Articles | Volume 18, issue 8
https://doi.org/10.5194/tc-18-3471-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/tc-18-3471-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Aug 2024
Research article |
| 07 Aug 2024
| 07 Aug 2024
The AutoICE Challenge
Andreas Stokholm
CORRESPONDING AUTHOR
DTU Space, Department of Space Research and Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
ϕ-lab, European Space Research Institute (ESRIN), European Space Agency (ESA), Frascati, Italy
Jørgen Buus-Hinkler
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Tore Wulf
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Anton Korosov
Nansen Environmental and Remote Sensing Center (NERSC), Bergen, Norway
Roberto Saldo
DTU Space, Department of Space Research and Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
Leif Toudal Pedersen
DTU Space, Department of Space Research and Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
David Arthurs
Polar View, Herlev, Denmark
Ionut Dragan
SpaceTec Partners, Brussels, Belgium
Iacopo Modica
GMATICS, Rome, Italy
Juan Pedro
EarthPulse, Barcelona, Spain
Annekatrien Debien
SpaceTec Partners, Brussels, Belgium
Xinwei Chen
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Muhammed Patel
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Fernando Jose Pena Cantu
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Javier Noa Turnes
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Jinman Park
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Linlin Xu
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Katharine Andrea Scott
Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Canada
David Anthony Clausi
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Yuan Fang
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Mingzhe Jiang
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Saeid Taleghanidoozdoozan
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Neil Curtis Brubacher
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Armina Soleymani
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Zacharie Gousseau
Department of System Design Engineering, University of Waterloo, Waterloo, Canada
Michał Smaczny
Warsaw University of Technology, Warsaw, Poland
Patryk Kowalski
Warsaw University of Technology, Warsaw, Poland
Jacek Komorowski
Warsaw University of Technology, Warsaw, Poland
David Rijlaarsdam
Ubotica Technologies, Dublin, Ireland
Jan Nicolaas van Rijn
Leiden Institute of Advanced Computer Science, Leiden University, Leiden, the Netherlands
Jens Jakobsen
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Martin Samuel James Rogers
AI Lab, British Antarctic Survey, Cambridge, United Kingdom
Nick Hughes
Norwegian Ice Service, Norwegian Meteorological Institute, Oslo, Norway
Tom Zagon
Canadian Ice Service, Environment and Climate Change Canada, Ottawa, Canada
Rune Solberg
Norwegian Computing Center (NR), Oslo, Norway
Nicolas Longépé
ϕ-lab, European Space Research Institute (ESRIN), European Space Agency (ESA), Frascati, Italy
Matilde Brandt Kreiner
Danish Meteorological Institute (DMI), Copenhagen, Denmark
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A relationship between the Ku-band radar scattering horizon and snow depth is found using a radar scattering model. This relationship has implications for (1) the use of snow climatology in the conversion of satellite radar freeboard into sea ice thickness and (2) the impact of variability in measured snow depth on the derived ice thickness. For both 1 and 2, the impact of using a snow climatology versus the actual snow depth is relatively small.
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Short summary
The AutoICE challenge encouraged the development of deep learning models to map multiple aspects of sea ice – the amount of sea ice in an area and the age and ice floe size – using multiple sources of satellite and weather data across the Canadian and Greenlandic Arctic. Professionally drawn operational sea ice charts were used as a reference. A total of 179 students and sea ice and AI specialists participated and produced maps in broad agreement with the sea ice charts.
The AutoICE challenge encouraged the development of deep learning models to map multiple aspects...
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