Sometimes the most fascinating little pieces show up buried deep in the comments section of a blog. Here’s a little snippet from Steve McIntyre’s, where he mentions in passing his experience in producing one of those holy consensus reports:
I was an IPCC 4AR reviewer and requested data from two then unpublished papers – Hegerl et al 2007 and D’Arrigo et al 2006, Rob is a coauthor of the latter. IPCC refused to provide it and referred me to the authors. The authors complained and IPCC told me that, if I requested data for any of other unpublished papers submitted to IPCC for use in AR4, I would be expelled as a reviewer.
(Scroll down to comment 76 if the link doesn’t take you there directly).
Just an FYI. The comment is number 76 in the blog comments.
Cheers
Steve’s website is excellent, maybe a tad heavy in the science, but he is putting paid to the idea of independent scientists, with pure hearts and open honesty pursuing science.
The reality is hidden data, refusals to share data, threats and abuse.
Steve is the guy who exposed the Hockey Stick Lie from IPCC TAR. When the 3rd report was filed the Hockey Stick was the center piece of the SPM, repeated over and over.
Now it is gone . . . some peer- review process eh ??
This is looking remarkably like the whole gun control “research” fiasco in medical journals. Refusal to provide raw data is common. If a guy won’t pony up his raw data to a reviewer on request, you’ve got to wonder.
Mr. McIntyre’s testimony that – the IPCC told me that, if I requested data for any of [the] other unpublished papers submitted to IPCC for use in AR4, I would be expelled as a reviewer – is a damning indictment of the IPCC.
it is fairly clear that the IPCC process is highly political….I know when I am being sold and I am being sold….
Steve McIntyre is doing amazing work for anyone who cares to look into the murky dealings of climate science.
I find it astounding that access to data, basic replicability of these studies and sufficient disclosure for genuine understanding of what they’re up to isn’t standard operating procedure.
I also find it astonishing that no one considers that mode of operation scandalous. They’re dealing with funding orders of magnitude larger than the sponsorship scandal and we don’t even get basic disclosure of their data and methods to support their studies. Absolutely unbelievable.
shouldn’t this reviewer have been asking for algore or davidsuzuki’s phone number instead of data sets, one of those fools could have told him all he needs to know
Kevin:
They are not interested in science; they are interested in fleecing money via carbon credits from unsuspecting nations with stupid electorates.
It is all about the money and who get to keep it.
Think of it as ADSCAM on steroids.
Although not my major, statistics was my minor, I have posted this link before … it is worth a watch.
http://ted.com/tedtalks/tedtalksplayer.cfm?key=p_donnelly
McKintrick has my complete support … models don’t mean sh*t if they are wrong … if feeding the latest 6/49 numbers get the same results in a model … the models are wrong.
Now that you mention it, Ural, I must say that I agree that TED Talks — ted.com/tedtalks – is indeed an interesting source of top quality dialectics and rhetoric. I agree that Peter Donnelly’s talk is excellent, even tough or perhaps partly because while I have a great appreciation for combinatorics, probability, and statistics, I wasn’t very academically good at them. On the other hand, I was top of the class in time-series analysis (there is some other evidence to suggest that I’m weird that way, I found differential equations hard, and partial differential equations easy, when almost everybody else finds the opposite to be true).
And now we find that at the heart of the climate modeling debates is the matter of time series analysis. Funny how that works. It is important, though, for those who are proposing action, even to the degree that their models are correct, that they not study only the first eleven chapters of “Time Series Analysis: Forecasting and Control”, by Box and Jenkins, 1976 (ISBN 0-8162-1104-3), but in particular, after the statistics are all said and done, chapter 12, “Design of Feedforward and Feedback Control Schemes”. It’s harder than it looks, especially when the fear-mongering ponzi-scheme protection-racket fraud-artists won’t even let you use the real data in your analysis and design. Bloody shysters.
I’ve only spent a few hours at the TED Talks site, and needless to say there are many thesis presented there that I do not agree with, yet one of the ones is I do find most interesting, not that I want to discuss it here because that would be off topic, but if you like, is the work of Dan Gilbert, who is a psychology professor at Harvard, and author of “Stumbling on Happiness”, and who has an excellent thesis on the relationship between the pre-frontal cortex and the human experience of happiness.
(PS: Last week you mentioned a visit next time you’re in these tinyurl.com/2zbfmx parts, Ural. Please do drop me a line to the vitruvius2 account at gmail when you’re next headed this way.)
Vitruvius,
Just like an engineer to bring a time series analysis to uncertainty principle fight.
That’s because, Ural, when we’re trying to reason about uncertainty, which as Mr. Donnely so eloquently explains is rather difficult for us, and as is shown in the case that is the topic of this thread, one of the tools we have available for our use in managing our uncertainty is time-series analysis, as it allows us to test the certainty of claimed causalities. The key notion is that cause and effect takes time: it is not instantaneous.
In the case of the current global warming fashion/craze/crime, we see Mr. Gore’s propaganda effort show temperature and carbon dioxide curves as vertically stacked separate graphs. And, indeed, to the casual observer, it looks like they go up and down together. But overlap the graphs on the same horizontal time axis, and it’s clear that carbon dioxide concentrations follow the rises and falls of temperature, they do not lead it. At this point the reasonable man must ask, how can A cause B, if A doesn’t happen, time-wise, until after B does? Is A having a post-hoc causative premonition, or is it just jumping on the B bandwagon, and in either case, given that the evidence is that A is not causing B, and assuming that B is a problem, which I doubt, would we want to base public policy and massive spending on controlling A, or B?
Some people are trying to redefine the temporal role of carbon dioxide concentrations. That reminds me of an old story. Apparently a mathematician, a scientist, and an engineer were each asked: Suppose we redefine a horse’s tail to be a leg. How many legs does a horse have? The mathematician answers “5”; the scientist “1”; and the engineer says “But you can’t do that!”
Vitruvius, nice exposure of the correlation=causation fallacy in Algore’s charts. He did the same thing in his support of gun control.
If I were a more charitable man I’d say he just doesn’t understand the difference between correlation and causation. But I’m not. Therefore given the man’s level of education I conclude he’s a lying sack of parrot droppings.