CO2 alarmism is now falling apart because the global warming predicted by the IPCC ratified climate models show little similarity with observations of no warming the last 17 years. This is commonly viewed as evidence that mathematical modeling of global climate is impossible because weather and climate is "chaotic" and thus unpredictable.
It is true that weather is not predictable over more than a week, but climate as averaged weather may well be mathematically predicatble over long time. For example, the simple climate model of no change of global temperature, may well be a good model over centuries, until the next ice age.
The IPCC climate models predict global warming (at variance with observations) because they are so constructed, that is to show warming even if there is none, not because it is impossible to construct climate models which fit observations.
The defunding of mathematical climate modeling to be expected because of the failure of the IPCC models thus lacks rationale in a world in which prediction is needed and may be possible by clever use of computational mathematics.
In any case the question of the role of climate modeling is now on the table.
Hi Claes,
SvaraRaderaIndeed, a "no change" null hypothesis climate model outperforms IPCC models by factor of 7:
http://hockeyschtick.blogspot.com/2013/10/a-scientific-no-change-in-temperature.html
and a simple stochastic model also outperforms IPCC models:
http://hockeyschtick.blogspot.com/2013/08/simple-climate-model-outperforms-ipcc.html
In my recent posts on Lorenz and chaos theory, I was referring to the GCMs used by the IPCC et al have not proven their skillfulness, not that there isn't any method to produce reasonable predictions, but didn't make that clear.
The GCMs appear to have little skill beyond a few years, due to incorrect assumptions [i.e. sensitivity] and the exponentially propagating errors due to chaos.