1. Turns out a Category 1 hurricane can, under the right circumstances, do a heck of a lot of damage. So can tropical storm force winds.
2. Up until this week, New York City and New Jersey could (and, for all I know, did) make the sort of arguments that would have kept insurance reserves available to pay for Sandy far too low. The argument would have been: no tropical cyclone has made landfall in New Jersey as a hurricane in 109 years, therefore the risk is low. Acceptance of those arguments can result in greater insurer insolvency and policyholder shortfalls. Turns out the theoretical flaws with that kind of argumentation, which we hear from some Texas coastal politicians all the time, can come back to bite you in the rear.
Footnote: Indeed, one might argue that it is STILL the case that no tropical cyclone has made landfall in New Jersey as a hurricane in 109 years since Hurricane Sandy may well have made landfall in New Jersey as a non-tropical cyclone with hurricane-force winds. But in the intervening time, tropical storms and hurricanes making landfall elsewhere or just going up the coast have caused plenty of damage.
3. Would someone care to reanalyze the costs and benefits of burying power lines in light of Sandy?
4. How much of the shore damage on the east coast was due to real or threatened government subsidized insurance or other regulatory interventions that stimulate development on the coast?
5. Every natural disaster creates its special brand of coverage dispute. Katrina and Ike developed the law of concurrent cause in wave v. wind disputes. Looks like “Hurricane” (or is it “Superstorm”) Sandy may result in major disputes over the meaning of a hurricane. The insurance industry has a lot riding on this due to heightened hurricane deductibles.
6. Are Irene and Sandy enough to persuade regulators and others that reliance on historical data alone is inferior to relying on models in an era of climate change? Could, after all, just be coincidence. Will our laws create a more comfortable environment for insurers to use models.
7. I would love to see a regression in which damage caused, live lost and proximity of the disaster epicenter to major media centers were the independent variables and ink spilled was the dependent variable. I predict the media-epicenter proximity variable will remain significant. In plain English, when 20 million people in Texas are hit by a major hurricane, it is not treated even 1/3 the same as when 60 million people in the New York/DC area are hit. #whine.
8. I would support a national micro data information superhighway that gave people information down at the micro level during emergencies. To some extent, private enterprise is doing this already, i.e. Google Maps or utility services that provide some information on power outages. But, often what is needed in times of disaster are things that reduce costly search for essentials in times, such as emergency, when search costs go up. When you don’t have gas, hunting for gas stations that do is very stressful. When you are away from home, knowing whether your particular house has power is very important. Maybe the existing internet or cell phone network is adequate for this purpose. After all, it is part of Internet lore that the system was designed to provide communications after a nuclear war. But maybe we need something yet more resilient. I can imagine radio-provided data that small-scale computers such as cell phones can interpret — kind of like audio QR-codes or Shazam, but for the purpose of distributing local data.