It seems depending on who you talk to, climate sensitivity is either underestimated or overestimated. In this case, a model suggests forcing is underestimated. One thing is clear, science does not yet know for certain what the true climate sensitivity to CO2 forcings is.
There is a new Paper from Tanaka et al (download here PDF) that describes how forcing uncertainty may be underestimated. Like the story of Sisyphus, an atmospheric system with negative feedbacks will roll heat back down the hill. With positive feedbacks, it gets easier to heatup the further uphill you go. The question is, which is it?
Insufficient Forcing Uncertainty Underestimates the Risk of High Climate Sensitivity
ABSTRACT
Uncertainty in climate sensitivity is a fundamental problem for projections of the future climate. Equilibrium climate sensitivity is defined as the asymptotic response of global-mean surface air temperature to a doubling of the atmospheric CO2 concentration from the preindustrial level (≈ 280 ppm). In spite of various efforts to estimate its value, climate sensitivity is still not well constrained. Here we show that the probability of high climate sensitivity is higher than previously thought because uncertainty in historical radiative forcing has not been sufficiently considered. The greater the uncertainty that is considered for radiative forcing, the more difficult it is to rule out high climate sensitivity, although low climate sensitivity (< 2°C) remains unlikely. We call for further research on how best to represent forcing uncertainty.
CONCLUDING REMARKS
Our ACC2 inversion approach has indicated that by including more uncertainty in
radiative forcing, the probability of high climate sensitivity becomes higher, although low climate sensitivity (< 2°C) remains very unlikely. Thus in order to quantify the uncertainty in high climate sensitivity, it is of paramount importance to represent forcing uncertainty correctly, neither as restrictive as in the forcing scaling approach (as in previous studies) nor as free as in the missing forcing approach. Estimating the autocorrelation structure of missing forcing is still an issue in the missing forcing approach. We qualitatively demonstrate the importance of forcing uncertainty in estimating climate sensitivity – however, the question is still open as to how to appropriately represent the forcing uncertainty.
h/t and thanks to Leif Svalgaard
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I’ll have to read all of that. It will be interesting to see how greater uncertainty does not make it harder to rule out lower sensitivity.
“there are things we know we know. We also know there are known unknowns”
how ironic…
“The greater the uncertainty that is considered for radiative forcing, the more difficult it is to rule out high climate sensitivity, although low climate sensitivity (< 2°C) remains unlikely."
This statement sounds like an assumption is being made. I will have to read it to find out, but not now.
Although much of what was summarized here pings my [snip] meter, I parse this sentence, “The greater the uncertainty that is considered for radiative forcing, the more difficult it is to rule out high climate sensitivity, although low climate sensitivity (< 2°C) remains unlikely." as:
"The less we know about something, the harder it is to rule things out, even the results we aren't looking for."
Am I parsing this wrong? Because this seems like a very obvious statement worded ambiguously.
In my experience, the more the writer knows about a subject, the easier it is to read what what they have written. Foggy language often obscures foggy ideas. Just an observation.
From the PDF report:
page 7, lines 6, 7, & 8
“. . . subject to uncertainties (CO2, CH4, and N2O forcing), prescribed/parameterized radiative forcing without uncertainties (other greenhouse gas, aerosol, volcanic (Ammann et al., 2003), and solar (Krivova et al., 2007) forcing), and “missing forcing.”
Overall this is too technical for me but I do wonder whether water vapor is included in “other greenhouse gas” or not at all? Stratospheric H2O is mentioned at the end of Sec. 2.1, p. 5. There has been considerable discussion about clouds in the context of ‘forcing’ and they seem not to be included here.
The Unwashed Speaketh:
H2O is around 90% or more of GHG. CO2 is way less than 5%.
H2O, above freezing, absorbs heat. H2O, below freezing, allows heat to increase.
So, either, the CLIMATE is the egg IN the bowl, maybe rolling, but not splatting.
Or, the CLIMATE is on top of the bowl, rolling off at some point, and going SPLAT.
Right??
Yes, I will read it too.
I am going to assume, for now, that there being too much noise, too many signals, and the inability to distinguish Signal from Noise.
We need a detangler.
Until then, don’t monkey around with all those dials.
Leverite.
First impression: Our models all do a lousy job of estimating climate sensitivity, but we’re pretty sure it’s worse than we thought anyway.
I must be really dumb, please explain how greater ignorance about CO2 forcing results in greater sensitivity in forcing. It would appear to me that the very tiny amount of CO2 in the atmosphere would preclude any appreciable effect.
