Articles | Volume 13, issue 9
The Cryosphere, 13, 2421–2438, 2019
https://doi.org/10.5194/tc-13-2421-2019
The Cryosphere, 13, 2421–2438, 2019
https://doi.org/10.5194/tc-13-2421-2019

Research article 17 Sep 2019

Research article | 17 Sep 2019

Estimating snow depth on Arctic sea ice using satellite microwave radiometry and a neural network

Anne Braakmann-Folgmann and Craig Donlon

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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: Publish subject to minor revisions (review by editor) (06 Jul 2019) by Lars Kaleschke
AR by Anne Braakmann-Folgmann on behalf of the Authors (09 Jul 2019)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (24 Jul 2019) by Lars Kaleschke
AR by Anne Braakmann-Folgmann on behalf of the Authors (30 Jul 2019)  Author's response    Manuscript
ED: Publish as is (15 Aug 2019) by Lars Kaleschke
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Short summary
Snow on sea ice is a fundamental climate variable. We propose a novel approach to estimate snow depth on sea ice from satellite microwave radiometer measurements at several frequencies using neural networks (NNs). We evaluate our results with airborne snow depth measurements and compare them to three other established snow depth algorithms. We show that our NN results agree better with the airborne data than the other algorithms. This is also advantageous for sea ice thickness calculation.