Back in 2007, the IPCC AR4 SPM stated that:
“Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”
This is a clear statement that I think is very well supported and correctly reflects the opinion of most climate scientists on the subject (and was re-affirmed in two recent papers (Jones and Stott, 2011;, Huber and Knutti, 2011)). It isn’t an isolated conclusion from a single study, but comes from an assessment of the changing patterns of surface and tropospheric warming, stratospheric cooling, ocean heat content changes, land-ocean contrasts, etc. that collectively demonstrate that there are detectable changes occurring which we can attempt to attribute to one or more physical causes.
Yet, in a paper just out in BAMS (Curry and Webster, 2011) this statement is apparently evidence that IPCC is unable to deal with uncertainty. Furthermore, Judith Curry has reiterated on her blog that the term ‘most’ is imprecise and undefined. For instance:
Apart from the undefined meaning of “most” in AR4 (which was subsequently clarified by the IPCC), the range 50.1-95% is rather imprecise in the context of attribution.
However, Curry’s argument is far from convincing, nor is it well formed (why is there a cap at 95%?). Nor was it convincing when I discussed the issue with her in the comments at Collide-a-Scape last year where she made similar points. Since the C&W paper basically repeats that argument (as has also been noticed by Gabi Hegerl et al who have a comment on the paper (Hegerl et al.)), it is perhaps worth addressing these specific issues again.
Let’s start with what the statement actually means. “Most” is an unambiguous adjective (meaning more than half), and ‘very likely’ in IPCC-speak means that the statement is being made with between 90 to 99% confidence (i.e. for every 10 such statements, the scientists expect 9 or more to pan out). Given that some people have found this confusing, it may help somewhat if the contents of the statement are visualised:
Figure 1: Two schematic distributions of possible ‘anthropogenic GHG contributions’ to the warming over the last 50 years. Note that in each case, despite a difference in the mean and variance, the probability of being below 50, is exactly 0.1 (i.e. a 10% likelihood).
The figure shows two Gaussian distributions, both of which have the probability of x being less than 50 at 0.1. i.e. P(x<50)=0.1. If either of them had been the distribution of the estimated increase in global temperatures due to anthropogenic greenhouse gas increases relative to the observed increase, the IPCC statement would have been almost exactly correct (i.e. if x=100*trend_caused_by_GHG/actual_trend). These distributions show a number of key issues that need to be appreciated. First, the actual increase of temperatures purely due to the rise in GHGs is not precisely known (and therefore there is a distribution of potential values). Note that we are presuming that there is a single ‘true’ answer, so the distribution is a measure of our ignorance, not a claim that the answer itself is a random variable.
Second, the IPCC statement is not a declaration about what the most likely value of ‘x’ is. It states merely that P(x> 50%) is at least 0.9. In the two figures, one has the mean value of x at 80%, while the other has the mean value at 100%. Both fit the IPCC statement equally well. Some people have interpreted the IPCC statement confusing the likelihood of the statement with the actual relative trend (i.e. that the 90% refers to the expected attribution), but that would be a big misreading of the text.
Third, there is certainly a potential for the increase in temperatures due to anthropogenic GHG changes to be greater than the observed trend because we know that there have been both natural (volcanic and solar) and human-caused (reflective aerosols, land use change) factors that are expected to have lead to cooling over the post-1950 period (therefore there is no cut off at 95% of the actual trend). The actual trend will be a function of the warming factors, balanced by the cooling factors. And of the warming factors, the well-mixed greenhouse gas (CO2, CH4, N2O, CFCs) changes are the dominant term (about 75% of the increase in warming factors from 1950, the rest is related to black carbon effects, ozone etc.).
Fourth, the statement clearly encompasses many different estimates of what the actual trends are being driven by and is not therefore a particularly strong conclusion. Myles Allen (Allen, 2011) points out that during the drafting, the text was changed from ‘contributed substantially’ to ‘most’, and focused on greenhouse gases rather than the total anthropogenic effect specifically in order to have a more quantitative conclusion and more justifiable statement.
Now let’s put some real numbers in here. Attribution is fundamentally a modelling task, and the principal models that can be used are the coupled GCMs – at least to start with. What do they estimate the warming trend from the well-mixed GHGs to have been over the last 50 years? The figure below shows this for some of the GISS CMIP5 models (more model data can be downloaded from CMIP5 portal):
The 50 year trends (here, from 1956 to 2005, 5 ensemble members), are 0.84ºC (range [0.79,0.92]) for just greenhouse gas forcing. and 0.67ºC (range [0.54,0.76]) for the all-forcings case (in CMIP3, the envelope of the all-forcing trends is [0.4,1.3], or equivalently 0.74 +/- 0.22ºC (1 sigma spread) using 55 individual model simulations – the wider spread reflecting structural variations in the models and forcings). As in the more recent model simulations, the GISS CMIP3 50 year trends using only well-mixed GHG forcings is around 0.1ºC more than the ‘all-forcing’ case (data here).
The actual observed trend depends a little on the dataset used, but is around 0.6 +/- 0.05ºC (1 sigma uncertainty in the OLS fit). If we then estimate the percentage (as illustrated above), assuming a 0.2ºC sigma in the model spread, ‘x’ is roughly 140% +/- 35% (1 sigma). If we interpreted that range as a Gaussian distribution (not really a good idea, but simple enough for illustration), we’d estimate that P(x<50%) would be less than 1% (even less likely than the IPCC AR4 statement allowed for).
