can be identified by the model when applied to the AVHRR-PM and MODIS Aqua data sets of the Cloud_cci.