OK folks, here’s a question – no peeking. In terms of the total number of hurricane-days (i.e. days at wind-speed gt 65 knots) west of 69W, where does 2005 rank in the league table including all years since 1851? Bonus points if you get the top five right regardless of order.
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Climate Audit 
24 Comments
I have no fear of a public display of ignorance, so here goes:
1995
2004
1950-ish
1933 (though they classified many as tropical storms, probably incorrectly)
2005
Now I’ll go and check!
#1. this doesn’t depend on classifications, since I’m calculating days directly from the track data. Each qualifying measurement counts as 1/4 day.
Ouch!
In order of increasing frequency: 1995, 2001, 2005, 1935, 1940
Part 1: I’ll go with the average rank, r* = (N+1)/2 = 78.5
Part 2:
floor(runif(5,min=1851,max=2006))Do I get extra credit for making all of my data and algorithms freely available on the web?
5 years with most “west” hurricane days, summed by 1/4 days:
1916 2005 1887 1886 1933
26.50 31.25 32.25 33.00 37.75
Surprised me as well. I guess what they mean is that 2005 is unprecedented in the last sevennnnn-ty years.
RE #6
It’s interesting to look at the plots for each of the seasons Steve lists:
1886
1887
1916
1933
2005
I think that even the most casual observer will note the lack of Eastern Atlantic activity in the records for 1886, 1887, 1916 and 1933. In 2005 the Eastern Atlantic came alive with recorded activity.
Occam’s choices:
1. Unknown tropical weather phenomena in the Eastern Atlantic that prevented storm formation in 1886, 1887, 1916 and 1933 but not in the 2005 era
2. Unknown tropical weather phenomena that enhanced Eastern Atlantic activity in the 2005 era but not in earlier eras.
2. Much better data (esp. satellite) in 2005
#6 Interesting!
FWIW: I got a different answer:
> Track = read.table("http://data.climateaudit.org/data/hurricane/unisys/Track.ATL.txt",header=TRUE,sep="\t")
> sort(tapply(rep(0.25,sum(idx)),Track$year[idx=-690>Track$long&Track$wind>75],sum),decreasing=T)
1933 2005 1886 1955 1916 1893 1887 1896 1926 1954 2004 1961 1906
...
#6 — “I guess what they mean is that 2005 is unprecedented in the last sevennnnn-ty years.”
Steve, that wouldn’t be — couldn’t be — a little cynical levity, would it? 🙂
Speaking with a more properly serious demeanor here, keeping in mind the gravity of the topic, I’m wondering if the desire for portentious conclusions isn’t blinding some members of the climatology field to the necessity of doing the very basic analyses we’re seeing done here that appear to portend climate deportentiation.
I have in mind also Margo’s very basic analysis of hurricane counts and Student t-test of the result in item 47 here, followed by her shock at the realization that people are publishing portentious conclusions without thinking to do simple tests of their assumptions.
In the spirit of data-averaging, the picture emerging from the background noise (i.e., from the panoply of portentious papers continually catastrophizing climate) seems to be that trendiness in some climatology circles appears to involve more conclusory pathways rather than mere systematic variations in seasonal patterns.
TAC – here’s how I did the calculation:
I used 65 knots, but with 75 knots and this method only 1886 and 1887 were reversed. I couldn’t get your script to work.
Every time I use R, I marvel at the ability to get results in so few lines (while others – ahem – are still trying to get research grants so that they get grad students to do the calculation.)
#9. Pat, I saw a website once which promised that you could make smileys out of images. Maybe one of the computer types can create a special Dr Evil smiley for portentous claims.
#7. David, that’s interesting to look through the 5 years in succession. I don’t think that Occam’s razor needs much more sharpening.
Steve,
You may want to edit your post to say “greater than or equal to 65 knots” since that is what your script is based on. Otherwise it’s not clear.
#10 SteveM, thanks for showing your code. It make it so much easier to identify what we did differently.
Incidentally, the discrepancy in our results was caused by your conditioning on .GE. while I used .GT. (see below).
Also, in #8 I cut and pasted the wrong result (corresponding to (wind .GT. 75), which I tried when (wind .GT. 65) did not reproduce your results — oops!.
FWIW, I do get your results when conditioning on (wind .GE. 65):
> Track = read.table("http://data.climateaudit.org/data/hurricane/unisys/Track.ATL.txt",header=TRUE,sep="\t")
> sort(tapply(rep(0.25,sum(idx)),Track$year[idx=Track$long=65],sum),decreasing=T)
1933 1886 1887 2005 1916 1955 1893 1998 1878 1906 1950 1944 2004
37.75 33.00 32.25 31.25 26.50 24.75 23.75 22.50 22.25 22.00 22.00 21.25 21.25
JohnA or SteveM: Is there a primer (FAQ?) on how to publish R code, equations, etc., on CA? I just noticed that my #14 did not display as expected (it seems that “greater-than” and “less-than” symbols are handled in peculiar ways by WordPress).
#9 Pat,
I appreciate alliteration, and jargon is grand, but can you tell me what it means? 😉
If you put your R code within
#17 Thanks.
Just testing…[delete if you want]
> Track sort(tapply(rep(0.25,sum(idx)),Track$year[idx = 65],sum),decreasing=T)
1933 1886 1887 2005 1916 1955 1893 1998 1878 1906 1950 1944 2004
37.75 33.00 32.25 31.25 26.50 24.75 23.75 22.50 22.25 22.00 22.00 21.25 21.25
#17 John, I think I followed the rules in #18, and it still did not render what I expected.
Can you send them to me via climateaudit AT gmail.com and I’ll see how to do it.
> Track sort(tapply(rep(0.25,sum(idx)),Track$year[idx< -Track$long=65],sum),decreasing=T)
1933 1886 1887 2005 1916 1955 1893 1998 1878 1906 1950 1944 2004
37.75 33.00 32.25 31.25 26.50 24.75 23.75 22.50 22.25 22.00 22.00 21.25 21.25
Ok. The above was done by putting tags around the code.
Klotzbach, Gray and Thorson just released their Hurricane forecast report for 2007, linked here
In section 7 of that report, they discuss some of the hurricane counting issues touched on here.
The link is http://hurricane.atmos.colostate.edu/Forecasts/2006/dec2006/