There are good reasons why the IPCC assessed that the probability was not as low as suggested by the models or any individual attribution paper. Specifically, the overall assessment must take into account potential structural uncertainties that don’t come into the straight model analysis. For instance, the models may systematically be overestimating the GHG-driven trend, they may be underestimating the internal variability, and they may be undersampling the structural uncertainty in making models themselves. The first kind of error would cause an overestimate in the mean of the distribution, while the other factors would cause an underestimate in the variance of the trends – all would increase P(x < 50%). On the other hand, the net forcing is almost certainly less than the effect of anthropogenic GHGs alone and so that biases the mean of the ‘all-forcings’ trends low, and some of the spread in the trends is related to different models having different forcings (biasing the spread wide). These elements can be quantified during the attribution (using fingerprint scaling, monte-carlo emulators etc.), but when they are all taken into account, the difference is less than one might think (it turns out that structural uncertainty likely isn’t being underestimated and the internal variability in models comfortably spans the range inferred in the real world (Yokohata et al., 2011; Santer et al., 2011)).
Curry and Webster specifically bring up two issues that, they claim, lessen the confidence one should have in the IPCC statement: that the history of solar forcing is uncertain in scale, and that aerosol forcings have a huge error bar. These two statements are true as far as they go – the scale of solar forcing is not tightly constrained prior to about 1960, and the total aerosol forcing and it’s variation in time is uncertain. But C&W’s specific complaint is that the attribution studies used in AR4 used solar forcing that was too large compared to more recent studies. However, reducing any warming trend associated with solar actually makes the attribution statement more likely which somewhat undercuts their point.
With respect to aerosols, the key thing to remember that regardless of the magnitude of the change, the sign of the forcing is almost certainly negative (i.e. the net aerosol effect has been one of cooling). The dominant anthropogenic aerosols are sulphates (derived from the SO2 emitted during the burning of sulphur-containing fossil fuels), which are reflective, and hence cooling. Other aerosols (black carbon, organic carbon, nitrates) are more uncertain, but have a net effect that is smaller.
Now, the statement in AR4 specifically states that the effect of greenhouse gases is more than half of the observed trend, which is actually independent of the effects of aerosols. But with the high probability of aerosols being a net cooling, this increases the ratio of the GHG-driven trends to the actual forced trend.
The final issue is whether the internal variability of the system on multi-decadal timescales has been properly characterised. For instance, it is possible that all the models grossly underestimate the internal variability, in which case any expected trend due to GHGs would be drowned out in the noise. But there is no positive evidence for this at all – as Hegerl et al point out, the estimates of multi-decadal variability in the models and observational records all overlap within their (substantial) uncertainties (arising from the shortness of the record, and the difficulty in estimating internal variability in the presence of multiple forcings). So while it is conceivable be that there is a bias, it is currently undetectable, which implies it can’t be that large.
In summary then, the IPCC AR4 statement was a fair, even conservative, assessment. There is an unfortunate tendency to reify the particular statements made by IPCC, since there were clearly other correct statements that could have been made. For instance, it might well have been worthwhile to add a statement about the likely range of the anthropogenic trends (i.e 80-120% of the actual trend or similar), so that a better picture of the appropriate distribution could be given (see Huber and Knutti, 2011) for examples). But claims that the statement was unsupported, or that it demonstrated that IPCC was ignoring uncertainty are simply untenable.
The next iteration (IPCC AR5) is now underway, but given the early results of the CMIP5 models (which are on the whole very similar, as discussed at fall AGU), and more recent literature on this issue (see refs below), I see no reasons in the recent literature why the conclusions in AR5 will be much different. But if anyone still finds the assessment confusing, they have an opportunity to make their points via the IPCC review process, and the resulting conclusions will likely be clearer because of them.
References
- G.S. Jones, and P.A. Stott, "Sensitivity of the attribution of near surface temperature warming to the choice of observational dataset", Geophysical Research Letters, vol. 38, pp. n/a-n/a, 2011. http://dx.doi.org/10.1029/2011GL049324
- M. Huber, and R. Knutti, "Anthropogenic and natural warming inferred from changes in Earth’s energy balance", Nature Geoscience, vol. 5, pp. 31-36, 2011. http://dx.doi.org/10.1038/ngeo1327
- J.A. Curry, and P.J. Webster, "Climate Science and the Uncertainty Monster", Bulletin of the American Meteorological Society, vol. 92, pp. 1667-1682, 2011. http://dx.doi.org/10.1175/2011BAMS3139.1
- G. Hegerl, P. Stott, S. Solomon, and F. Zwiers, "Comment on “Climate Science and the Uncertainty Monster” J. A. Curry and P. J. Webster", Bulletin of the American Meteorological Society, vol. 92, pp. 1683-1685, 2011. http://dx.doi.org/10.1175/BAMS-D-11-00191.1
- M. Allen, "In defense of the traditional null hypothesis: remarks on the Trenberth and Curry WIREs opinion articles", WIREs Climate Change, vol. 2, pp. 931-934, 2011. http://dx.doi.org/10.1002/wcc.145
- T. Yokohata, J.D. Annan, M. Collins, C.S. Jackson, M. Tobis, M.J. Webb, and J.C. Hargreaves, "Reliability of multi-model and structurally different single-model ensembles", Climate Dynamics, vol. 39, pp. 599-616, 2011. http://dx.doi.org/10.1007/s00382-011-1203-1
- B.D. Santer, C. Mears, C. Doutriaux, P. Caldwell, P.J. Gleckler, T.M.L. Wigley, S. Solomon, N.P. Gillett, D. Ivanova, T.R. Karl, J.R. Lanzante, G.A. Meehl, P.A. Stott, K.E. Taylor, P.W. Thorne, M.F. Wehner, and F.J. Wentz, "Separating signal and noise in atmospheric temperature changes: The importance of timescale", Journal of Geophysical Research: Atmospheres, vol. 116, pp. n/a-n/a, 2011. http://dx.doi.org/10.1029/2011JD016263
#94–
I knew my previous comment was not as clearly written as I’d hoped, so let me try again.
