Articles | Volume 13, issue 9
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

Model code and software

Neural networks for snow depth on sea ice estimation A. Braakmann-Folgmann

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.