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The missing hockey stick is found hiding in central England

Tamino has been looking at the CET - Central England Temperature record - and does some clever stuff picking out a few potential problems with the older records. (The direct link above to the blog post doesn't seem to be working so you may have to go Tamino's main blog page to find his article.) But he ignores the fact that this "longest single instrumental temperature record" has been buggered about with, especially since 1974. with station changes, adjustments and tweaking, all with the good intention of "improving" the record.

But no matter because he takes this: The monthly temperature anomalies - the difference between each month’s value, and the average for that month during a reference period (the entire time span ).


And by his sooper secret process - " I used a *modified* Savitzky-Golay filter because I apply a weighting function of my own design, tailored to minimize the impact of noise on the result. I called it "Savitzky-Golay" without the "modified" because this post is not about filters, so I decided to keep it simple. I'm working on a peer-reviewed publication to introduce my new weighting function. Furthermore, I also applied a wavelet filter and a low-pass filter. The results are the same. The very large warming in the last 30 years is real, and shows up just as prominently in all the filters I applied."

He turned it into this!


Hurray! The hockey stick is back! Trebles all round! But he can do better: "I’ve also plotted lines marking out the episodes of known changes in the precision of the data...If we plot only the most precise part of the data, from 1800 to the present, we get a very clear picture of the climatological changes in CET for the last two centuries:


Bish, bash, bosh; job done.


Turn Steve McIntyre and Ross McKittrick loose on this guy. Lets see what a little "peer review" does to his manipulation.

I bet if you fed a series of random numbers into his "filter" it would produce the same results.

Never trust a man who uses a weighting factor of his own design, unless he has years of experience in the business being studied.

Example: I used to design weighting factors in predictive models for the supermarket business, because I'd worked in the industry for over twenty years, and I understood the component weightings and their relative importance.

The problem in the glowball wormening "industry" is that it's peopled with morons who understand climate but not statistics, and vice versa. And even the climatalogical statisticians have an agenda (ie. to push the we're all gonna diiieeeee!!!! theory), because their funding is dependent on a high level of public alarm.

Kill them all. The effect on our climate will be miniscule.

His results are very different to the results of this analysis:


It seems like he is finding hockey sticks in just about everything.

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