Articles | Volume 20, issue 11
https://doi.org/10.5194/tc-20-6501-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-6501-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Nov 2026
Research article |
| 12 Nov 2026
| 12 Nov 2026
Multi-sensor satellite analysis reveals latitudinal and morphometric controls on ice phenology across 31 000 lakes on the Alaska North Slope
Alexander L. Nguyen
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
Cesar G. Lopez
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
Jennifer Melara-Valle
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
Eliza Ross
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
Alexander S. Bradley
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
Maggie R. Limbeck
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
Claire C. Masteller
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
Roger J. Michaelides
CORRESPONDING AUTHOR
Department of Earth, Environmental, and Planetary Sciences, Washington University in St. Louis, Saint Louis, MO, 63130, USA
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It is of great importance to engineers and geomorphologists to predict the rate of bed load in rivers. In this contribution, we used a large dataset of measured data and developed an artificial neural network (ANN), a machine learning algorithm, for bed load prediction. The ANN model predicted the bed load flux close to measured values and better than the ones obtained from four standard bed load models with varying degrees of complexity.
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Short summary
Arctic lakes undergo freezing and thawing, but the timing and duration of these events across large areas is not well known. Using a machine learning model applied to satellite imagery, we successfully identify lake ice conditions on over 30 000 lakes in Alaska with high accuracy. Our results indicate that latitude is an important control on lake ice conditions, with secondary effects from lake size and shape. These findings have implications for future greenhouse gas emissions in the Arctic.
Arctic lakes undergo freezing and thawing, but the timing and duration of these events across...
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