Alex, you had written:
“These features all would occur whatever the cause of the observed warming at the surface and in the oceans.”
That’s not correct. For instance, had surface warming been due to increased insolation, or decreasing albedo, we would not see stratospheric cooling.
Your later comments seem quite bizarre to me, if you will forgive the blunt characterization. They seem to amount to saying that there are multiple “proofs” of the greenhouse effect, but that they don’t prove anything.
But there’s a problem for your idea: the modeled stratospheric cooling can’t be separated from the warming at lower levels. If you throw out the latter, you also throw out the former. Similarly for the other issues: current understanding implies warming. Throw out the implied warming and you also throw out the understanding.
Oh, and by the way, climate sensitivity isn’t programmed into most models–it’s an emergent property. So your suggestion “to build a chemistry climate model with low climate sensitivity” would be, at least, non-trivial.
Brian,
I think you are suffering from the same lack of input/output understanding as BPL. To say a given input will result in a certain output, it must produce that same output, each and every time. A one-time occurrance cannot be attributed to a specific input, if it is not repeatable. This is precisely why scientists attempt to duplicate other scientists work.
#100 Alex Harvey
This statement does not make sense. It sounds like gobbledygook to me. If there were a strong negative feedback you would see a different pattern of cooling in the vertical profile than we are currently seeing. The fact of tropospheric warming and stratospheric cooling matches what would happen if you put a blanket in the troposphere trapping heat.
In other words Prof. Held(? where’s his paper) is saying if the Earth cooled the troposphere and the stratosphere would cool. Of course that makes sense. But what does that have to do with human induced warming?
Look, I’m a skeptic. In fact I’m so skeptical I only sometimes trust peer reviewed papers. I’ll tell you what I do trust though… those papers that survived peer response. Right now you are presenting a tentative hypothesis that sounds like it’s based on an untested idea. That is meaningless until you prove it. So why don’t you write the paper?
Otherwise you are selling snake oil to the masses, and that is not science.
As to Ozone Depleting Substances… Do you really think the science is not examining that??? Have you read any IPCC reports? Have you dug around to catch up on the literature in attribution? If you have, you have not dug deep enough.
Alex says:
As I said in #83, in order for the observed stratospheric cooling to be useful in distinguishing between competing hypotheses you would need to build a chemistry climate model with low climate sensitivity (e.g. 1.5 K) and force that with increased TSI + observed GHG and ODS changes and THEN compare the modelled vertical heat distribution with observations.
Alex, the TSI has been observed to not change significantly during the age of satellites. As I understand it it’s changed enough to quantify temperature anomalies during the solar cycle, but not anywhere near enough to explain the observed warming trend.
IOW, if you actually run the model you propose and vary TSI according to actual observations you don’t get the results you pretend to expect.
If you want to create a model that uses observed atmospheric changes and varies TSI just for fun, go right ahead. It’s not useful in the real world unless you can show that TSI actually *has* changed significantly.
Really, try to do something better than throwing innuendo about not running models there’s no reason to waste time on and pretending it means something.
And while you’re proposing ‘competing hypothesis’ you might try actually citing one that’s consistent with actual observations. You know, actual CO2 levels, actual TSI, actual observed temperature changes. Explaining historical data would be good too: any ‘competing hypothesis’ constraining sensitivity to 1.5 degrees also needs a mechanism to explain paleoclimate. As a free clue for you, that’s, uhm, extremely difficult to do with a sensitivity much below 3.
Alex Harvey,
as added CO2 is known to lead to cooling in the stratosphere is a fundamental result of the physics of radiative transfer it does not help us to distinguish between competing hypothetical explanations for observed global warming.
I don’t understand your logic here. The case for the observed global warming being caused by CO2 is based on the same physics of radiative transfer which says adding CO2 causes the stratosphere to cool. So why do you accept one cause and effect but not the other?
Also, what are the other “competing explanations” for the observed global warming?
Stratospheric ultrafast confusion –
It started @ 20 with a reference to
http://www.gfdl.noaa.gov/blog/isaac-held/2012/01/21/22-ultra-fast-responses/
0. Ultrafast responses are not the only responses.
1. Suppose as in the excellent post by Isaac Held that atmospheric CO2 is instantly doubled.
This changes the radiative properties of the atmosphere. This in turn has consequences, and some of them happen quite quickly.
2. One of these quick responses is stratospheric cooling, which is caused as follows:
a. The stratosphere is heated by UV from the sun, absorbed by O3 (ozone). The stratosphere loses energy (cools) by radiating IR. The famous greenhouse gasses including O3 and CO2 do this. CO2 does not pick up UV energy directly. Instead CO2 gains energy from collisions with O3 – and then CO2 radiates the energy away. So, more CO2, more cooling.
3. But the stratosphere is also warmed by IR from either above or below. Suppose there came to be less IR coming from below. The stratosphere would cool (other things being equal, which they never are).
