Guest Post by Willis Eschenbach
Yeah, I know Nature doesn’t have human emotions, give me a break. I’m aware it is unscientific and dare I call it atavistic and perhaps even socially unseemly to say Nature “hates” straight lines, but hey, it’s a headline, cut me some poetic slack.
My point is, everyone is aware that nature doesn’t deal in straight lines. Natural things move in fits and starts along complex paths, not straight from point to point. Phenomena have thresholds and edges, not slow linear changes at the perimeter. Tree branches and coastlines are jagged and bent. Things move in arcs and circles, relationships are complex and cyclical. Very little in nature is linear, particularly in complex systems.
Forcing is generally taken to mean downward radiation measured at the TOA (top of atmosphere). The IPCC says that when TOA forcing changes, the surface temperature changes linearly with that TOA forcing change. If there is twice the forcing change (twice the change in solar radiation, for example), the IPCC says we’ll see twice the temperature change. The proportionality constant (not a variable but a constant) that the IPCC says linearly relates temperature and TOA forcing is called the “climate sensitivity”.
Figure 1. Photo of impending change in climate sensitivity.
Today I stumbled across the IPCC justification of this linearity assumption. This is the basis of their claim of the existence of a constant called “climate sensitivity”. I quote it below.
I’ve removed the references and broken it into paragraphs it for easy reading. The references are in the original cited above. I reproduce all of the text on the web page. This is their entire justification for the linearity assumption. Having solved linearity in a few sentences, they then proceed to other matters. Here is their entire scientific justification for the assumption of linearity between forcing and temperature change (emphasis mine):
Linearity of the Forcing-Response Relationship
Reporting findings from several studies, the TAR [IPCC Third Assessment Report] concluded that responses to individual RFs [Radiative Forcings] could be linearly added to gauge the global mean response, but not necessarily the regional response.
Since then, studies with several equilibrium and/or transient integrations of several different GCMs [Global Climate Models] have found no evidence of any nonlinearity for changes in greenhouse gases and sulphate aerosol. Two of these studies also examined realistic changes in many other forcing agents without finding evidence of a nonlinear response.
In all four studies, even the regional changes typically added linearly. However, Meehl et al observed that neither precipitation changes nor all regional temperature changes were linearly additive. This linear relationship also breaks down for global mean temperatures when aerosol-cloud interactions beyond the cloud albedo RF are included in GCMs. Studies that include these effects modify clouds in their models, producing an additional radiative imbalance.
Rotstayn and Penner (2001) found that if these aerosol-cloud effects are accounted for as additional forcing terms, the inference of linearity can be restored. Studies also find nonlinearities for large negative RFs, where static stability changes in the upper troposphere affect the climate feedback (e.g., Hansen et al., 2005).
For the magnitude and range of realistic RFs discussed in this chapter, and excluding cloud-aerosol interaction effects, there is high confidence in a linear relationship between global mean RF [radiative forcing] and global mean surface temperature response.
Now, what strikes you as odd about that explanation of the scientific basis for their claim of linearity?
Before I discuss the oddity of that IPCC explanation, a short recap regarding climate sensitivity. I have held elsewhere that climate sensitivity changes with temperature. I will repeat the example I used to show how climate sensitivity goes down as temperature rises. This can be seen clearly in the tropics.
In the morning the tropical ocean and land is cool, and the skies are clear. As a result, the surface warms rapidly with increasing solar radiation. Climate sensitivity (which is the amount of temperature change for a given change in forcing) is high. High sensitivity, in other words, means that small changes in solar forcing make large changes in surface temperature.
By late morning, the surface has warmed significantly. As a result of the rising temperature, cumulus clouds start to form. They block some of the sun. After that, despite increasing solar forcing, the surface does not warm as fast as before. In other words, climate sensitivity is lower.
In the afternoon, with continued surface warming, thunderstorms start to form. These bring cool air and cool rain from aloft, and move warm air from the surface aloft. They cool the surface in those and a number of other ways. Since thunderstorms are generated in response to rising temperatures, further temperature increases are quickly countered by increasing numbers of thunderstorms. This brings climate sensitivity near to zero.
Finally, thunderstorms have a unique ability. They can drive the surface temperature underneath them below the temperature at which the thunderstorm formed. In this case, we have local areas of negative climate sensitivity – the solar forcing can be increasing while the surface is cooling.
