Articles | Volume 14, issue 12
Atmos. Meas. Tech., 14, 7749–7773, 2021
https://doi.org/10.5194/amt-14-7749-2021
Atmos. Meas. Tech., 14, 7749–7773, 2021
https://doi.org/10.5194/amt-14-7749-2021

Research article 09 Dec 2021

Research article | 09 Dec 2021

Improved cloud detection for the Aura Microwave Limb Sounder (MLS): training an artificial neural network on colocated MLS and Aqua MODIS data

Frank Werner 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-2021-146', Anonymous Referee #1, 18 Jun 2021
  • RC2: 'Comment on amt-2021-146', Carlos Jimenez, 13 Jul 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Frank Werner on behalf of the Authors (30 Sep 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (30 Sep 2021) by Patrick Eriksson
RR by Anonymous Referee #1 (08 Oct 2021)
RR by Carlos Jimenez (19 Oct 2021)
ED: Publish subject to minor revisions (review by editor) (21 Oct 2021) by Patrick Eriksson
AR by Frank Werner on behalf of the Authors (23 Oct 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (27 Oct 2021) by Patrick Eriksson
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Short summary
In this study we present an improved cloud detection scheme for the Microwave Limb Sounder, which is based on a feedforward artificial neural network. This new algorithm is shown not only to reliably detect high and mid-level convection containing even small amounts of cloud water but also to distinguish between high-reaching and mid-level to low convection.