4. Now suppose we increase atmospheric CO2 slowly. As we know, the surface environment warms and the oceans acquire much more energy. Hence there must be less IR going from below to the stratosphere. (Conservation of energy you know). So, stratospheric cooling again.
Very interesting discussion.
I have another climate 101 question for the experts here, concerning the attribution:
How can you differentiate between H2O and CO2, when trying to find CO2 greenhouse effect?
I mean most of the greenhouse effect is due to H2O, due to the feedback effects.
So what is the fondamental difference between co2 and water that i am missing?
Could stratospheric cooling be caused by increased water vapor in the troposphere, whatever the cause of this increase?
Thanks.
[Response: The stratosphere is mostly affected by concentrations of GHGs in the stratosphere – and that is dominated by CO2 and O3. H2O in the stratosphere is much less than CO2 in abundance, so while it does have an impact, the very small changes (relatively speaking) can’t explain the temperature changes. For instance, strat water vapour goes from ~3 ppmv to 7 ppmv as you go up (increasing because of CH4 oxidation). CO2 is 390 ppm (i.e. 6 to 10 times more). The change in H2O from increases CH4 is a couple of ppm at most, changes because of dyanmics/trop/strat exchange maybe 1 ppm. Changes in CO2 have been over 100 ppm. Even when you factor the radiative effectiveness into it, the changes in CO2 make by far the biggest difference – particularly in the mid to upper-stratosphere. – gavin]
I was looking at the ‘Prof. Held’ statement again. As with so many bad arguments, people set up a hypothetical that has no basis in fact and then say see we don’t know. It’s a straw man argument, but a pretty weak one.
Gavin said:
“For instance, strat water vapour goes from ~3 ppmv to 7 ppmv as you go up (increasing because of CH4 oxidation). CO2 is 390 ppm (i.e. 6 to 10 times more).”
How is that 6 to 10 times more? (Sorry if I’m being dense, but at least I’m paying attention.)
[Response:Sorry, I’m the one being dense. I shouldn’t blog on the run … say 60 to 100+ times as much, instead. – gavin]
For anyone who has the tangential interest, one “Alex Harvey” advanced some ideas at Deltoid a few months ago, starting at #1. Almost all of the 700+ comments on that thread were related to that poster and a shifting set of claims (e.g. #485), at least one of which was based on his use of a term that he refused to define for the majority of the thread.
On that post #46 points out that “…there are at least three Alex Harveys (or Alexander Harveys) who post in climate change forums…” so this Alex Harvey might not be that one. I note that that poster declared he trusted scientists based in part on likability and (ahem) held up Isaac Held as someone who he would trust (#74) because (amongst other reasons) “He doesn’t delete embarrassing posts because when he doesn’t know the answer as at RealClimate – just tells it the way he sees it.” He made various claims about various papers etc. – but also revealed a number of very fundamental errors of understanding and execution that suggest that his interpretation of more sophisticated issues may not be entirely accurate. He clung the concept that it is very likely that there are unknown factors such as (#632) large but hitherto unknown internal variability cycles (or forcings) that might render actual climate sensitivity quite low – despite the lack of evidence for such cycles/forcings, and the existing explanations doing rather well…
…and that poster was referred more than once to RealClimate to benefit from expert discussion (even as it was noted that he quote-mined from RealClimate when it suited him).
Dan H.: “To say a given input will result in a certain output, it must produce that same output, each and every time.”
Whiskey, Tango, Foxtrot? So by your definition, we can’t do physics on anything more complicated than the collision of two billiard balls? Dude, you really need to catch up.
Ray,
The entire input/ouput discussion started with post #34, where it was stated that climate science does not have the luxury of input/output testing. This is generally true, as variables cannot be held constant, but are changing continuously. Jumping from input/output testing to suggest that we cannot do physics on the climate is quite a stretch, to say the least. Physics is much more that just the collisions between two objects.
If you have a method of measuring the effect on the Earth’s climate of changing only one variable, while holding all the others constant, I am all ears. Until then, input/output testing cannot be performed.
Ray, if you get in an argument with Dan H., he wins, because new readers unfamiliar with his tactics will not be able to tell which of you is confusing things and pretending to be a scientist.
“A control variable is a variable that effects the dependent variable. When we ‘control a variable’ we wish to balance its effect across subjects and groups so that we can ignore it, and just study the relationship between the independent and the dependent variables.”
http://www.sahs.utmb.edu/pellinore/intro_to_research/wad/vars_hyp.htm
Dan H., Your conception of science is about 80 years out of date. It would appear that you would deny that biology, ecology, geology, climate science–indeed most of modern science–is science. And yet they work. Complexity does not preclude science.
Hank,
Wow! Is it my imagination, or did you actually agree with me for once. I guess there is a first time for everything.
The arrogance of those who use their guest status in these comments to “teach” others science that does not hold up is staggering.
I would hope they would try to open their minds a bit and actually learn something, since that is what this board is supposed to be for.
> Dan H
suggests it’s necessary to have
> “a method of measuring … changing only one variable,
> while holding all the others constant ….”
Bunk.
Experimental design copes with such variables that can’t be held constant.
Dan then uses his debating ploy again: ignore being shown wrong; claim response to correct his misstatement amounts to agreeing with him.
“blah blah blah blah blah Ginger blah blah blah ….”
Plonk.
Complexity? Who needs it?
