A collection of fudge from The Team, sweet!
Solution 1: fudge the issue. Just accept that we are Fast-trackers and can therefore get away with anything.
[Hat tip: M. Hulme]
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.
I will press on with trying to work out why the temperature needs a ‘fudge factor’ along with the poorer modelling for winter.
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?
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.
Either the scale needs adjusting, or we need to fudge the figures…
;****** APPLIES A VERY ARTIFICIAL CORRECTION FOR DECLINE*********
2.6,2.6,2.6]*0.75 ; fudge factor
if n_elements(yrloc) ne n_elements(valadj) then message,’Oooops!’
h/t to Tom Nelson
Maybe it isn’t fudge, but a social issue. Robert Bradley writes:
Here is my favorite quotation:
“[Model results] could also be sociological: getting the socially acceptable answer.”
- Gerald North (Texas A&M) to Rob Bradley (Enron), June 20, 1998.
See “Gerald North on Climate Modeling Revisited (re Climategate 2.0)”: http://www.masterresource.org/2011/11/gerald-north-on-climate-modeling-revisited-re-climategate-2-0/