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Hmmm.....
Epsilon formed and persisted in fairly cold waters (around 24C), for a tropical cyclone. It may well be that shear has been more significant than temperatures in this extraordinary year. Roger Coppock wrote: Atlantic TS Epsilon Is About a 1 in 80,000 Year Event!!!!! Tropical storm Epsilon, number 29, is now active in the Atlantic: http://www.wxforecasts.com/ameriwx/a...age&hwvmetric= http://www.wxforecasts.com/ameriwx/a...ems&hwvmetric= If one controls for the increasing capability to observe tropical storms over the last 126 Atlantic hurricane seasons, this year's 29 Atlantic storms are about a 1 in 80,000 event! If one ignores the 4 storms per year per century growth in counted storms, this year's 29 storms is a 1 in 1,700,000 event. I won't use this, because it is misleading. I'll leave the lying and exaggeration to the Carbon industry lobbyists. They are the experts at that. Storms [1] 11 7 6 4 4 8 12 19 9 9 4 11 9 12 7 [16] 6 7 6 11 9 7 12 5 10 5 5 11 5 10 11 [31] 5 6 7 6 1 5 14 3 5 3 4 6 4 7 8 [46] 2 11 7 6 3 2 9 11 21 11 6 16 9 8 5 [61] 8 6 10 10 11 11 6 9 9 13 13 10 7 14 11 [76] 12 8 8 10 11 7 11 5 9 12 6 11 8 8 15 [91] 10 13 7 8 11 9 10 6 12 9 11 12 6 4 13 [106] 11 6 7 12 11 14 8 7 8 7 19 13 8 14 12 [121] 15 15 12 16 15 29 The data are from the NOAA web page given at this URL: http://www.aoml.noaa.gov/hrd/hurdat/...arandStorm.htm Currently, these data are preliminary and dated Friday, July 15, 2005 9:00PM. sort(Storms) [1] 1 2 2 3 3 3 4 4 4 4 4 4 5 5 5 [16] 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 [31] 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 [46] 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 [61] 9 9 9 9 9 9 9 9 9 9 9 10 10 10 10 [76] 10 10 10 10 11 11 11 11 11 11 11 11 11 11 11 [91] 11 11 11 11 11 11 11 12 12 12 12 12 12 12 12 [106] 12 12 13 13 13 13 13 14 14 14 14 15 15 15 15 [121] 16 16 19 19 21 29 Storms[126] [1] 29 mean(Storms) [1] 9.142857 sd(Storms) [1] 4.086493 fitted.model Call: lm(formula = Storms ~ Year, data = aframe) Coefficients: (Intercept) Year -70.80045 0.04115 residuals(fitted.model)[126] 126 17.28496 residuals(fitted.model)[126]/sd(Storms) 126 4.229779 pnorm(residuals(fitted.model)[126]/sd(Storms)) 126 0.9999883 # Yes, except for this year's extreme and a few others, # the residuals of the "Storms" data are normally # distributed. A normal quartile-quartile plot shows a # straight line, confirming this. 1/(1-pnorm(residuals(fitted.model)[126]/sd(Storms))) 126 85498.98 # Which rounds to 1 in 80,000. # NOTE: # to remove any bias due to increasing capability to observe # hurricanes, I have used the current value of the trendline # and not the mean as a baseline. Thus, the call to the # residual here. Had I used the mean as a base line the # result would have been 1 in 1,700,000. I'll leave the # lying and exaggeration to the fossil fools. pnorm((Storms[126]-mean(Storms))/sd(Storms)) [1] 0.9999994 1/(1-pnorm((Storms[126]-mean(Storms))/sd(Storms))) [1] 1697027 |
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