Scientists started manipulating temperatures upwards after 1960, and then they were surprised to find that their manipulated data diverged from tree rings. What is the average IQ of this lot?
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“What is the average IQ of this lot?”
Ironically, their IQ matches the adjustment values prior to 1960.
How do you hide the decline? Let’s get Mikey! He hides everything.
Is Mikey your pet dog, to whom everything looks like a bone?
Mikey’s Pet dog is Tammy over at Airhead! Or maybe they are Litter mates!
To Mikey, everything looks like a hockey stick.
There’s the problem thorny with lying about/manipulating the data. You have to constantly remember who got which lie/adjustment so you can tell the same lie consistently. But eventually you forget and it all breaks down.
Sort of like Caspar Ammann and Gene Wahl trying to cross-reference two of their own papers that were going through simultaneous review. It’s hard to claim logical precedent when you don’t know which paper is finally going to come out “first”.
Intellegence Quotient: Possibly high on standard tests
Integrity Quotient: Below 5th percentile, by any measure
Influence Quotient: Dropping like a stone (priceless!)
Yeh, that was a hoot, but I’m really beginning to doubt the IQ is very high. Some of the things they do and say, it just isn’t believable they’re capable of complex thought. Maybe the 100-120 range, but I wouldn’t give most of them more than that.
The Tree Ring Divergence post 1960… This is a joke, right?
CEOs, CFOs, etc. whose pay, bonus, & stock options depend on the value of a companies stock, manipulate numbers to inflate the numbers to get more money. Climate Scientists, whose grant money depends on showing that their line of research is valid manipulate numbers to get more grant money. Difference? Problem? Same final disposition?
So climate scientists are inherently CEO material? Enron anyone!
The corporation I worked for used performance to base pay raises and bonuses for second level managers and above, so the sharpest pencil got the best annual increases. Although not listed in the job requirements creative writing skills resulted in the greatest advancement opportunities.
Where I work results are Important, but Integrity is formost. And we are audited, internally and externally, on a regular basis (someone, not at my organization but within the program, just got prison time for blowing off weld inspections). Never fudge the numbers, you always get caught eventually.
Steve,
Do you have a source for this data. I know the link is to NCDC / NOAA but THEY don’t provide a data source. This is impressive.
It is probably based on their value added corrections to “KNOWN” errors! “Wink, Wink”
Sean
See below link (towards bottom of page).
Paul
http://www.ncdc.noaa.gov/oa/climate/research/ushcn/ushcn.html
Yes Sean. It is USHCN Version 1 data.
Nobody uses it.
So where is the equivalent graph for the current version?
Mosh
Are you saying the latest version has gone back to raw data or does it still show a similar level of adjustment?
“net effect is about the same as that of the TOB adjustments in the HCN version 1 temperature data (Hansen et al. 2001), which is to be expected since the same TOB-adjustment method is used in both versions.”
ftp://ftp.ncdc.noaa.gov/pub/data/ushcn/v2/monthly/menne-etal2009.pdf
Ahh, good old menne et al again.
My statistics training taught me that you cannot ‘correct’ errors after the fact. This is equally true whether the errors are systematic or stochastic.
To ‘correct’ an error you have to be certain how large it is, in which direction, and what it’s uncertainty is, *before* the measurements are made.
The best you can honestly do is accommodate the additional variance by stirring it into the pot.
You seem to say that one size fits all is not the best practice!
Or in cases where possible, throw the errant data out.
Before we all get hung up on USHCN version 1 v version 2 , According to Steve MacIntyre NCDC say :-
recent scientific advances that better address uncertainties in the instrumental record. Because different algorithms were used in making adjustments to the station data which comprise both data sets, there are small differences in annual average temperatures between the two data sets. These small differences in average temperatures result in minor changes in annual rankings for some years”.
There are no substantial changes and the issue of the difference between raw + final remains even though there does not appear to be a specific graph to show it under version 2.
http://climateaudit.org/2007/02/15/ushcn-versions/