One of the first labs in 1st semester physics is to slide a block of wood down an inclined plane that is part of a protractor. You put the block on the plane when it is close to horizontal, then gradually increase the slope until the block slides down. Do it repeatedly until you think you have enough data, or until time runs out. In writing this up you should show understanding
1. of how the downward force of gravity yields a resultant smaller force parallel to the inclined plane
2. that no matter how careful you are, the block slides at quite different angles.
Ray,
Really! It amazes me how you can leap to such crazy conclusions. Complexity is irrelevant. The scientific method works from the simplest up to the most complex systems.
What Matt, Hank, and myself have been referring to is to control certain variables, while changing an input, and observing the output. This is much easier done in vitro than in vivo.
Just because technology has allowed us to analyze more complex systems in ways scientists of the past centuries never dreamed of, does not mean that the scientists of old would deny the science of today. It appears that you are the only in denial; specific with regards to methodolgy.
re. Dan H. and his posts:
It seems he can’t see the big picture no matter how many times he is informed on specific issues and relevance factors. His mind may be filtering out the relevant information preventing him from seeing the big picture or he is for some odd reason practicing the art of obtuscation – new word copyright John Reisman :)
Maybe some posts should come with a new obtuscation label as a guide for new readers!
It is amazing how dense some people can be. Does anybody here do any real science any more? By the content of that last few post, I have to seriously question whether them (Pete appears to understand science).
Equating a simple experiment with the “big picture” seems absurd in all aspects.
Dan H., In systems where control of a single variable is not possible for whatever reason, a well verified model can be used to accomplish the same purpose. Any more, systems of the type you are discussing are the minority. That’s not how science gets done anymore. This isn’t fricking chem lab.
Oh, and Dan, when was the last time you published a peer-reviewed paper?
Dan H.”Hank,
Wow! Is it my imagination, or did you actually agree with me for once. I guess there is a first time for everything.”
Dan, all of your victories are in your imagination.
> What Matt, Hank, and myself have been referring to
Dan pretends corrections are agreement.
Dan is debating imaginary friends.
Boring, deeply boring.
Hank @ 118 “blah blah blah blah blah Ginger blah blah blah ….”
YES, not only apropos to Dan H, but a fantastic Farside reference. I just wanted to let Hank (who I enjoy reading on this board) know that someone got the joke. Woof!
Gavin, thank you for your (quick!) response.
So the basic thing i missed is that the stratospheric cooling is primarily caused by ‘more IR out radiation by more CO2 + less UV absorption by less O3’ rather than ‘less upcoming IR from the troposphere due to more GHG’
Any post/paper on the quantification of each of these causes? Thanks again.
#122 Dan H.
Your wrong. Here’s why. You present your arguments as if they are significant to ‘climate science’ as a whole somehow by inference (whether you admit it or not that is the effect). Focusing on any single experiment is lame at best and incredibly stupid at near worst. There are even worse aspects to your obtuscation though.
Climate science is not about a single experiment and your narrow-minded focus distracts people from the truth of the ‘big picture’.
Climate science, as in all science, is about how the single experiments affect, the bigger picture. You still cant see the forest because there are all these trees in your way.
As to who is dense, look in a mirror. I know, I know, you won’t be able to see your density because you are in the way.
John,
All your insults aside, I was not the one being narrow minded.
My point has been that climate science is not a simple input/output experiment, and that drew the ire of many posters here. Now, ironically, you are arguing my point as if it goes against what I am trying to say. Maybe you should stop listen to the other posters here, especially those who seem to exemplify your final paragraphs.
[You’re once again repeatedly saying nothing of importance and wasting peoples’ time in the process. Contribute something worthwhile or have your comments deleted]
Addendum to my analysis of Dan H.’s perspective:
To those that are interested in understanding ‘real science’ the big picture is the sum of all the little pictures (experiments, observations, physics, etc.) and from the big picture comes more relevant understanding.
Climate science has many facets and all the evidence points to human induced warming. So in all its complexity, it’s as simple as that. Those that have too much density or filters will miss the main point and by inference Dan H. seems to keep missing the point because of his narrow-minded view. Don’t be ‘tricked’ by his obfuscation and keep your focus on what the ‘real science’ is telling us.
Dan H., No one is trying to say climate science is not complex. What we are saying is that complexity does not preclude attribution. There is no reason why science or attribution require a simple analysis with control of all variables. Indeed, in some fields (e.g. ecology), such an approach shortchanges the subject matter and actually fails to predict the system behavior.
Look at what control of variables is trying to accomplish, and then think how the same goal can be accomplished when it is not possible. That is how science is extending its reach.
#129 Dan H.
Pot meet Kettle. Dan, you say others that point out the fallacies in your posts are ‘dense’ and then when you are called on it you say people are insulting you.
There is a bible quote that applies here. Don’t try to remove the splinter from your friends eye until you remove the log from your own.
John,
Are you implying that you are the kettle?
Don’t you find it a bit ironic that you are now carrying the torch I started when I claimed that climate science was not a simple input/output test (technically Matt started it (#34), but I reinforced it). You claim that I am wrong, then seem to repeat my claims. You talk about missing the forest for the trees, but that seems to be what people are doing when they argue for simple testing. I have been arguing that the situation is more complex. You appear to be arguing the same, but claim it is not. I am sure you understand my position on this.
I find it rather humorous that the moderator seems to think my comments are not important, but those who sling mud, make jokes, or add other inane comments are somewhat vitally important to this discussion. If this is where climate science is headed, it is no wonder that support is waning.
“If you have a method of measuring the effect on the Earth’s climate of changing only one variable, while holding all the others constant, I am all ears.”
