Articles | Volume 13, issue 9
https://doi.org/10.5194/tc-13-2421-2019
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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Cited articles

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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.