Over the decades, supercomputer simulations of Earth’s climate have yielded unprecedented insights into how the interplay of atmosphere, ocean, and land shapes the planet’s response to rising levels of greenhouse gases. But as these climate models have grown in complexity, researchers have started to worry the simulations have a substantial climate footprint of their own.
Climate models divide the atmosphere into thousands of boxes and use the equations of fluid dynamics to calculate how mass and energy move between them. The individual calculations aren’t taxing. “Climate models are very sparse in computation,” says Sarat Sreepathi, a computational earth scientist at Oak Ridge National Laboratory.
In the grand scheme of global warming, those emissions are minimal, says Bryan Lawrence, a climate scientist at the U.K.’s National Centre for Atmospheric Science and study co-author—no more than what 200 average Americans emit in a year. Cryptocurrency mining, meanwhile, has emitted many millions of tons of CO. But that’s no excuse not to measure the emissions, Lawrence says. “It is small beer,” he says. “On the other hand, we may not need to do as much small beer.
Making hard choices about just how many climate model runs are needed could also limit emissions, Lawrence says. The last round of CMIP proposed 190 different modeling experiments for centers to run—not just to provide baseline climate projections, but also to study aspects of climate change from geoengineering to paleoclimate. Many centers scrambled to do as many runs as possible, he says. “Modeling centers feel like they have to do CMIP to be in the game.
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