As you can see, in the real world the temperature cannot be calculated as some mythical constant “climate sensitivity” times the forcing change. Sensitivity goes down as temperature goes up in the tropics, the area where the majority of solar energy enters our climate system.
So the IPCC claim of linearity, of the imagined slavish response of surface temperature to a given change in TOA forcing, goes against our daily experience.
Let me now return to the question I posed earlier. I asked above what struck you as odd about the IPCC explanation of their claim of linearity regarding forcing and temperature. It’s not the fact that they think it is linear and I disagree. That is not noteworthy.
Here’s what made me stand back and genuflect in awe of their claims. Perhaps I missed it, but I didn’t see a single word about real world observations in that entire (and most important) justification for one of their core positions.
I didn’t see anyone referenced who said something like ‘We measured solar radiation and downwelling longwave radiation and temperature at this location, and guess what? Temperatures changed linearly with the changes in radiation.’ I didn’t see anything at all like that, you know, actual scientific observations that support linearity.
Instead, their claim seems to rest on the studies showing that scientists looked at four different climate models, and in each and every one of the models the temperature change was linearly related to forcing changes. And in addition, another model found the same thing, so the issue is settled to a “high confidence” …
I gotta confess, that wasn’t the first time I’ve walked away from the IPCC Report shaking my head, but that one deserves some kind of prize or award for sheer audacity of their logic. Not a prize for the fact that they think the relationship is linear when Nature nature hates straight lines, that’s understandable, it’s the IPCC after all.
It is the logic of their argument that left me stammering.
Of course the model results are linear. The models are linear. They don’t contain non-linear mechanisms. And of course, if you look at the results of linear models, you will conclude with “high confidence” that there is a linear relationship between forcing and temperature. They looked into five of them, and case closed.
I mean, you really gotta admire these guys. They are so far into their models that they actually are using the linearity of the model results to justify the assumption of linearity embodied in those same models … breathtaking.
I mean, I approve of people pulling themselves up by their own bootstraps, but that was too twisted for me. The circularity of their logic made my neck ache. I kept looking over my shoulder to see if the other end of their syllogism was circling behind to strike me again. That’s why I genuflected in awe. I was overcome by the sheer beauty of using a circular argument to claim that Nature moves in straight lines … those guys are artists.
Meanwhile, back in the real world, almost no such linear relationships exist. Nature constantly runs at the edge of turbulence, with no linearity in sight. As my example above shows, the climate sensitivity changes with the temperature.
And even that change in tropical climate sensitivity with temperature is not linear. It has two distinct thresholds. One is at the temperature where the cumulus start to form. The other is at the slightly higher temperature where the thunderstorms start to form. At each of these thresholds there is an abrupt change in the climate sensitivity. It is nowhere near linear.
Like other natural flow systems, the climate is constantly restructuring to run “as fast as it can.” In other words, it runs at the edge of turbulence, “up against the stops” for any given combination of conditions. In the case of the tropics, the “stops” that prevents overheating is the rapid proliferation of thunderstorms. These form rapidly in response to only a slight temperature rise above the temperature threshold where the first thunderstorm forms. Above that threshold, most of any increase in the incoming energy is being evaporated and used to pump massive amounts of warm air through protected tubes to the upper troposphere, cooling the surface. Above the thunderstorm threshold temperature, little additional radiation energy goes into warming the surface. It goes into evaporation and vertical movement. This means that the climate sensitivity is near zero.
Now it is tempting to argue that the IPCC linearity claim is true because it only applies to a global average temperature. The IPCC only formally say that there is “a linear relationship between global mean RF [radiative forcing] and global mean surface temperature response.” So it might be argued that the relationship is linear for the global average situation.
But the average of non-linear data is almost always non-linear. Since daily forcing and temperature vary non-linearly, there is no reason to think that real-world global averages vary linearly. The real-world global average is an average of days during which climate sensitivity varies with temperature. And the average of such temperature-sensitive records is perforce temperature sensitive itself. No way around it.
The IPCC argument, that temperature is linearly related to forcing, is at the heart of their claims and their models. I have shown elsewhere that in other complex systems, such an assumed linearity of forcing and response does not exist.
