Nature hates straight lines

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’ ...

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Paul Loock
October 25, 2010 10:03 am

It’s unfair to use observations, measurements and causation in modern climatology. You have made the same mistake as Ferenc Miskolczi. We do not live in a world of physics, chemistry etc.. We are parts of superlinear computerprograms and nature is what you see on TV.

John Day
October 25, 2010 10:12 am

Milwaukee Bob said:
> “not exactly”? “tend to be”? Would that be like –
> your not exactly pregnant but you possibly could tend to be?
Yep, those quoted words are all well-known “weasel words”, often used to masquerade dodgy beliefs as science ….
… except when used to describe finding “ideal models” in Nature. They don’t exist. The best you can do is an N-th order approximation. Always. No exceptions. (Those are _not_ weasel words)
As proof of this, Milwaukee Bob, will now attempt to provide me with any of these solid examples (i.e. real observables) of “ideals” that can be found in Nature.
1. Two points on a sheet of paper that describe a perfect line. (IAW, how sharp is your pencil? Darn that pesky ‘noise of observation’!)
2. A perfect circle anywhere in the Universe. (Orbits of satellites? Surface of mercury blob suspended in deep space? Nope, sorry, they’re all perturbed by nearby and distant objects, i.e. by everything. Darn that pesky ‘process noise’!)
3. A ray of light as a “straight line”? Nope, it wobbles, perturbed by gravity etc.
No matter how ‘ideal’ you think your object is, _if_ it can be observed, I will find a microscope with enough magnification (down to atoms, and beyond) to find non-ideal flaws (‘noise’) in it.
We’re not talking about ‘close enough for government work’. We’re talking ‘Perfect’, with a capital pee.
:-]

October 25, 2010 10:24 am

mRE says:
“Um, crystals have perfectly straight lines, and absolutely precise angles.”
As Willis constantly reminds everyone: don’t assume; quote what he wrote.
Willis wrote: “Very little in nature is linear, particularly in complex systems.” [my emphasis]
Crystals are not complex systems.

George E. Smith
October 25, 2010 10:25 am

“”” mRE says:
October 25, 2010 at 9:47 am
Um, crystals have perfectly straight lines, and absolutely precise angles. “””
No they don’t !! you’ve obviously never grown a crystal.
Every crystal ever grown; even including hypothetically perfect crystals; none of which have ever been grown; has had a finite size; there simply isn’t enough matter in the unvierse to grow an infinite size crystal. So all crystals have a boundary where each and every crystal “plane” or “line” must teminate.
Beyond that boundary; there are no atoms or molecules of the “crystal”; just a vaccuum or air or whatever.
So the interatomic forces between adjacent atoms/molecules, cease to exist beyond the boundaries of the crystal; so the interratomic distances will be different near the boundary than they are internally in the crystal so the lines cannot be straight nor the planes flat; even everywhere they exist. oh I nearly forgot; that most crystals are not a zero kelvin Temepratures; so they all ahve random atomic motions all the time; so they never all actually lie on a plane or a straight line.
Save your breath; EVERY single concept that we introduce or discuss in MATHEMATICS whether POINTS, LINES, PLANES, CIRCLES, SPHERES, is a complete fiction that we made up in our heads. Absolutely nothing in mathematics actually exists anywhere in the universe as a real object; they are all fake.
Points for example have a position only and no dimensions of any kind; Heisenberg’s principle of uncertainty says that if such a thing existed; it could have any momentum up to (but not including) infinity; so it likely would never be in our ken for long enough to ever find it. I excluded infinite momentum just to cover my A***; maybe infinite is possible in that case of a real point existence.
x^2 + y^2 + z^2 = a^2 is supposed to be a sphere IN MATHEMATICS. That equation makes no provision for 8,000 metre high mountain ranges on its surface. We may have approximations to some of the fictional items of mathematics; in the real universe; which after all is why we invented the fictional ones; but our mathematical prestidigitations with those fictional elements can only approximate the actual behavior of any part of the real universe; although it could exactly explain the behavior of one of our equally ficticious models of some portion of the universe.
The trick is to construct better models that replicate the real behavior of the universe more accurately. but we can never describe the real universe in mathematics; only a model of it.

