Articles | Volume 18, issue 2
https://doi.org/10.5194/tc-18-933-2024
https://doi.org/10.5194/tc-18-933-2024
Research article
 | 
29 Feb 2024
Research article |  | 29 Feb 2024

Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model

Hannah Niehaus, Larysa Istomina, Marcel Nicolaus, Ran Tao, Aleksey Malinka, Eleonora Zege, and Gunnar Spreen

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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-2023-2194', Anonymous Referee #1, 09 Nov 2023
    • AC1: 'Reply on RC1', Hannah Niehaus, 11 Dec 2023
  • RC2: 'Comment on egusphere-2023-2194', Anonymous Referee #2, 27 Nov 2023
    • AC2: 'Reply on RC2', Hannah Niehaus, 11 Dec 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to revisions (further review by editor and referees) (04 Jan 2024) by John Yackel
AR by Hannah Niehaus on behalf of the Authors (08 Jan 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (19 Jan 2024) by John Yackel
AR by Hannah Niehaus on behalf of the Authors (19 Jan 2024)
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Short summary
Melt ponds are puddles of meltwater which form on Arctic sea ice in the summer period. They are darker than the ice cover and lead to increased absorption of solar energy. Global climate models need information about the Earth's energy budget. Thus satellite observations are used to monitor the surface fractions of melt ponds, ocean, and sea ice in the entire Arctic. We present a new physically based algorithm that can separate these three surface types with uncertainty below 10 %.