Climate modeling - a dose of reality
A thoughtful comment that was elevated to a full post - at
Watts Up With That:
The �ensemble� of models is completely meaningless, statistically
Saying that we need to wait for a certain interval in order to conclude that �the models are wrong� is dangerous and incorrect for two reasons. First � and this is a point that is stunningly ignored � there are a lot of different models out there, all supposedly built on top of physics, and yet no two of them give anywhere near the same results!
This is reflected in the graphs Monckton publishes above, where the AR5 trend line is the average over all of these models and in spite of the number of contributors the variance of the models is huge. It is also clearly evident if one publishes a �spaghetti graph� of the individual model projections (as Roy Spencer recently did in another thread) � it looks like the frayed end of a rope, not like a coherent spread around some physics supported result.
Note the implicit swindle in this graph � by forming a mean and standard deviation over model projections and then using the mean as a �most likely� projection and the variance as representative of the range of the error, one is treating the differences between the models as if they are uncorrelated random variates causing deviation around a true mean!.
Say what?
This is such a horrendous abuse of statistics that it is difficult to know how to begin to address it. One simply wishes to bitch-slap whoever it was that assembled the graph and ensure that they never work or publish in the field of science or statistics ever again. One cannot generate an ensemble of independent and identically distributed models that have different code. One might, possibly, generate a single model that generates an ensemble of predictions by using uniform deviates (random numbers) to seed �noise� (representing uncertainty) in the inputs.
This is just a small excerpt -- the entire thing is a wonderful eye-opener and wonderful smack-down on the global warming crowd.
Models are only good if they accurately model the behavior of what they are based on. The climate change models have never ever worked. The simplest test is to see how well they hindcast. There are all sorts of doom and gloom forecasts but when you plug the last 200 years of climate data into these models, they do not hindcast accurately -- the climate conditions the models say we are supposed to have now do not match what we measure now. No match!
Posted by DaveH at June 18, 2013 8:46 PM