Colin from Mission B.C.
October 25, 2010 10:42 am

Charlie A says:
October 25, 2010 at 8:27 am
The global average temp indeed is not an accurate depiction of the temperature anywhere on the globe, but it is still a useful metric.
~~~
Why? How?
Proponents of CAGW assume this statement to be true, a priori. But, I’m not convinced it is. To me, a global average temperatures is like a global average phone number. Interesting…maybe…but useful? Hardly.
And, I’m not even going to get into the issues of accuracy (or lack thereof) of measuring average temperature (see surfacestations.org).

James Evans
October 25, 2010 10:50 am

Willis,
If you’re going to spend the entire first paragraph of your post defending your headline, then why not just use a different headline?

tryfan
October 25, 2010 10:55 am

Hmmm… This seems to more of a semantic problem. Isn’t the whole concept of linearity a metaphore, except in pure mathematics? It’s usable to explain stuff, but doesn’t exist in the real world.
You don’t convince me this time, Willis.

Bob Layson
October 25, 2010 10:57 am

The chief purpose in seeking ”the” global average temperature is to have something that needs fixing and to have someone or something to blame it on.
Would the global average temperature be experienced at the average latitude and longitude?

October 25, 2010 10:59 am

George E. Smith says:
October 25, 2010 at 10:03 am (Edit)
So how does the IPCC protestation of a LINEAR relationship jibe with the climatists claim of a LOGARITHMIC relationship ?
George,
they do NOT claim a linear relationship. They argue that if you have 2 forcings (for example)
1. Solar
2. Aerosol
And you want to estimate the response to both you can combine them by summing.
read what they wrote. they wrote that you can combine indpendent RF (radiative forcings) by adding them.

Tom
October 25, 2010 11:21 am

So how does the IPCC protestation of a LINEAR relationship jibe with the climatists claim of a LOGARITHMIC relationship ?

Well, if you scroll up to the next post on the blog, you’ll see it:
dF = 5.35 ln (C/C0)
dT = S dF
Radiative forcing is a logarithmic function of CO2 concentration. Temperature change is a linear function of radiative forcing.
But since you take both sides of this debate here, it’s tempting to think you’re just trying to stir up trouble.

Editor
October 25, 2010 11:27 am

Slightly O/T, but as an oddball fact, New Zealand sits astride what is regarded as the longest natural straight line in the world, clearly visible for space – the Great Fault spanning both North and South Island
Nature ain’t all bad
Andy

October 25, 2010 11:28 am

John Day.
yes, Willis missed this one badly.
First, The IPCC in this section is discussing the following:
“The TAR and other assessments have concluded that RF is a useful tool for estimating, to a first order, the relative global climate impacts of differing climate change mechanisms (Ramaswamy et al., 2001; Jacob et al., 2005). In particular, RF can be used to estimate the relative equilibrium globally averaged surface temperature change due to different forcing agents. However, RF is not a measure of other aspects of climate change or the role of emissions (see Sections 2.2 and 2.10). Previous GCM studies have indicated that the climate sensitivity parameter was more or less constant (varying by less than 25%) between mechanisms (Ramaswamy et al., 2001; Chipperfield et al., 2003). However, this level of agreement was found not to hold for certain mechanisms such as ozone changes at some altitudes and changes in absorbing aerosol. Because the climate responses, and in particular the equilibrium climate sensitivities, exhibited by GCMs vary by much more than 25% (see Section 9.6), Ramaswamy et al. (2001) and Jacob et al. (2005) concluded that RF is the most simple and straightforward measure for the quantitative assessment of climate change mechanisms, especially for the LLGHGs. This section discusses the several studies since the TAR that have examined the relationship between RF and climate response. Note that this assessment is entirely based on climate model simulations.”
So you have a variety of forcings. Nothing is said about a linear relationship.
Continuing:
