 Arctic ice is melting because of rising global temperatures, but scientists have not been able to forecast how fast it is happening. Physicist Ivan Sudikov from the University of Dayton and his colleagues have developed a mathematical model to better predict how Arctic sea ice melts. It can be used to develop more accurate climate models, which in turn helps us make more informed decisions about mitigating climate change. White Arctic sea ice reflects most of the sunlight it receives. Small ponds of meltwater form on sea ice due to various factors such as the topography of the ice, the distribution of snowfall, and rising global temperatures. These ponds, which appear as dark spots on the ice, absorb more sunlight, accelerating the growth of these ponds. Sudikov's model takes into account the horizontal heat transfer from one pond to the next, as well as the topography of the ice to predict the growth of these ponds. The model draws parallels between the 100-year-old icing model, which simulates the basic physics of ferromagnetic materials, and sea ice topography. This can help improve climate models by reducing the need for difficult and expensive data collection in the Arctic. The model is also based on simple mathematics that don't require powerful computers to crunch the numbers. Sudikov says that this model illustrates the universality of the laws of physics. He hopes to apply these ideas to better understand tundra lake growth and permafrost melt in the Arctic.