Maths great in solving problems or predicting outcomes if all the variables are included and given the correct weight.

This is where climate modelling fails dismally. Really complex systems are difficult to express mathematically because we don't know all the variables are,their interactions and degree of influence.

Thank you for this article and its very important implications. As a scientific academic of many years I have witnessed the dumbing down of hardcore disciples (relative to soft science) to such an extent it is possible to be a graduate major in biological science without a working knowledge of statistics and calculus. IMHO such a graduate is unemployable. The present appalling situation almost certainly derives from the desire of so called universities to put bums on seats for funding purposes and from the desire of the Labor/Greens to insist that everybody can have a tertiary education irrespective of whether they have the ability or even want such a degree. It is time to get education reformed from the grass roots up in this nation regardless of what the rest of the world is doing. China could eat us in respect for scholarship without even being aware of it.

Amusing post by Jeremy who links to some one or other who says about Spencer:

"Which seems to go completely against the point I thought he was trying to make, that some sort of internal variability was responsible for decadal climate change."

Internal variability is now being proved to be the dominant cause of climate change.

Later the link, in the comments says:

"More importantly, the central problem with Spencer's argument for PDO (or any other oscillation) driving warming is that he is trying to fit a rising curve to something that oscillates up and down. The only part of the 20th century curve you can really match that way is the part that goes sort of up-and down - the middle 1930 to 1980 bit."

This is wrong; PDO has been shown in many papers be asymmetrical in the intensity of the phases and their duration as this simple graph shows:

http://farm3.static.flickr.com/2702/4503452885_79b5c09c4f_o.jpg

Also in the comments someone more alert than either Jeremy or the author says:

"I thought Spencer's novel claims were about the forcing/feedback distinction, and whether it was appropriate to add upwelling SW and LW at the TOA to derive the TOA forcing when they have different effects at the surface, and he only plugged the data into a noddy model to get a first order estimate of what it meant. He first showed how the conventional feedback diagnosis method applied to the idealised situation with a step-function forcing gives the right answer (saying much the same as you just did), then showed how quasi-random fluctuations in forcing messed this up. Is there much progress to be made in spending a lot of time criticising the noddy estimate, and ignoring what he claims to be the main point?"