“Each RF agent has a unique spatial pattern (see, e.g., Figure 6.7 in Ramaswamy et al., 2001). When combining RF agents it is not just the global mean RF that needs to be considered. For example, even with a net global mean RF of zero, significant regional RFs can be present and these can affect the global mean temperature response (see Section 2.8.5). Spatial patterns of RF also affect the pattern of climate response. However, note that, to first order, very different RF patterns can have similar patterns of surface temperature response and the location of maximum RF is rarely coincident with the location of maximum response (Boer and Yu, 2003b). Identification of different patterns of response is particularly important for attributing past climate change to particular mechanisms, and is also important for the prediction of regional patterns of future climate change. This chapter employs RF as the method for ranking the effect of a forcing agent on the equilibrium global temperature change, and only this aspect of the forcing-response relationship is discussed. However, patterns of RF are presented as a diagnostic in Section 2.9.5.”
THEN they discuss how the various forcings can be “combined”
“Reporting findings from several studies, the TAR concluded that responses to individual RFs could be linearly added to gauge the global mean response, but not necessarily the regional response (Ramaswamy et al., 2001). Since then, studies with several equilibrium and/or transient integrations of several different GCMs have found no evidence of any nonlinearity for changes in greenhouse gases and sulphate aerosol (Boer and Yu, 2003b; Gillett et al., 2004; Matthews et al., 2004; Meehl et al., 2004). Two of these studies also examined realistic changes in many other forcing agents without finding evidence of a nonlinear response (Meehl et al., 2004;
Matthews et al., 2004).”
And if you take the time to actually READ some of the papers cited you will see what they did in the experiements
http://www.cccma.ec.gc.ca/papers/gboer/PDF/CliDyn_sens_response.pdf
section 9, additivity and sensitivity.
Its also good for people to get a sense of the time constants involved.
Further, folks need to read on from the section that willis quoted to understand more of the problem
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch2s2-8-5.html
the biggest thing he failed to point out was the efficacy, and you will note that efficacies are important because of the non linearities
“Since the TAR, several GCM studies have calculated efficacies and a general understanding is beginning to emerge as to how and why efficacies vary between mechanisms. The initial climate state, and the sign and magnitude of the RF have less importance but can still affect efficacy (Boer and Yu, 2003a; Joshi et al., 2003; Hansen et al., 2005). These studies have also developed useful conceptual models to help explain variations in efficacy with forcing mechanism. The efficacy primarily depends on the spatial structure of the forcings and the way they project onto the various different feedback mechanisms (Boer and Yu, 2003b). Therefore, different patterns of RF and any nonlinearities in the forcing response relationship affects the efficacy (Boer and Yu, 2003b; Joshi et al., 2003; Hansen et al., 2005; Stuber et al., 2005; Sokolov, 2006). Many of the studies presented in Figure 2.19 find that both the geographical and vertical distribution of the forcing can have the most significant effect on efficacy (in particular see Boer and Yu, 2003b; Joshi et al., 2003; Stuber et al., 2005; Sokolov, 2006). Nearly all studies that examine it find that high-latitude forcings have higher efficacies than tropical forcings. Efficacy has also been shown to vary with the vertical distribution of an applied forcing (Hansen et al., 1997; Christiansen, 1999; Joshi et al., 2003; Cook and Highwood, 2004; Roberts and Jones, 2004; Forster and Joshi, 2005; Stuber et al., 2005; Sokolov, 2006). Forcings that predominately affect the upper troposphere are often found to have smaller efficacies compared to those that affect the surface. However, this is not ubiquitous as climate feedbacks (such as cloud and water vapour) will depend on the static stability of the troposphere and hence the sign of the temperature change in the upper troposphere (Govindasamy et al., 2001b; Joshi et al., 2003; Sokolov, 2006).
In short. when the IPCC talks about combining the forcings LINEARLY, they are not saying that the responses to forcing are linear. they are saying that the forcings can be SUMMED. linearly combined.
AND its important to understand why they say this is a “useful” approach.
basically, if you have a list of forcings ( we’ve all seen the charts) you want to know if you can simply add them together.

stumpy
October 25, 2010 11:37 am

What the IPCC should have simply said is:
“We have a high level of confidence that our models assume a linear response”
and their justification:
