How Dr. Chelsea Ackroyd is Changing Snow Science
Predicting when mountain snow will melt is a massive headache for water managers, especially in the West. We’ve used airborne lidar (lasers) for years to measure snow depth , but new research led by Dr. Chelsea Ackroyd shows these same lasers can observe how fast the snow is going to melt by measuring its reflectivity.
The "Shadow" Problem
Usually, scientists use solar-powered cameras to map snow albedo (reflectivity). But in rugged spots like the Coast Mountains of British Columbia, deep shadows and clouds often leave those cameras "blind".
Because lidar is an active sensor, bringin its own light source, it can peek into those dark corners where traditional cameras fall short.
Small Grains, Big Melt
It all comes down to snow grain size. Fresh, fine-grained snow reflects sunlight and stays cool. As snow ages, the grains get bigger and start absorbing heat like a dark t-shirt on a summer day.
By analyzing the "intensity" of the laser returns, Ackroyd’s team was able to map these grain sizes across Place Glacier with incredible detail.
Why This Matters
Mapping snow on a mountain isn't easy. The team had to account for the steepness of the slopes to keep the data accurate, but once they did, their laser maps matched high-end imaging gear within a 2% error margin.
This is a game-changer for water security. We can now:
Predict runoff better: More accurate reflectivity data means better flood and water supply forecasts.
Look into the past: We can apply this method to old lidar archives to see how snowpacks have changed over the last decade.
Monitor anywhere: We no longer need perfect "sunny day" conditions to get high-quality snow data.
For the communities that rely on these mountain "water towers," Ackroyd’s research is a major step toward a more predictable water future.
Source: Ackroyd, C. et al. (2026). Remote Sensing of Environment.