Rather than extrapolating from storms that occurred when times were cooler, they’re deploying vast computing power to create “synthetic” storms that—so the modelers hope—will better reflect the realities of an era that’s getting hot.
The synthetic-storm methodology that Sobel’s team uses was pioneered by Kerry Emanuel, a hurricane expert at MIT. The Columbia crew’s secret sauce is the model it has written, which incorporates particular assumptions about the physics of how climate change will affect hurricanes. Rather than employing Swiss Re’s current standard, a top-down approach that starts with the paths of past hurricanes and, as Sobel puts it, uses historical data to “just jiggle it a little bit,” the Columbia modelers use a bottom-up method, starting with data on weather-related factors they think are both relevant to hurricanes and likely to be influenced by global warming. Among those factors: “wind shear,” which is the variation in wind speed and direction at different altitudes; sea-surface temperature; and the amount of moisture in the air. Using that data, their algorithm calculates when a hurricane will form, how it will move, and how intense it will be. Theoretically, this more-forward-looking approach could be more accurate.
Here is an example from eos.org
"Variables were taken from ECMWF operational forecasts and used for stress testing simulations for critical infrastructure in the city of Khulna in Bangladesh. In this example, Hurricane Matthew (29 September 2016, 18:00 Central European Summer Time) has been displaced from the Gulf of Mexico 163.5° eastward and 5° northward to just offshore of Bangladesh. Conditions for sea level pressure (colors), 10-meter zonal and meridional wind components (arrows), and precipitation (not shown) were replicated in a simulation of this new location to gauge the damage that such a storm might inflict on this region."
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