Movie Trailer
http://www.youtube.com/watch?feature=player_embedded&v=IZzMuU7oNBs

http://blogs.telegraph.co.uk/news/jamesdelingpole/100121659/climategate-2-0-junk-science-101-with-michael-mann/

ClimateGate FOIA grepper! – Email 2035

do know that Trenberth, [Dai's] co-author, is extremely defensive and combative when ever criticized about anything because he figures that he is smarter than everyone else and virtually infallible. [Ed Cook]
—
Keith [Briffa] indicated that you discovered a computational error in Dai’s program that produced unusually extreme PDSI values in some cases. (Has Dai and that miserable prat Trenberth been told about this? As you might tell, I have genuine dislike for that arrogant Kiwi) [Ed Cook]

http://tomnelson.blogspot.com/2011/12/ed-cook-says-that-trenberth-extremely.html

Climategate 2: A consensus emerges

http://www.abc.net.au/unleashed/3707172.html

Read about Tony Cox here:-

http://www.climateconversation.wordshine.co.nz/open-threads/climate/regions/australia/#comment-26245

Anthony Cox is a lawyer and secretary of The Climate Sceptics, he has degrees in law and climatology

ClimateGate FOIA grepper! – Email 636

Solution 1: fudge the issue. Just accept that we are Fast-trackers and can therefore get away with anything.
[Hat tip: M. Hulme]

Email 5175-Tom Wigley – 2004

In any simple global formula, there should be at least two clearly identifiable sources of uncertainty. One is the sensitivity (d(melt)/dT) and the other is the total available ice. In the TAR, the latter never comes into it in their analysis (i.e., the ‘derivation’ of the GSIC formula) — but my point is that it *does* come in by accident due to the quadratic fudge factor. The total volume range is 5-32cm, which is, at the very least, inconsistent with other material in the chapter (see below). 5cm is clearly utterly ridiculous.

Email 5054, Colin Harpham, UEA, 2007

I will press on with trying to work out why the temperature needs a ‘fudge factor’ along with the poorer modelling for winter.

Email 1461, Milind Kandlikar, 2004

With GCMs the issue is different. Tuning may be a way to fudge the physics. For example, understanding of clouds or aerosols is far from complete – so (ideally) researchers build the “best” model they can within the constraints of physical understanding and computational capacity. Then they tweak parameters to provide a good approximation to observations. It is this context that all the talk about “detuning” is confusing. How does one speak of “detuning” using the same physical models as before? A “detuned” model merely uses a different set of parameters that match observations – it not hard to find multiple combinations of parameters that give the similar model outputs (in complex models with many parameters/degrees of freedom) So how useful is a detuned model that uses old physics? Why is this being seen as some sort of a breakthrough?

Email 1047, Briffa, 2005

We had to remove the reference to “700 years in France” as I am not sure what this is , and it is not in the text anyway. The use of “likely” , “very likely” and my additional fudge word “unusual” are all carefully chosen where used.

Email 723, Elaine Barrow, UEA, 1997

Either the scale needs adjusting, or we need to fudge the figures…

Briffa_sep98 code

;****** APPLIES A VERY ARTIFICIAL CORRECTION FOR DECLINE*********
;
yrloc=[1400,findgen(19)*5.+1904]
valadj=[0.,0.,0.,0.,0.,-0.1,-0.25,-0.3,0.,-0.1,0.3,0.8,1.2,1.7,2.5,2.6,2.6,$
2.6,2.6,2.6]*0.75 ; fudge factor
if n_elements(yrloc) ne n_elements(valadj) then message,’Oooops!’

http://tomnelson.blogspot.com/2011/11/climategate-emails-oh-fudge.html

“Our science is solid and it proves unequivocally that the world is warming and that this warming is due to human activities.” – WMO Deputy Secretary-General Jerry Lengoasa