The Cryosphere
The Cryosphere
TC
Articles | Volume 18, issue 9
Articles | Volume 18, issue 9
https://doi.org/10.5194/tc-18-3933-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-3933-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 9
Research article
 | 
04 Sep 2024
Research article |  | 04 Sep 2024

AWI-ICENet1: a convolutional neural network retracker for ice altimetry

Veit Helm, Alireza Dehghanpour, Ronny Hänsch, Erik Loebel, Martin Horwath, and Angelika Humbert

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Latest update: 14 Nov 2024
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Short summary
We present a new approach (AWI-ICENet1), based on a deep convolutional neural network, for analysing satellite radar altimeter measurements to accurately determine the surface height of ice sheets. Surface height estimates obtained with AWI-ICENet1 (along with related products, such as ice sheet height change and volume change) show improved and unbiased results compared to other products. This is important for the long-term monitoring of ice sheet mass loss and its impact on sea level rise.
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