Articles | Volume 16, issue 14
https://doi.org/10.5194/amt-16-3531-2023
https://doi.org/10.5194/amt-16-3531-2023
Research article
 | 
25 Jul 2023
Research article |  | 25 Jul 2023

What CloudSat cannot see: liquid water content profiles inferred from MODIS and CALIOP observations

Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes

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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-2023-49', Anonymous Referee #1, 18 Apr 2023
    • AC1: 'Reply on RC1', Rick Schulte, 26 May 2023
  • RC2: 'Comment on amt-2023-49', Anonymous Referee #2, 29 Apr 2023
    • AC2: 'Reply on RC2', Rick Schulte, 26 May 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Rick Schulte on behalf of the Authors (26 May 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (07 Jun 2023) by Linlu Mei
RR by Anonymous Referee #1 (07 Jun 2023)
RR by Anonymous Referee #2 (13 Jun 2023)
ED: Publish as is (20 Jun 2023) by Linlu Mei
AR by Rick Schulte on behalf of the Authors (26 Jun 2023)  Author's response   Manuscript 
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Short summary
In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.