Climate models.
If you push on a thing hard enough, it will break. If you only have one thing, and you push on it til it breaks, you can’t claim that you didn’t break it because the experiment can’t be repeated, and it might have been just natural variation. We are pushing really hard on our only climate system, and it will eventually break; not a question of whether, but when.
And you can’t really do “identical” experiments on even simple systems like bouncing billiard balls, since the balls, and the momentum, and the position are only known as well as can be measured; measurements are never perfectly identical.
Kevin McKinney, #101:
I am wondering if there is some semantic confusion concerning the distinction between the “greenhouse effect” and the “enhanced greenhouse effect”. I will clarify my own understanding.
I don’t believe there is any argument or uncertainty over the greenhouse effect itself. That there is a “greenhouse effect” has been known since the time of Jean Baptiste-Joseph Fourier in the 18th century and John Tyndall in the 19th century. Tyndall demonstrated empircally the absorption of radiation by atmospheric carbon dioxide.
There is so little to disagree about in the basic theory of the greenhouse effect that Richard Lindzen and Kerry Emanuel could happily co-author an encyclopaedia article together on the subject in 2002:
R.S. Lindzen and K. Emanuel (2002) The greenhouse effect. in Encyclopedia of Global Change, Environmental Change and Human Society, Volume 1, Andrew S. Goudie, editor in chief, pp 562-566, Oxford University Press, New York, 710 pp.
That’s worth reading, by the way, just to see how much Lindzen and Emanuel agree on. Anyhow, I take the greenhouse effect to be about as certain as gravity.
The “enhanced greenhouse effect” is quite another matter. (And I’m sure that Lindzen and Emanuel disagree passionately here.) While no one questions the greenhouse effect, there is much argument and uncertainty once “feedbacks” are included. This is mostly what the global warming controversy is about.
Now as far as I can tell, these “feedbacks” are theories in their own right. In order to estimate how much of the recent warming is the result of natural causes and how much is the result of CO2 emissions, the uncertain theories about feedbacks are combined with the certain theory of the greenhouse effect (and of course plenty of other theories).
Climate sensitivity is the equilibrium response to a doubling of CO2 after assuming the Planck response greenhouse effect + the theory of the water vapour/lapse rate feedback + the various theories of the cloud feedbacks. And depending on which definition of climate sensitivity you are using, you may also include the snow-ice-albedo feedback, vegetation feedbacks and probably others.
Now let me stress that I am not trying to validate the objections of climate change skeptics. It is the IPCC AR4 “very likely” range of climate sensitivity that is (I think) 1.5 K to 6 K and the “likely” range 2 K to 4.5 K. At the 1.5 K end, the warming problem is not that serious. And at the other end, it’s catastrophically serious. And the reason for the discrepancy is uncertainty over the “feedbacks” – uncertainty over the “enhanced greenhouse effect”. Without feedbacks, there would be no uncertainty.
So do we agree so far?
Now… In order for stratospheric cooling to be relevant to attribution – one would think – there would need to be an argument that the magnitude of CO2-caused stratospheric cooling is related in some way to the magnitude of CO2-caused warming at the surface. If not, then appeals to stratospheric cooling as evidence that humans are causing the warming at the surface would not make any sense. Observations of stratospheric cooling would simply be more proof that CO2 levels have increased – which is not disputed.
Now Isaac Held is a climate science veteran and certainly no skeptic. Yet the statement at his blog implies that the rate of stratospheric cooling bears no relationship at all to the greenhouse warming at the surface. I immediately wondered, then how on earth can it be relevant to attribution of warming at the surface? I have asked the question here and received no straight answers. Next stop, I may just ask Prof. Held himself.
Finally, I note that you say building a low sensitivity GCM might be difficult. Well, some of the IPCC climate models already have sensitivities as low as 2.1 K. And without the positive cloud feedbacks they would apparently have a sensitivity of 1.9 K +/- 0.15 K (AR4 Chapter 8). So, I guess you could easily build a low sensitivity model by simply taking out the clouds. Or one could build a parameterisation of Lindzen’s Iris, as proposed in the original Lindzen et al. 2001 Iris paper.
I do hope this is a bit clearer.
Lotharrson, #111:
I am the same person who posted in the Deltoid thread. I am at pains to distinguish myself from the other Alexander Harvey who posts more frequently than I do and appears to have a physical sciences background and a deeper understanding of climate science that I do. Having googled myself, though, I have found many posts by posters named Alex Harvey that certainly aren’t me and I doubt they are the other Alexander Harvey. Thus, I believe there are at least three of us. I live in Syndey, Australia. I am a computer programmer and have an honours degree in history and philosophy of science. I am the Wikipedian of the same name. I have been teaching myself climate change science for about six years.
How about you? ;-)
As the main post says:
“Now let’s put some real numbers in here. Attribution is fundamentally a modelling task, and the principal models that can be used are the coupled GCMs – at least to start with.”
#133 Dan H.
I will be direct.
1. First, thank you for proving my point that you have a high density factor when if comes to learning.
2. Your arguments are ambiguous fluff.
3. I’m not saying it’s complex actually I’m arguing that it’s simple. More CO2 traps more heat, less CO2 traps less heat.
4. Your comments are not important as they rarely have substance.
5. Are you sure you’re not a politician… your spin factor is rather high.
MORE CO2 = MORE TRAPPED HEAT.
If you still think it’s more complex than that after all the evidence is weighed then you are still missing the point.
