muso wrote on Aug 17
th, 2012 at 7:01pm:
Soren wrote on Aug 17
th, 2012 at 9:35am:
Climate sensitivity of 3 °C is not climate change by 3 °C, of course.
Climate sensitivity of 3 °C means a predicted change due to CO2 IF NOTHING ELSE changes.
Keep trying and you'll understand it eventually. The radiative forcing due to CO2 plus methane plus nitrous oxide plus ozone etc is around 4W/m2. This equates to about 1 Celsius degree (1 Kelvin, 1K) for a doubling of CO2. Added to this are the various feedbacks which occur as a result of the CO2 (etc) forcing. These include the water vapor feedback, the ice-albedo feedback, the cloud feedback, and the lapse rate feedback. Now if we add up all these feedbacks and together with the radiative forcings, we get a sensitivity to CO2 doubling of approximately 3 °C ± 1.5 °C.
Now this does not include such unlikely scenarios as the Earth suddenly shifting off its axis due to Iranian Clerics masturbating, enormous stratospheric volcanoes such as the Mt Toba eruption, which happened about 70,000 years ago, huge meteroid impacts, dramatic rapid fluctuations in solar output or God sneezing.
So yes, it doesn't account for any of the above changes.
What I'm describing here is strictly equilibrium climate sensitivity. This applies over about a 100 year timescale. Apart from that, there is "effective climate sensitivity" (ESS) which covers slower factors as major albedo changes such as those due to major ice caps melting. This is less certain than the ECS, but is likely to be around double that of the ECS,
sigh.....
Then there is the transient climate sensitivity(TCS), much beloved of Roy Spencer and his croneys. The TCS is lower than the ECS because it doesn't take into account the "inertia" of ocean heat uptake.
You make it sound like feedback behaviour are known. Far from it. It is still well in the assumption stage from the AGW'rs of an increase rather than a descrease in temp due to feedbacks
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 bounced upwards 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, they accumulate.
Even though the models are tested below with one year (2006) as the dotted blue line, the blue bands are envelopes of model outputs for 2001-2010, and we would hope that even if the models got the year wrong, the observations would at least fall within the extremes of the decadal predictions, but frequently they didn’t. Indeed the authors note that the decade itself was not that critical saying “virtually the same results are obtained when the GCM solution envelope is stretched to thirty years.”
The four global models tested are: CM2, HADGEM1, CCSM3 & GISS-EH
much more
http://joannenova.com.au/2012/08/models-get-cloud-feedback-wrong-but-only-by-70w...