![](http://web.archive.org./web/20110108055929im_/http://www.gfdl.noaa.gov/pix/user_images/mb/pct_counts_2_thumb.gif)
Anthropogenic climate change will almost certainly increase the number of the most destructive hurricanes (see “Nature: Hurricanes ARE getting fiercer — and it’s going to get much worse” and NOAA here, the source of the figure).
Also, while this has not been modeled much, warming will put more water in the air above the ocean for hurricanes to sweep up and deluge down, as Kevin Trenberth, head of NCAR’s Climate Analysis Section, explains here.
A trickier question is how that will translate into an increase in landfilling hurricane and, even trickier, how much that will translate into increased damage, when you have to correct for non-climatic factors that would increase damage (population and GDP growth) and those that would decrease damage (better hurricane warning and building codes). Hurricanes are uniquely difficult to do this kind of analysis for because, as Judith Curry has pointed out, “It’s the strongest storms that matter most.”
“More than half the total hurricane damage in the U.S. (normalized for inflation and populations trends) was caused by just five events,” explained MIT hurricane expert Kerry Emanuel in an email to me a while back. Storms that are Category 4 and 5 at landfall (or just before) are what destroy major cities like New Orleans and Galveston with devastating winds, rains, and storm surges. One extra Cat 4 or 5 hitting Miami and you’ve obliterated the damage records.
So one thing you can safely say about a hurricane damage analysis study: Its conclusions should not be generalized into broader conclusions about the impact of climate change on extreme weather.
Into this mix comes a new study, “Emergence time scales for detection of anthropogenic climate change in US tropical cyclone loss data,” by Crompton, Pielke and McAneney (PDF here via the NYT/ClimateWire article). Yes, it’s that Pielke (see Foreign Policy’s “Guide to Climate Skeptics” includes Roger Pielke, Jr.), who just can’t avoid making an outrageous and baseless attack on the integrity of those whose real-world data happen to disagree with his widely-criticized modeling:
The study concludes, unjustifiably, as we’ll see:
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