Articles | Volume 15, issue 12
Atmos. Meas. Tech., 15, 3875–3892, 2022
https://doi.org/10.5194/amt-15-3875-2022
Atmos. Meas. Tech., 15, 3875–3892, 2022
https://doi.org/10.5194/amt-15-3875-2022
Research article
01 Jul 2022
Research article | 01 Jul 2022

The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data

Edward Gryspeerdt et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-371', Anonymous Referee #1, 10 Jan 2022
    • AC1: 'Response to reviewers', Edward Gryspeerdt, 01 Mar 2022
  • RC2: 'Comment on amt-2021-371', Anonymous Referee #1, 11 Jan 2022
    • AC1: 'Response to reviewers', Edward Gryspeerdt, 01 Mar 2022
  • RC3: 'Comment on amt-2021-371', Anonymous Referee #2, 22 Jan 2022
    • AC1: 'Response to reviewers', Edward Gryspeerdt, 01 Mar 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Edward Gryspeerdt on behalf of the Authors (01 Mar 2022)  Author's response
ED: Referee Nomination & Report Request started (09 Mar 2022) by Hang Su
RR by Anonymous Referee #2 (24 Mar 2022)
RR by Anonymous Referee #1 (26 Mar 2022)
ED: Publish subject to technical corrections (06 Apr 2022) by Hang Su
AR by Edward Gryspeerdt on behalf of the Authors (15 Apr 2022)  Author's response    Manuscript
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Short summary
Droplet number concentration is a key property of clouds, influencing a variety of cloud processes. It is also used for estimating the cloud response to aerosols. The satellite retrieval depends on a number of assumptions – different sampling strategies are used to select cases where these assumptions are most likely to hold. Here we investigate the impact of these strategies on the agreement with in situ data, the droplet number climatology and estimates of the indirect radiative forcing.