Monday, April 27, 2015

Independent audit of adjustments to climate data

Good:
My cue for those pieces was the evidence multiplying from across the world that something very odd has been going on with those official surface temperature records, all of which ultimately rely on data compiled by NOAA’s GHCN. Careful analysts have come up with hundreds of examples of how the original data recorded by 3,000-odd weather stations has been “adjusted”, to exaggerate the degree to which the Earth has actually been warming. Figures from earlier decades have repeatedly been adjusted downwards and more recent data adjusted upwards, to show the Earth having warmed much more dramatically than the original data justified.
So strong is the evidence that all this calls for proper investigation that my articles have now brought a heavyweight response. The Global Warming Policy Foundation (GWPF) has enlisted an international team of five distinguished scientists to carry out a full inquiry into just how far these manipulations of the data may have distorted our picture of what is really happening to global temperatures.
I've been blogging about the fishy adjustments to the data for five years or so.  There are some heavy hitters on the panel, and so I expect some pretty pointed results to be announced when they are done.

Hat tip: Rick via email, who remarks "They're catching up to you".

5 comments:

Ted said...

Don't worry worry we are going to put our Top Men on it ......... Top men.

Move along ....... Nothing to see here.


Yes. Top men!!!!!

libertyman said...

Just to reiterate, if you adjust data does it still remain data?

Borepatch said...

libertyman, that's precisely the question.

Matt W said...

Yes, it is still "data" but the integrity of the data is suspect so the information that can be derived from that data is also suspect.

Ted said...

It's one thing to "clean" your dataset to eliminate the null's. /. Prevent divisions by zero. /. Maybe even reduce the number of " outliers".

It's an entirely different thing to "adjust " your data set to account for various factors that may or may not be valid. Then your any conclusions based on those factors are only as valid as the ogininal factors. Throw in some secret sauce and the whole thing is highly suspect