Articles | Volume 20, issue 6
https://doi.org/10.5194/tc-20-3467-2026
https://doi.org/10.5194/tc-20-3467-2026
Research article
 | 
17 Jun 2026
Research article |  | 17 Jun 2026

Airborne lidar and machine learning reveal decreased snow depth in burned forests

Arielle Koshkin and Adrienne M. Marshall

Model code and software

Airborne Lidar and Machine Learning Reveal Decreased Snow Depth in Burned Forests Arielle Koshkin and Adrienne Marshall https://zenodo.org/records/14728778

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Short summary
Wildfires are burning higher in elevation and changing how snow accumulates and melts, disrupting the magnitude and timing of streamflow. Using machine learning and high resolution snow maps, we found that burned forests hold less snow compared to unburned forests, especially in spring, at higher elevations, and on south-facing slopes. These results show how fire reshapes mountain snowpacks, with important implications for water resources in a warming climate.
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