Kenneth Golden, a mathematician at the University of Utah, was perusing images of Arctic sea ice when he noticed a pattern that seemed familiar. When seen from above, the melting sea ice looked like a field of white mottled with dark splotches where the ice had turned to liquid. To Golden it seemed awfully similar to the arrangement of atoms in a magnetic material. There’s no obvious reason for magnets to have a relationship with aerial photos of ice, but the thought stuck with him. More than a decade later, this intuition has finally solidified into a model that could be used to better predict the effects of climate change on sea ice.
Melt ponds are exactly what they sound like: pools of water that form on top of sea ice when the ice's top layer melts in the spring and summer. The ponds are important because they change the reflectivity of ice. Ice has a high albedo, meaning it reflects most of the sunlight that hits it. Water, however, has a low albedo and absorbs a large portion of sunlight as heat. This produces a feedback loop: As ice melts to form melt ponds, a higher percentage of the ice's surface absorbs sunlight as heat, which melts even more ice, producing more, larger melt ponds.
Knowing what percentage of the ice's surface is made of melt ponds is therefore critical to knowing the rate at which Arctic ice is melting, which contributes to the global climate. But because the Arctic is so big, and satellite imaging has limited resolution, measuring the overall area of melt ponds is a hard problem. This is where Golden comes in.
Golden started studying sea ice as a math major at Dartmouth College, even traveling to Antarctica his senior year. He focused his career on more theoretical math, but ten years after his first Antarctic expedition, he got a call from his undergraduate research advisor inviting him to join a large polar research project with the US Navy.
Read more at Wired
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