Clouds, aerosols, albedo, RF, temperature, natural variation, atmospheric constituents, fossil fuel output, attribution, volcanoes, solar, GCR’s, Iris Effect… all weighed and measured. We are warming and humans have imbalanced the radiative forcing of Earth.
#135 Alex Harvey
1. Enhanced is just enhanced (we added some CO2, CH4 and N2O, which is warming the oceans and increasing the H2O.
2. I did a 60 second video on the History of Climate Science with Spencer Weart’s help: http://ossfoundation.us/
3. The controversy about feedbacks in the peer reviewed/responded literature is largely not if they exist or if they are more positive or negative, but rather how strong re. how much warming to expect.
4. Feedbacks are not hypothetical. It is safe to say that without feedbacks, we probably could not get in or out of ice ages as easily as we do.
5. stratospheric cooling = put on a jacket and you trap more heat by radiating it back to your body, thus not allowing it to escape, thus cooling above your jacket (less heat escaping)…
Alex Harvey, Ah, you make a distinction between the greenhouse effect and the “enhanced greenhouse effect”. Do you also distinguish between macro- and micro-evolution? Because these distinctions have equal validity.
You would not get 33 degrees of warming from the greenhouse effect without positive feedbacks. We know with 100% certainty that many of the feedbacks are operative. You cannot make a climate model work without significant positive feedback. I am curious why you think that positive feedbacks magically stop when you reach a concentration of 287 ppmv?
The fact of the matter is that you simply cannot understand Earth’s climate over the eons without such positive feedbacks. The inability of minds like Lindzen’s, Spencer’s, etc. to do so is a direct result of their rejection of such feedbacks.
Alex Harvey
Just found this in:
Southern Hemisphere Atmospheric Circulation Response to Global Warming
PAUL J. KUSHNER, ISAAC M. HELD, AND THOMAS L. DELWORTH
NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey
(Manuscript received 24 February 2000, in final form 1 August 2000)
Can you point me to where Prof. Held says: “the existence of stratospheric cooling tells us nothing about the sensitivity of the climate to increasing greenhouse gases.”
Alex Harvey,
“So do we agree so far?”
I wouldn’t put it that way but it seems we’re basically in agreement.
“Now… In order for stratospheric cooling to be relevant to attribution – one would think – there would need to be an argument that the magnitude of CO2-caused stratospheric cooling is related in some way to the magnitude of CO2-caused warming at the surface.”
No. It’s relevant, just not some kind of total proof.
The cooling and the warming are necessarily related, just not by a simple or well-understood relationship.
“Now Isaac Held is a climate science veteran and certainly no skeptic. Yet the statement at his blog implies that the rate of stratospheric cooling bears no relationship at all to the greenhouse warming at the surface.”
You are the one implying that. Why don’t you quote the guy?
This appeal to authority is bordering on dishonesty in my opinion.
“So, I guess you could easily build a low sensitivity model by simply taking out the clouds. Or one could build a parameterisation of Lindzen’s Iris, as proposed in the original Lindzen et al. 2001 Iris paper.”
I guess. But your model would match observations and reconstructions very poorly, would it not?
So, as you implied earlier, it probably wouldn’t be worth building. :-)
Harvey is misunderstanding Held currently at
http://www.gfdl.noaa.gov/blog/isaac-held/2012/01/21/22-ultra-fast-responses/#comment-436
Although I may amend my current consideration as I try to understand this argument better. Isaac Held seems to be saying that the stratospheric cooling is not a feedback, but rather an ‘ultra-fast’ response.
It does not seem that he is saying there is no connection between increased CO2 and stratospheric cooling.
If my understanding increases I will amend.
Alex, Having read your exchange with Prof. Held, I would say that it seems you are confused about the attribution argument. First, no one tries to determine CO2 sensitivity from stratospheric cooling. Instead the argument goes
1)Stratospheric cooling demonstrates that the greenhouse effect of CO2 is nowhere near saturated.
2)A dozen or so other independent lines of evidence demonstrate that CO2 sensitivity is roughly 3 degrees per doubling, with 90% CL between 2 and 4.5 degrees per doubling.
I’d be careful about going to the 95% CL–a sensitivity above 5 degrees per doubling might as well read “GAME OVER”.
AH 135: At the 1.5 K end, the warming problem is not that serious.
BPL: Want to bet?
I’m not sure that’s a viable or relevant claim about the real world any more. In particular, check out the updated research (illustrated in that post) suggesting that “serious” is already present at 1 K of warming, and note that (regardless of the actual sensitivity) we’re already 80% of the way there and we haven’t reached equilibrium yet, which means 1 K warming is basically unavoidable.
I don’t believe that’s necessary.
Do the feedbacks of interest operate in response to all forcings or just anthropogenic ones? If the former, why do you think that confidence levels in the magnitude of various feedbacks influences attribution confidence? Isn’t is sufficient to measure all the significant forcings (and their confidence levels) and partition them into anthropogenic and natural? (I expect this question to raise your belief/hope as expressed on Deltoid that a significant chunk of recent warming is due to a hitherto unknown, reasonably large, slow pseudo-cyclic natural variation, or some other reasonably large unknown factor as long as it’s anything but anthropogenic.)
Unless I’ve missed something significant, the data clearly doesn’t support the hypothesised effect, so building such a parameterisation wouldn’t have any relevance to the climate system.
