As glaciers retreat under the pressure of rising global temperatures, new research suggests that detailed 3D elevation models could vastly improve our ability to predict their behavior and better prepare for climate-driven disasters.
Though glaciers cover only about 10% of Earth’s surface, their influence is global. They regulate sea levels, stabilize Earth’s climate, and serve as major sources of freshwater. Yet many glacier studies to date offer limited seasonal detail, especially in remote regions.
In a recent study published in GIScience & Remote Sensing, researchers from The Ohio State University unveiled a method to capture the subtle and seasonal shifts of glacial ice more accurately than ever before. Using daily high-resolution imagery from the PlanetScope satellite constellation, they tracked the vertical and horizontal movement of three glaciers: La Perouse Glacier in Alaska, Viedma Glacier in Argentina, and Skamri Glacier in Pakistan.
Their goal was to separate seasonal melt from long-term climate trends, and the results were striking.
3D Models Capture Differences in Glacier Behavior
Between 2019 and 2023, two glaciers La Perouse and Viedma underwent consistent thinning, showing evidence of long-term retreat. However, Skamri Glacier in Central Asia actually showed a slight net gain in ice, suggesting local climatic stability.
The 3D models also revealed that glaciers respond to climate changes in distinct ways. While the La Perouse Glacier responded almost immediately to changes in precipitation speeding up or slowing down within days both Viedma and Skamri glaciers exhibited a delayed response of about 45 days. This delay, or “lag time,” is critical in understanding how glaciers react to shifts in temperature, rainfall, or snowfall.
These glaciers are influenced by both local weather and global climate patterns. The 3D data gives insight into those relationships in ways that traditional 2D models simply can’t.
A New Standard in Remote Glacier Monitoring
Traditionally, glacier studies rely on sporadic snapshots due to challenges in accessing remote and hazardous locations. The study’s satellite-based monitoring offers a scalable alternative, capable of capturing seasonal dynamics with high temporal resolution.
This method allowed researchers to track not only surface height changes but also internal ice flow and movement patterns all of which are essential for long-term climate modeling and hazard forecasting.
Real-World Impact: From Climate Science to Disaster Prevention
Accurate predictions of glacier melt are crucial for managing water supplies, agriculture, and disaster preparedness. Rapid melting can lead to glacial lake outburst floods (GLOFs), landslides, and water shortages. With high-resolution data, scientists may be able to issue earlier warnings and develop better mitigation strategies.
The study also underscores how local glacier behavior is shaped by complex interactions, not just one dominant climate factor. This understanding will be key as researchers examine other glaciers or ice sheets such as those in Greenland, Antarctica, or the Himalayas in future projects.
Building a Future for Data-Driven Environmental Research
Ohio State co-author Shengxi Gui and Qin hope this project will inspire other scientists to harness satellite data to study not only glaciers but also forests, wetlands, and other ecosystems threatened by climate change.
With climate impacts accelerating worldwide, 3D models like these may become indispensable in bridging science and action, offering a clearer picture of a planet in flux and helping communities adapt before it’s too late.