Global climate models are enormously complex mathematical endeavors. To keep them manageable, scientists chop the Earth into large grids to track impacts. Some models use grids the size of continents; others can be as small as 150 square kilometers.
Either way, however, the large-scale resolution means that many important regional and local impacts effectively disappear.
University of California, Berkeley, economist Michael Hanemann has attempted to refine the resolution to examine the economic impacts of climate change in far smaller chunks of property. As he downscales to a 12-square-kilometer grid to look at impacts within California, for instance, he finds that damages - and uncertainties - increase precipitously.
Take temperature increases. A model might show an average increase of 2ÂºC across an entire continent - a harmless enough jump. But that average might in reality reflect a slight 0.5Âº increase on the coasts and a more consequential 3Âº or 4Âº increase mid-continent - a far different beast entirely.
The same is true with time scales, Hanemann noted. A two-week heat snap can be devastating to both lives and livelihoods - for some crops even a few days of heat above 90ÂºF kills the season. But that kind of heat can get masked in a model using monthly averages.
"The more I've looked into the literature and talked to physical scientists, the more evident it is that most of the damage is done during extreme events," Hanemann said. But they are largely invisible to many economic models using broad spatial and temporal scales.
"Running (a climate model) on a daily time stamp is a massive computing problem, so it's understandable why they do what they do," he added.
"But this significantly understates things."
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