09 October 2009

United States hurricane landfalls and damages: Can one-to five-year predictions beat climatology?

My paper on one to five year hurricane predictions is now out and you can find it here in PDF. Here is the abstract:
This paper asks whether one- to five-year predictions of United States hurricane landfalls and damages improve upon a baseline expectation derived from the climatological record. The paper argues that the large diversity of available predictions means that some predictions will improve upon climatology, but for decades if not longer it will be impossible to know whether these improvements were due to chance or actual skill. A review of efforts to predict hurricane landfalls and damage on timescales of one to five years does not lend much optimism to such efforts in any case. For decision makers, the recommendation is to use climatology as a baseline expectation and to clearly identify hedges away from this baseline, in order to clearly distinguish empirical from non-empirical justifications for judgments of risk.
Pielke, Jr., R.A., 2009. United States hurricane landfalls and damages: Can one-to five-year predictions beat climatology?, Environmental Hazards, Vol. 8, pp. 187-200.


The Iconic Midwesterner said...

Who says academics don't have a sense of humor? Were I British I might want to call this paper "cheeky." (I may anyway.)

For starters, I don't believe for a minute you are really agnostic on the question of differences in land falling hurricane rates being a matter of limitations in the data-set vs. the result of an unidentified (or unidentifiable) natural mechanism. That being said, I find the logic of your "resolution" of the issue to be inescapable. Even if we accept the data as being unproblematic, that would still mean positing a theory which should have no practical effect upon forecasting hurricane landfalls and damage, the North Atlantic remaining stubbornly free of things to destory.

As for your larger point concerning forecasts and how policy makers should view them, I think it is well made.

I do have one caveat. I'll make an analogy here to garden variety weather forecasts, specifically temperature forecasts. As is well known forecasts do a pretty good job in giving a view of the next 24-48 hours, while after about 72 hours their usefulness degrades quickly. Now, when you look at the post-72 hour temperature forecasts you can almost see the models they use fleeing to the protection of the seasonal averages. Now, were I a model maker I would also do exactly that, but the idea that in doing so I am giving a forecast related to the specifics of the atmospheric condition actually present, well, would be false. In that sense, it's not really a "forecast" at all.

However, that shouldn't blind us to the fact that the 24-48 hour forecasts are qualitatively better and do accurately tell us things that lie outside seasonal averages.

What would that mean in this context? Well, maybe 5 year forecasts will be limited to running to the safety of average landfall rates, but there is hope that a shorter seasonal forecast might also prove to be better. It is conceivable that atmospheric conditions could be identified that would allow us to accurately forecast storm incidence in the Atlantic basin.

That being said (and here I'm caveating my caveat), I do not see any reason to beleive we can identify atmospheric conditions which would influence the entire span of the hurricane season. (How did the "seasonal forecast" become the yard stick anyway?) For example, a monthly forecast released in the last week of the previous month, would be ambitious enough undertaking. And, we would accumulate enough data quickly to make fairer evaluations of the forecasts so we could lessen (if not all the way eliminate) the fallacious tendencies you identified.

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