Given the centrality of the claim to their results and to the very models themselves, I think that something more than ‘we found linearity in every model we examined” is necessary to substantiate this most important claim of linearity. And given the general lack of linearity in complex natural systems, I would say that their claim of linearity is an extraordinary claim that requires extraordinary evidence.
At a minimum, I think we can say with “high confidence” that it is a claim that requires something more weighty than ‘the models told me so’ ...

MarkR says:
October 26, 2010 at 6:06 am (Edit)
Clear at dawn. Clouding up before noon. Thunderstorms in the afternoon. Progressively clearing at night.
The hourly change in climate sensitivity that I have described occurs all over the tropics. That’s not “one point” as in your example. The tropics are 40% of the planet. More importantly, it is the hot end of the planet-sized heat engine we call the climate. What happens in the tropics is central to the heat balance of the planet. So your example of heating one square km. fails because it is not a parallel situation.
Also, the average of a non-linear variable contains the non-linearity. The maximum daily temperature in the tropics occurs in the mid-afternoon, at a time of minimum climate sensitivity.
The minimum daily temperature, on the other hand, occurs typically towards or just after dawn, long after the daytime clouds have dissipated. With clear skies, the entire surface can radiate more strongly to space. Temperatures are lower, so less energy is going into evaporation and more is going into raising the ocean temperature. So at that time, climate sensitivity is high.
So despite the fact that we are dealing with averages, the averages act differently. Actually, that should provide a possible test of the theory. If I can find sufficient data I’ll report back with some results.
Onwards …
George E. Smith says:
October 26, 2010 at 3:12 pm
You are very much correct.
Science has been very sloppy and complacent with just generalizing and not looking for absolute accuracy.
I have a design for power generation that engineers have no problem to say that it will run. Now add a physics design on efficiency and the engineer admitted it was beyond his area to even speculate and it would have to go to a University and would probably take years to understand the motion physics I had discovered and the designs of how this new physics can very easily be recreated.
I have yet to find that University.
The Modellers
http://www.climateaudit.org/?p=2565#comments
Chapter 1 of AR4 has some surprisingly interesting comments about models that, to the extent that the points are disclosed in the body chapters, are disclosed so opaquely that they would be undecipherable to anyone other than a few. Here are some interesting comments about flux adjustment – an issue that must surely raise civilian eyebrows. A “flux adjustment” in a GCM is defined below as an “empirical correction that could not be justified on physical principles” i.e. a fudge factor, and one of the accomplishments of recent GCMs has been to apparently get past that. AR4:
[…]
Demesure says: January 7th, 2008 at 1:17 am
For the French non flux-ajusted model LMD/ISPL (team of Hervé le Treut, lead Author of Chapter 1 of WG1 AR4), here is the archive http://web.lmd.jussieu.fr/~lmdz/LMDZ-info/ of internal correspondances between modellers.
It seems they have divergence problems of their own, for example some quite “funny” and illustrative translations in this letter: http://web.lmd.jussieu.fr/~lmdz/CRs/LMDZ/CR17012002
– “Olivier has mentionned the problem of snow accumulation reaching several km must be resolved”
– “Flux comparisons between top and bottom atmosphere show a discrepancy of about a dozen W/m2, it’s too much”
– “Zonal means show a big cold biais (5 to 15°C) at the tropopause”
eadler says:
October 26, 2010 at 9:45 am
What has been shown using this procedure is that climate sensitivity calculated from models are in the same range as climate sensitivity deduced from paleo data.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.172.3264&rep=rep1&type=pdf
Climate sensitivity estimated from ensemble simulations
of glacial climate
————————–
I imagine you realize this paper is just like all the other climate model simulations of the ice ages. Not a single one outlines what Albedo they used for all that extra glacier and sea ice. In fact, it is very telling that they do not outline the single most important factor in why temperatures fell so much in the ice ages.
This paper is just as useless as all the other ones using a climate model when the biggest key assumptions used are not outlined. In fact, I am tired of reading them looking for the key assumptions to be outlined properly – they never are. Throw this one into the pile marked “another climate paper that does not use objective data – it says whatever the author wanted it to say.” That pile will be the biggest one in your office so you don’t have to search for it.
As far as I can tell, it is possible to replace any curve with a straight line tangent section as long as you make sure to limit the scope of your results to the narrow range on that curve where tangency applies with reasonable accuracy.
