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Testing Climate Models Against Reality: What a Novel Idea!
Reference
Groisman, P.Ya., Bradley, R.S. and Sun, B.  2000.  The relationship of cloud cover to near-surface temperature and humidity: Comparison of GCM simulations with empirical data.  Journal of Climate 13: 1858-1878.

What was done
"Will cloud cover enhance the process of climate changes (i.e., provide a positive feedback) or will it dampen any changes (i.e., provide a negative feedback)?"  This is the question that inspires the authors' work.  They note that "modern GCMs parameterize effects of clouds differently and produce a wide range of apparent 'effects' of cloudiness on climate" and that the proper treatment of cloud cover "is crucial for a proper assessment of the climate system."  They then note that to determine if a model's treatment of cloud cover is "proper," it must be shown that the model contains a package of physical parameterizations that function successfully on timescales from diurnal to decadal and that fully describe the behavior of the contemporary climate system.  With this said, they proceed to use modern empirical observations to conduct just such a reality check.  Specifically, they evaluate the models for what they predict in terms of differences between long-term mean values of surface air temperature and atmospheric humidity for average and clear sky or for average and overcast conditions.

What was learned
In the words of the authors, "not all the GCMs reproduce these associations properly."  Although there was a general agreement in reproducing mean daily cloud-temperature associations in the cold season among all models tested, "large discrepancies between empirical data and some models are found for summer conditions."  In one of the models, in fact, the overall cloud effect on summer surface temperature was actually of the wrong sign!

What it means
The authors conclude that "a correct reproduction of the diurnal cycle of cloud-temperature associations in the warm season is still a major challenge for two of the GCMs that were tested," suggesting to us that state-of-the-art GCMs still have a long way to go before their predictions - especially of warming - can be given much credence.  Yet powerful forces at work in the world have for years claimed that we must revamp our entire system of energy production based on what the predecessors of today's GCMs predicted "way back when."  Does that not seem strange?  Does it not suggest that there is some ulterior motive for wanting such changes? ... and that climate model predictions of global warming are but a wonderful lever for pushing the world in that direction?


Reviewed 15 July 2000