“we have no idea what happens in the real world (reality), its full of tricky things we dont quite understand (like clouds for example) which confuse everything, and to understand it all would be too hard and timely given the current timescale, so we prefer to use an assumption (also known as a model) so we can progress on, otherwise it will be too late for our children as we need to act now (assuming our assumption is correct)”
Que footage of dead polar bears, images of calving ice etc….

October 25, 2010 11:41 am

Smokey says: “mRE says:
“Um, crystals have perfectly straight lines, and absolutely precise angles.”
As Willis constantly reminds everyone: don’t assume; quote what he wrote.
Willis wrote: “Very little in nature is linear, particularly in complex systems.” [my emphasis]
Crystals are not complex systems.”
And, actually, crystals are not so perfect as this guy seems to think. It is in fact typical for crystals in the real world to have irregularities and defects. And beyond that, if the position of the constituent particles of a crystal were all so predictably, perfectly arranged, they they would have to have very poorly defined momenta, by the uncertainty principle, so their velocities could be just about anything you can imagine-clearly such uncertainty in the amount of particle motion, would not make much sense for a solid object. If we conversely say that it’s a solid, so the velocities of the particles must be all very low, then we are saying that we can’t define the position of the particles precisely-how can one say that the particles are arranged in a specific, precise way with respect to one another, if the particles don’t even have well defined positions?
On the quantum level, all matter is “fuzzy” and not neat and exact in shape.

GaryW
October 25, 2010 11:45 am

John Day, (October 25, 2010 at 4:35 am)
There are no ‘model free’ _measurements_ of Nature!!!
What ‘model’ do you ‘consult’ to get your local time and temperature?
“I don’t use a model, I just look at my watch and the thermometer in my patio!”
Ha! You’ve just consulted two ‘models’!

I was going to let this one slide but it just kept bugging me. You have presented an interesting inclusion to the definition of a model. To an engineer, the watch and the thermometer are calibrated measurement instruments. In both cases, a single physical quantity is measured in real time and read out directly. In the case of the clock, counting the vibrations of a mechanical element such as a quarts or ceramic crystal. The thermometer is using the change in volume of a material, calibrated to known temperature values, to display temperature.
A model is generally expected to be some sort or representation of object, event, or series of events. Model and measurement are not what I, and I believe most people, would consider to be synonymous concepts.

John Day
October 25, 2010 11:56 am

> yes, Willis missed this one badly.
Nothing enhances the credibility of an argument better than than realizing and admitting an occasional error.
I must confess that there _is_ something that is more rare than a Perfect Circle or Line in Nature.
It is the “One-Sided, Science-is-Settled Argument”, that our AGW friends have been pandering for many years. It doesn’t exist, not even close.
😐

Bill Illis
October 25, 2010 12:04 pm

Tom says:
October 25, 2010 at 11:21 am
dF = 5.35 ln (C/C0)
dT = S dF
Radiative forcing is a logarithmic function of CO2 concentration. Temperature change is a linear function of radiative forcing.
————————
How many Watts/m2 is required on Sun’s surface to increase its temperature by 1.0C?
= +50,000 W/m2
How many Watts/m2 is required on Earth’s surface to increase its temperature by 1.0C?
= +5 W/m2
I don’t know how much more non-linear a phenomenon can get.
The temperature does not change linearly with the forcing.

John Day
October 25, 2010 12:17 pm

GaryW:
>calibrated measurement instruments … single physical quantity is measured in real time and read out directly.
In the mathematics of modeling, an ‘oracle’ is such an ‘ideal’ device. An oracle can read out true values without error or interpretation. Unfortunately, oracles are fictitious entities, invented solely for the sake of argument or elaborating a proof. They don’t exist in the real world.
Every measurement tool employs a model, subject to errors of implementation and interpretation.
For example, a yardstick measures extension in one dimension.
What if the markings are incorrectly applied? What if you mistook a ‘5’ for a ‘2’? Then you’ve introduced some errors into your measurements.
What if you haven’t noticed these errors? Then there is uncertainty in all the measurements made, past and future, caused by a faulty ‘model’.
The good news is that most of these instruments (note weaseling) are so reliable that we don’t worry about them. It’s the ‘clocks’ and ‘thermometers’ used for climate modeling that we should be concerned about.