The problem I see here is that technical limitation tends to get lost in translation, especially as written up by the popular press and the linear approximation that may be valid over a temperature range of five or ten degrees may be promulgated as a universal relationship.
Willis Eschenbach says:
October 26, 2010 at 5:35 pm
I think I am falling in love with your specificity on sensivity, large cognitive bias though ….. tropics gal.
Looking forward to next post.
Bill Illis says:
October 26, 2010 at 7:38 pm
Please endnote that pile for future use
Spector says:
October 27, 2010 at 12:35 am
Check out what software the journalists have had supplied in the past few years- maybe they couldn’t publish curves and went for the headers with the quickest graphics?
Willis: Let’s think more deeply about your tropical thunderstorms. Do they always begin to limit warming when surface temperature (2 m) rises to a fixed (or roughly fixed) temperature? No. Rapid convection begins to limit warming only when radiative cooling can no longer prevent surface temperature from exceeding the lapse rate. At this point, the cooling that occurs from expansion in a region of rising air leaves that air less dense that air above it, and the region of air can continue to rise to the tropopause. So your tropical thunderstorms limit surface warming ONLY when air higher in the tropics is cool enough to make the temperature gradient from the surface to the upper atmosphere is steep enough. Unfortunately, thunderstorms themselves warm the upper atmosphere and reduce this temperature gradient. So you have told us only part of the story: thunderstorms limit surface temperature rise, but also warm the upper atmosphere and turn themselves off! By this mechanism, convection produces a lapse rate that is roughly the same most locations in the troposphere. (One major exception is that at night the ground cools faster than the air and this cools air near the surface faster than air higher in the atmosphere.)
If anthropogenic GHGs and water vapor warm the upper atmosphere, tropical thunderstorms aren’t going to limit surface temperature rise until that surface temperature has risen to a higher temperature than before.
Frank says:
October 27, 2010 at 11:13 am
Well, yeah, kinda. Thunderstorms are first dependent on the formation of cumulus clouds. These depend upon the temperature differential between the surface and the level where condensation occurs (the “LCL”, or lifting condensation level).
However, where condensation and freezing are occurring in the clouds, energy is being released. It is this secondary energy, released by condensation and freezing, that drives the vertical circulation from the LCL to the upper atmosphere.
From there, the energy is free to radiate to space, or to be moved polewards. Because the tropical upper atmosphere is constantly radiating and moving polewards, the upper atmosphere does not warm.
Thunderstorms are huge heat engines that turn heat into mechanical work. The work that they do is to pump the working fluid (an air-water mixture) vertically and thus (eventually) poleward.
In such a situation, the speed at which the pump turns is the major variable. The energy is passing through the situation. Warm moist air starts at the tropical surface and is pumped vertically and hence polewards. There is no static “upper atmosphere” to be warmed. Instead, air in the upper atmosphere is constantly being added to and replaced. Thunderstorms are bringing air directly from the surface. The temperature can remain nearly the same, while larger masses of air are moved and a huge amount of work is done.
MFer! I just did about ½hr. typing (while “logged in” as usual, and got an error screen saying name and email required — with the loss of the entire entry (no, back page didn’t help). The name and email fields were not displayed. Had to log out and back in to get them. >:( WUWT??
[Reply: It’s a terrible WordPress glitch. Please let them know about it. ~dbs]
Abbreviated version:
Willis;
IIRC, it was recently a surprise (re-)discovery that the stratosphere is cooling, and its H2O rising.
There is also the notorious Un-Hot Spot in the tropical troposphere which was hand-waved (-swatted?) away with the remarkable logic that since one radiosonde thermometer could err, so could hundreds (in unity, in the same direction), so therefore since the Hot Spot might not be missing we’ll just assume it isn’t . Oof!
_______
Reading the above comments inspires me to suggest a Granularity Gauge Number, to be (rule-)assigned to every formula and data set, specifying the range of precision and measurement and the scope of applicability. “It wad frae monie a blunder free us,
An’ foolish notion.”
The “uncertainty” measures now in use don’t seem to be up to the job, judging from the results and such comments as Jones’ expert assessment of 90% confidence he was entirely correct — good enough for government work.
[Reply: It’s a terrible WordPress glitch. Please let them know about it. ~dbs]
Not to be too rude and crude, but WP is your blogware of choice. You let them know.