Temperature of the hydrosphere sets the percentage of the total CO2 in the enviroment that is in solution and the percentage that is in the atmosphere. Therefore temperature leads and CO2 follows, as most research facts seems to indicate.
Sounds to me like the greater the uncertainty the more certain you can be about the climate having high sensitivity than low sensitivity. Can anyone help me out with an alternative explaination to this?
What is certain is regardless of how much CO2 was in the atmosphere, every time it has been warmer civilizations have thrived and the more CO2 in the atmosphere the better it is for life on this planet. It has NEVER been warm enough on Earth or had never TOO MUCH CO2 to be toxic for life and civilizations. The debate is not over in this case, it’s nonsense to have such debate.
One would naturally assume that the preponderance and the properties of H2O would speak heavily for the egg in the bowl, n’est ce-pas?
Second impression: Our models all do a lousy job of estimating climate sensitivity and we don’t have any real idea how to make them better, but at least we have fixed one problem. Now there is virtually no possibility that one of them will kick out a prediction of low climate sensitivity accidentally.
Wordy way of requesting more research grants…
Does Leif Svalgaard agree with the characterisation of solar forcing displayed in the graph shown, and please would he explain what the red solar curve is representing in case I misunderstand it.
Thanks
already the uncertainty in aerosols is sufficient to make a low climate sensitivity for CO2 more likely. http://www.ferdinand-engelbeen.be/klimaat/oxford.html
Claiming an uncertainty that is only valid for the high end of the results is unscientific.
And I have to read the paper, to understand…
Surely this can be experimentally tested in a more direct fashion? Like testing how well parcels of “atmosphere” with slightly different levels of CO2 retain heat? It would need a little elegance in design to ensure all other factors remain the same, sure, but it would seem not too difficult a thing to do. Why would you need to “model” something like this when it would appear to be an issue that lends itself to simple measurement? Another thing that bothers me, if the sensitivities were high, surely we’d have had a run-away greenhouse effect sometime in the last 600 million years? It seems fairly well understood that a warming ocean outgases CO2, so once CO2 levels rise, they’d increase temps, which would warm the oceans which would outgas CO2, which would increase temps, which would warm the oceans, which would outgas CO2…
Why is the heat retention of different combinations of gases not tested directly? Or has that been done? A positive result, i.e. CO2 being shown to considerably effect the heat retention of a parcel of gas representative of the earth’s atmosphere would not, on its own, prove the AGW hypothesis as you’d still need to examine the various feedback processes but a negative result would falsify it. Has this been done?
I think you don’t understand the difference between positive feedback and negative feedback.
Negative feedback will not send the ball rolling back down the hill, it will only set a limit on how far up the hill it will go. Positive feedback will push it further up the hill. The tussle between the two will still see the ball going up the hill, the only question will be how far up the hill it goes.
Well, that’s settled then.
One would think that increasing uncertainty would not only indicate greater sensitivity but also less sensitivity, unless they only add uncertainty in one direction, up. Though they are correct, its a key issue that needs to be addressed and greater uncertainty needs to be conveyed to the public.
I’ll decode the rather opaquic language.
We can make the models work by changing the past solar radiative forcing and increasing the CO2 forcing sensitivity.
Firstly, it’s an implicit admission the models don’t work.
Secondly, Leif is adamant that past variations in solar radiation couldn’t have caused more than 10%(?) of the last century’s observed warming. His is the best scientific assessment we have, and I have no problem accepting it.
Thirdly, they also admit to a ‘missing forcing’. Something the models don’t include because the scientists don’t know about it.
Of course all of this is predicated on the surface record being correct and we know there are a host of issues with it. My assessment is that they are clutching at straws in order to explain something that doesn’t exist in the first place – a large part of the rise in global temperatures determined from the surface stations (and the average of Tmin and Tmax).
Interesting stuff, but is there not a whiff of Thomas Aquinas here? Much discussion about the number of angels capable of dancing on the head of a pin but ignoring the possibility that there are no angels. You can tweak models of a chaotic system all you like but it still has nil predictive power.
The only real question here is, Is climate a chaotic system? If the answer is yes, then don’t waste your time trying to model it. If no, please explain to this poor moron how climate (weather writ large) can be linear while weather has been shown not to be. Also, I’d like a critique of my thought that using an ensemble of model runs simply averages out the inputs and leaves a trend that is entirely due to the assumptions built in to the model.
Again it is all model based and calibrated against past events by using missing forcing parameters. It adds nothing to the discussions and has no more credibility than any other model based prediction.
If I’m understanding this, the paper is deriving climate sensitivity from the combination of historical surface temperatures and historical forcings? Is that right? I may be missing the point.
The question would then be, if so, how certain these quantities are.