He and his colleagues decided to apply the same approach to climate models, writing programs to tweak dozens of parameters in the source code of a public climate model. They harnessed about half of a supercomputer at Lawrence Livermore for nearly three years, producing 100,000 years of simulations across a wide array of climate scenarios. But in the summer of 2012, Lucas realized even those results had fallen well short of predicting the loss of Arctic sea ice that actually occurred. So he and colleagues undertook another modeling experiment, focused on sea ice. By consulting with experts on what variables could be at play and changing those parameters, his team was able to simulate the disappearance of far more Arctic sea ice, coming much closer to reality. Three variables accounted for 95 percent of the change. Two of them specified the size of snow particles on sea ice, which affects how much sunlight is reflected away. The last one, known as the “thermal conductivity of snow,” essentially defines how fast heat can move through ice. Like the other two variables, it is normally treated as a constant in the dedicated ice model the team used. But in this case, the researchers toggled it within a range that reflected its real-world variability. Lucas stops short of saying they’ve pinpointed the missing puzzle pieces in sea ice models. But by allowing for a range of “plausible” variations, “we find that we can explain most, but not all, of the differences between observations and [sea ice model] simulations,” he said in an e-mail. The experiment also created a much finer tool for Cvijanovic to explore the question she’d long pondered: Why did ancient periods of rapid warming in the Northern Hemisphere, known as Dansgaard–Oeschger events, seem to coincide with dramatic precipitation shifts all the way down in the tropics? Toward the end of her PhD work at the University of Copenhagen, in 2011 and 2012, Cvijanovic was part of a modeling group that tried to make sense of these abrupt climatic changes evident in Greenland ice core samples. She had made some crude attempts to explore these connections by adding energy fluxes in simulations, which essentially cranked up sea ice loss in artificial ways. But her colleague’s work at Lawrence Livermore enabled her to model extreme ice loss in a more realistic manner, by tweaking parameters within what’s considered the possible level of variation in nature.
Climate simulation models are becoming more accurate thanks to the work of nuclear weapons modellers in the US . scientists at the mit Livermore National laboratory used a supercomputer to create 100,000 years of climate simulation featuring a range of scenarios . together with sea ice researcher Ivana Cvijanovic , the nuclear models were able to more accurately reflect the rates of sea ice loss , helping to provide evidence of the previously unknown link between polar retreats and droughts in California .