Statistical Analysis of Glacier Change
As climate change continues to ravage the planet's ecosystem, being able to predict glacier loss while understanding its uncertainty has become a necessity. However, the standard practices to determine this uncertainty are not computationally feasible for large datasets. Our research focused on improving the accuracy of a method proposed by Rolstad et al (2009) that more efficiently approximates the uncertainty of glacier melting. We artificially created hundreds of glaciers of varying shapes, sizes, and terrains and assessed the accuracy of this approximation. We then devised a corrected approximation method that more accurately calculates the uncertainty while remaining efficient. Finally, we applied this corrected approximation method to glaciers in Iceland and Ecuador to explore real-world applicability.