Models get cloud feedback wrong, but *only* by 70W/m2 (that’s 19 times larger than the CO2 effect)

Yet another paper shows that the climate models have flaws, described as “gross” “severe” and “disturbing”. The direct effect of doubling CO2 is theoretically 3.7W per square meter. The feedbacks supposedly are 2 -3 times as strong (according to the IPCC). But some scientists are trying to figure out those feedbacks with models which have flaws in the order of 70W per square meter. (How do we find that signal in noise that’s up to 19 times larger?)

Remember climate science is settled:  like gravity and a round earth. (Really?)

Miller et al 2012 [abstract] [PDF] find that some models predict clouds to have a net shortwave radiative effect near zero, but observations show it is 70W per square meter. Presumably, cloud shortwave radiative effect means the sunlight bouncedupwards off the surface of the clouds and out into space.

What’s especially interesting about this paper is the level of detail. They test shortwave and longwave radiation, precipitation flux, integrated water vapor, liquid water path, cloud fraction, and they have observations from the top of the atmosphere and the surface. With so much information they can test models against short wave and long wave radiation, to see how well the models are really simulating clouds.

We can also see how four models appear to do well on one parameter, only to invariably fail on another. It is easy to see how a not-so-diligent researcher could “verify” some aspect of each and every model but without testing and comparing all the aspects, these single point “successes” are meaningless.

Critics will say this study was just one year in one region (2006 over the African Sahel) but if global climate models don’t understand cloud microphysics and the radiative effect of the condensed water vapor that covers 60% of Planet Earth, then they can’t predict the climate anywhere. And no, the pretense that predicting climate 100 years in advance is somehow easier than predicting a single year is bollocks… 100 years of climate modeling means adding up 100 years of errors. The errors don’t cancel out, theyaccumulate.

Jo Nova

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