Articles | Volume 14, issue 8
https://doi.org/10.5194/tc-14-2567-2020
https://doi.org/10.5194/tc-14-2567-2020
Research article
 | 
12 Aug 2020
Research article |  | 12 Aug 2020

A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data

Marcel König and Natascha Oppelt

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (31 Mar 2020) by Stef Lhermitte
AR by Marcel König on behalf of the Authors (14 Apr 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (23 Apr 2020) by Stef Lhermitte
RR by Anonymous Referee #2 (09 May 2020)
RR by Anonymous Referee #1 (10 May 2020)
ED: Publish subject to minor revisions (review by editor) (27 May 2020) by Stef Lhermitte
AR by Marcel König on behalf of the Authors (28 May 2020)  Author's response   Manuscript 
ED: Publish as is (01 Jul 2020) by Stef Lhermitte
AR by Marcel König on behalf of the Authors (02 Jul 2020)  Manuscript 
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Short summary
We used data that we collected on RV Polarstern cruise PS106 in summer 2017 to develop a model for the derivation of melt pond depth on Arctic sea ice from reflectance measurements. We simulated reflectances of melt ponds of varying color and water depth and used the sun zenith angle and the slope of the log-scaled reflectance at 710 nm to derive pond depth. We validated the model on the in situ melt pond data and found it to derive pond depth very accurately.