Thursday, January 04, 2007
Comparing hurricane return levels using historical and geological records
Hurricane return levels estimated using historical and geological information are quantitatively compared for Lake Shelby, Alabama. The minimum return level of overwash events recorded in sediment cores is estimated using a modern analogue (Hurricane Ivan of 2004) to be 54 m/s (105 kt) for a return period of 318 years based on 11 events over 3500 years. The expected return level of rare hurricanes in the observed records (1851-2005) at this location and for this return period is estimated using a parametric statistical model and a maximum likelihood procedure to be 73 m/s (141 kt) with a lower bound on the 95% confidence interval of 64 m/s (124 kt). Results are not significantly different if data are taken from the shorter 1880-2005 period. Thus the estimated sensitivity of Lake Shelby to overwash events is consistent with the historical record given the model. In fact, assuming the past is similar to the present the sensitivity of the site to overwash events as estimated from the model is likely more accurately set at 64 m/s. Read more.
I was commenting on Holland and Webster at my blog, made what I thought was a joke that maybe I had "discovered' a 200-300 periods oscillation in hurricanes.
ReplyDeleteStill, it was a coincidence to come here and read the time period you found.
Anon,
ReplyDeleteBe careful. A return period is the expected (or average) time between events. It does not imply an oscillation or a preferred time period. In fact the use of return periods for describing rare events is strictly valid only for a random set of events over time. I hope this helps.
Jim
Jim
ReplyDeleteThanks. True. I wasn't thinking in as Poisson processes.
As it happens, I also don't think the snippet buried in my dicussion of Holland in any way "means" there is a 200-300 year oscillation. Only that if one were to use the "eyeball" method, and "think" of a sine wave, you could speculate that between 1/2 and 3/4 of a period has based. This would obviously be pure speculation.
Oh, shoot. As long as I'm here, I was going to ask, can you suggest a reference describing techniques to apply "student-t like" hypothesis tests to data that are Poisson distributed?
ReplyDeleteAnon,
ReplyDeleteIn the context of hurricane climate studies, it is perhaps best to consider the machinery of generalized linear models (glm). For example, when considering hurricane frequency, although the response is a count variable the covariates are continuous variables (e.g., ENSO as characterized by sea-surface temperature over the tropical eastern Pacific). The R project for statistical computing has excellent resources for doing this kind of analysis and modeling. Good luck.
Jim
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ReplyDelete