Similarly taking out clouds because you are trying to (artificially) lower the sensitivity of the resulting model is not particularly smart. For one thing I would expect that to increase the uncertainty in emergent properties of the resulting GCM such as climate sensitivity thus failing in your apparent goal of a low sensitivity GCM. Lowering the most likely value but widening the uncertainty doesn’t suggest the problem is any less serious. For another thing, the point of GCMs is to model the significant aspects of the climate system with sufficient fidelity to be useful (which includes examining the climate sensitivity of the resultant model) rather than to achieve pre-determined values for some emergent properties at the expense of usefulness and fidelity.
Engineering Ph.D., also in NSW Australia and working in the software industry, including some programming.
I haven’t come across anyone else posting under my nym (with a double “s”).
“In order for stratospheric cooling to be relevant to attribution – one would think – there would need to be an argument that the magnitude of CO2-caused stratospheric cooling is related in some way to the magnitude of CO2-caused warming at the surface.”
You are conflating determination of cause with determination of sensitivity.
I would add to John Reisman’s list –
“5. stratospheric cooling = put on a jacket[CO2] and you trap more heat by radiating it back to your body, thus not allowing it to escape, thus cooling above your jacket (less heat escaping)… Adding energy from a heating pad [it’s the sun, it’s natural variability] can make you just as warm as putting on a jacket, but it will warm above you, the opposite sign of the effect of a jacket.
Which means that surface warming has to be CO2, or something that traps heat in the same way. We know from isotope ratios the the additional CO2 has a fossil fuel signature, and that the rate of CO2 increase in the atmosphere is proportional to human fossil use – hence the attribution of the warming we see to human fossil fuel CO2 emissions. (Even if there is something that traps heat in the same way as CO2(right wing hot air, pixie dust), in order for it to be the reason instead of CO2, it would have to also simultaneously cancel the effect of CO2 in exact proportion. I can’t think of anything that has this behavior, and neither have the denialists – they just claim that there might be something not yet known.)
That the warming of the troposphere accompanied by cooling of the stratosphere is a signature of AGW from CO2 doesn’t mean that we can understand precisely, or predict accurately, or measure exactly the transfer function for tropospheric warming to stratospheric cooling, since there are multiple factors which contribute to the stratospheric temperature – ozone, hydroxyl radical chemistry and its interaction with methane, solar UV variability which is different from visible solar variability, and other confounding factors. Because ozone is a major player, and the ozone levels vary with the rate of chlorofluorocarbon destruction, which since the Montreal protocols have been falling, the relationship between stratospheric cooling and CO2 tropospheric sensitivity might have been different in 1980 than now. This does not affect the sensitivity of tropospheric warming to increases in CO2.
Ray Ladbury, #145:
You write,
“The [attribution] argument goes
1)Stratospheric cooling demonstrates that the greenhouse effect of CO2 is nowhere near saturated.
2)A dozen or so other independent lines of evidence demonstrate that CO2 sensitivity is roughly 3 degrees per doubling, with 90% CL between 2 and 4.5 degrees per doubling.”
So where is it said that stratospheric cooling is important because it shows that the greenhouse effect of CO2 is not saturated? I find this rather hard to believe. It has been known since the 1950s that the greenhouse effect is not “saturated”. For example, in the RealClimate post “A Saturated Gassy Argument” (Spencer Weart and Raymond Pierrehumber, 26 June 2007), I note that stratospheric cooling is not even mentioned. Instead, Dr. Weart argues that John Tyndall knew that the greenhouse effect is not saturated as early as 1862, and he then laments that scientists should have refuted the “saturation” argument of Knut Ångström in 1920s, if they had bothered to think it through.
But you are right that I am confused about the attribution argument. It says in the IPCC AR4 SPM (“Understanding and attributing climate change”, p. 18):
“Warming of the climate system has been detected in changes of surface and atmospheric temperatures in the upper several hundred metres of the ocean, and in contributions to sea level rise. Attribution studies have established anthropogenic contributions to all of these changes. The observed pattern of tropospheric warming and stratospheric cooling is very likely due to the combined influences of greenhouse gas increases and stratospheric ozone depletion. {3.2, 3.4, 9.4, 9.5}”
What is missing in the AR4 is an explanation of why these various observations are relevant.
I took this statement to mean that the “attribution studies” related to “warming of the climate system” and more broadly to “understanding and attributing climate change”. I never would have guessed that stratospheric cooling is largely irrelevant to understanding the surface warming. And I can see that others here have been confused by this too.
Finally, you say in point (2) that there are about a “dozen or so” other independent lines of evidence that constrain climate sensitivity within the IPCC likely range. Well, these independent lines of evidence are exactly what I am interested in.
Gavin has written,
“Attribution is fundamentally a modelling task, and the principal models that can be used are the coupled GCMs – at least to start with.”
Of course, it is often said that it is a “denialist myth” that anthropogenic attribution requires these GCMs. Well, I do know that Forster and Gregory (2006) attempted to use satellite observations to constrain climate sensitivity in a way that was truly independent of the GCM results. Of course, Forster and Gregory have been challenged by Lindzen and Choi (2011) who have argued that use of simple regression biases to a higher sensitivity. And I realise that Hoffert and Covey (1992), Hansen et al. 1993, and similar studies have used data from the last glacial maximum to constrain climate sensitivity, although as far as I can tell, the GCMs are still required to estimate the change in global mean temperature – so they are not truly independent of GCMs. And as the recent Schmittner et al. (2011) study has shown, there is still a lot of debate about the magnitude of the LGM cooling.
So what I am missing? What are the other nine lines of independent evidence to make up your dozen?