10 Minute pre cap of Mike Manns book, “The Hockey Stick and the Climate Wars”, now out in paperback with a new intro by Bill Nye – Science guy and Lord of the Dance.
The average author might have been delighted at the idea that reviews were already popping up for a book not yet published. But for Micheal Mann, the excoriating e-views haven’t been so welcome. Michael Mann is a leading climate scientist and a lightening rod for those who believe Climate Change is anything from a plot to a lie. From harassing phone calls to angry emails to death threats, he’s paying a price to pursue his science. Today we speak with Michael Mann on the chill over Climate Change.
Michael Mann is the director of the Earth Systems Science Center at Pennsylvania State University. His new book is The Hockey Stick and the Climate Wars: Dispatches from the Front Lines
Mike’s Congressional appearance below – the Hockey Stick Under Oath:
Finally, if you’ve stuck it out this long, or if you need yet more..ClimateGate dissected here – Unwinding “Hide the Decline”
A great book- shows the duplicity, subterfuge of the Fossil fuel interests in there mission to maintain their profits, their power- at the expense of future generations.
Nice compilation of Mann shows 🙂
Chris Mooney and Indre Viscontas have a new interview with Michael Mann on the ‘Inquiring Minds’ podcast this week as well.
http://climatedesk.org/2013/11/meet-the-computer-geek-who-took-on-ken-cuccinelli-and-won/
An excellent listen!
Just wanted to say once again that much of the supposed scientific case against Michael Mann’s hockey-stick is built on “Time Series Analysis 101” screwups. (I know that I’ve posted this before, but it’s still worth repeating.)
Details/background can be found in this wottsupwiththatblog discussion thread: http://wottsupwiththatblog.wordpress.com/2013/07/10/debunking-the-hockey-stick/#comments
Here’s a summary for those who don’t want to wade through the material at the above link:
The “hockey sticks from random noise” attack on Mann is based on the following:
Screwup #1): A 100:1 cherry-pick of noise results for “hockey-stick” shapes. In the Wegman Report, the final “cherry pick factor” was closer to 1000:1.
Screwup #2): The “random noise” used to generate the infamous noise hockey-sticks was contaminated with hockey-stick signal statistics. Tree-ring data was used as a “template” for the synthetic noise. But the perpetrators forgot that tree-ring data consists of *signal* (i.e. the long-term climate hockey-stick) as well as noise. To use tree-ring data properly as a “random noise template”, you first must filter out the “hockey-stick” signal. That was not done. As a result, the random noise model was completely invalid, as it was badly polluted with hockey-stick signal statistics.
Screwup #3): For a fully valid comparison, you must compare the *size* of the noise hockey-sticks with the *size* of Mann’s genuine tree-ring hockey-stick. As it turns out, the “random noise” hockey-sticks produced with cherry-picked hockey-stick-contaminated “random noise” were *much* smaller than Mann’s hockey stick. A quick look at the singular value outputs from the processing runs could have confirmed that.
Any one of the above screwups is enough to invalidate the whole “hockey-sticks from random noise” claim. All three together just completely bury it.
This highlights one of the major attractions of climate-denialism. In the climate-denial community, you can be a completely incompetent screwup and still enjoy “rock star” treatment. The professional scientific community offers no such perks.
Following up with one more tidbit.
In the Wegman Report, 12 “sample” random-noise hockey-sticks are shown. They were selected from the 10,000 original “random noise hockey-stick” trials (hence the near 1:1000 cherry-pick factor I mentioned above).
However, it should be pointed out that in any set of random noise trials, half of any “random noise” hockey-sticks will be pointing down, not up. (I’ve confirmed this with my own experimentation with SciLab scripts.)
So what are the odds that 12 “random noise” noise hockey-sticks selected at random will be pointing up as shown in the Wegman report? It’s 1/(2^12) = 1/4096 = 0.024 percent!
This is yet another illustration of the incompetence/dishonesty that Michael Mann has had to deal with all these years.
(Being pedantic with myself here) — ‘…it should be pointed out in any *sufficiently large* set of random noise trials, *approximately* half of the “random noise hockey-sticks” will be pointing down, not up.’
That seems potentially damning. Why isn’t that more widely known?
Is it like the page 7 retraction that a newspaper runs after the page 1 blunder?
I believe that it is quite widely known. For some reason, however, those who make a very big deal about the supposed issues with other peoples’ work are very reluctant to acknowledge issues with their own work.
On a more serious note, I suspect one reason is that serious scientists tend to simply ignore work that they think is questionable. Why spend too much time addressing work that is almost certainly wrong? Most who work in the area will know it’s wrong, so there’s not much point. Of course, if your primary goal is to show that someone else’s work is wrong then you’re going to make a big deal of it safe in the knowledge that if your own work is flawed others are likely to simply ignore it. A bit simplistic maybe, but an element of truth I suspect.
Couldn’t McIntire etc. have performed autocorrelation on their ‘random noise’ template (or for the last 50, 100 or 150 years at least) and compared it against white noise (or some standard template) on a correlelogram to catch a signal impregnation? I would imagine any temp series, whether it mimics randomness or not, is naturally going to show greater autocorrelation than white noise, but at some point where the r value of each lag is significantly different, especially at longer lags, then…
I just woke up – my mind is still fuzzy – so maybe my hypothesis is showing my ignorance of what’s happening here, but it just seems like any credible mathematician could easily tell whether or not there was a signal in their ‘random’ template or not.
Book’s now available in paperback too!