by C. Rotter, Jan 26, 2021 in WUWT
A new team tries a new approach to Climate Modeling using AI and machine learning. Time will tell if a positive effort or extremely complicated exercise in curve fitting. Their goal is regional scale predictive models useful for planning. Few admit publicly that these do not exist today despite thousands of “studies” using downscaled GCM’s.
“There are some things where there are very robust results and other things where those results are not so robust,” says Gavin Schmidt, who heads NASA’s respected climate modeling program at the Goddard Institute for Space Studies. But the variances push skeptics to dismiss the whole field.
“There’s enough stuff out there that people can sort of cherry-pick to support their preconceptions,” says Dr. Hausfather. “Climate skeptics … were arguing that climate models always predict too much warming.” After studying models done in the past 50 years, Dr. Hausfather says, “it turns out they did remarkably well.”
But climate modelers acknowledge accuracy must improve in order to plot a way through the climate crisis. Now, a team of climatologists, oceanographers, and computer scientists on the East and West U.S. coasts have launched a bold race to do just that.
They have gathered some of the brightest experts from around the world to start to build a new, modern climate model. They hope to corral the vast flow of data from sensors in space, on land, and in the ocean, and enlist “machine learning,” a kind of artificial intelligence, to bring their model alive and provide new insight into what many believe is the most pressing threat facing the planet.
Their goal is accurate climate predictions that can tell local policymakers, builders, and planners what changes to expect by when, with the kind of numerical likelihood that weather forecasters now use to describe, say, a 70% chance of rain.