😐

JAE
October 25, 2010 12:22 pm

A warmer-guy might counter that: “there is an approximate linear relationship between forcing and sensitivity for small changes in forcing.” No?

October 25, 2010 1:00 pm

I skipped half the comments, sorry if this has been said.
Folks, this isn’t a science document, it is a document designed to make a business case. Read it like a business case, and as with any business case, keep carefull track of what they SAY and what they IMPLY and also keep carefull track of what specificaly they are referring to when the say and/or imply it.
If you read carefully the quote in Willis’ post, it doesn’t SAY response it linear. It says there’s no reason not to believe it is. Two different things. Further, referring to what? In this case they seem to be referring to a response at a given point to a forcing at that point being linear. For changes of on the order of a degree, that is a reasonable approximation. BUT:
Read the details. In 2.8.1 of the same section of AR4 WG1 you will find this quote:
” It should be noted that a perturbation to the surface energy budget involves sensible and latent heat fluxes besides solar and longwave irradiance; therefore, it can quantitatively be very different from the RF, which is calculated at the tropopause, and thus is not representative of the energy balance perturbation to the surface-troposphere (climate) system. While the surface forcing adds to the overall description of the total perturbation brought about by an agent, the RF and surface forcing should not be directly compared…”
That statement pretty much says that response to RF is NOT linear at surface. But pay attention to what they are referring to.
In 2.8.1 they are explaining that they measure forcing and (I presume) calculate sensitivity AT THE TROPOPAUSE. The temperature of the tropopause being the “effective” black body temperature of the earth, some 35 degrees colder than the surface, there is not a linear relationship in regard to forcing as it affects the tropopause versus the surface. And they said so. Let’s now put both statemtents in context.
The IPCC states that climate sensitivity at the tropopause to the doubling of CO2 is 3.7 w/m2 = 1 degree increase in temperature on a global scale. They IMPLY that surface response is linear, but to what? By their own statement in 2.8.1, it is NOT directly correlated to RF, even though it is IMPLIED (no reason not to in their words) that surface response is linear. Which, to a given forcing AT THE SURFACE it approximately is, but NOT to the climate sensitivity of of the system as a whole, which they measure at the tropopause.
So, the CO2 doubling = 3.7 w/m2 = 1 degree is IMPLIED to mean “at surface” but in fact means “at tropopause” and will yield a DIFFERENT number at surface. Based on Stefan Boltzman, an increase of 1 degree at the tropopause, where it is about -20C, would require an RF of exactly 3.7 w/m2. At surface, at an average of +15C, it would require 5.5 w/m2. The 3.7w/m2 translates to a “system” change as seen from space of 1 degree, but a surface change of only (mental math approximation mine) of .6 degrees.
By extention, with feedbacks included, the sensitivity at tropopause is 2 to 4.5 degrees, which at surface would be 1.2 to 3 degrees. FURTHER, there is no such thing as a freakin average at earth surface. The higher latitudes are colder and so have a HIGHER sensitivity to a given forcing than the warmer latitudes (Stefan Boltzman) The colder seasons have a higher sensitivity to a given forcing than the warmer seasons (Stefan Boltzman). Night time (cooler) temps have a higher sensitivity to a given forcing than day time (warmer) temps (Stefan Bolzman).
Any attempt to interpret a forcing at the tropopause to a linear response at surface is, therefore, ludicrous. As per what they SAY in 2.8.1, it is not. As per what they IMPLY, we should see temps increase by 2 to 4.5 degrees for CO2 doubling. But they only IMPLY this, and the complexity of the report combined with the vagueness in the manner it is written regarding what statement refers to what issue (the hallmark of a business document designed to mislead) makes it difficult discerne.
But the surface response they claim is, according to them, less than the sensitivity they claim.

It's always Marcia, Marcia
October 25, 2010 1:14 pm

When you are sitting at a desk doing math you can have things be linear. When you get up and walk away from the desk into the real word you can forget hopes of things being linear.
Everything is complex. We barely know anything about everything.