Articles | Volume 17, issue 19
https://doi.org/10.5194/amt-17-5957-2024
https://doi.org/10.5194/amt-17-5957-2024
Research article
 | 
11 Oct 2024
Research article |  | 11 Oct 2024

The Ice Cloud Imager: retrieval of frozen water column properties

Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson

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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 egusphere-2024-829', Anonymous Referee #1, 01 May 2024
    • AC1: 'Reply on RC1', Eleanor May, 17 Jul 2024
  • RC2: 'Comment on egusphere-2024-829', Anonymous Referee #2, 17 Jun 2024
    • AC2: 'Reply on RC2', Eleanor May, 17 Jul 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Eleanor May on behalf of the Authors (17 Jul 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (31 Jul 2024) by S. Joseph Munchak
AR by Eleanor May on behalf of the Authors (20 Aug 2024)
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Short summary
The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.