A Longer Look at Climate Sensitivity

Second, the sun plus the albedo were all that were necessary to make these calculations. I did not use aerosols, volcanic forcing, methane, CO2, black carbon, aerosol indirect effect, land use, snow and ice albedo, or any of the other things that the modelers claim to rule the temperature.
Surely, if you measure albedo from top of atmosphere, it comprises the net of aerosols, BC, aerosol indirect effect (clouds), land use, snow and ice, plus some other things.
Although perhaps that’s implicit in what you wrote.
BTW, you have a typo in the graphic – Observerver.

Willis..I’m reminded of the time I was given a paper on a variational method in transient heat transfer…with the 1/4 of the semester grade contingient upon elucidating the method shown in the 4 page paper…and then applying it to a “sample” problem.
I walked in to my “night” in the graduate heat transfer course, and started with the 38 pages of “overheads” (yes, I’m dating myself, I hate that..I have to use a mirror…)and one hour and 10 minutes later I concluded. I apologized to the professor, Dr. Lu (R.I.P.) and said, “I had all I could do to figure out what this fellow had condensed in these 4 pages…I did NOT have time to apply this method to a “sample problem”.
Dr. Lu used it as an object lesson. ‘Papers are very condensed, they oft times lack many details to truly explain the method they present.’…He went on to say, ‘They can contain valuable information, but it may take much effort to find out WHAT that information is!’..
HA! I think the same as your presentation. To really understand your method, takes more than looking at the write up for 1/2 hour, and spouting out a instant judgement based on one’s EMOTIONS rather than intellect.
I just ask that you FORMALIZE this concept in a longer and more detailed writing, perhaps a 150 page PDF, with citations!
Max

Willis Eschenbach says:
May 31, 2012 at 8:13 pm

BarryW says:
May 31, 2012 at 7:50 pm
So given the time frame of your calculation, the temperature rise and the .3 deg C per doubling for the NH, how much of the temperature rise is “attributable” to CO2?

Well, since my numbers fit the data very well with no CO2 involved, and furthermore there is no significant trend in the residuals, I’d say about zero is attributable to CO2 …
w.

Playing Devil’s Advocate, CO2 can affect the albedo, so it’s included. The theory is that an increase in temperature due to CO2 will result in increased water vapour being held in the atmosphere, which can manifest as clouds, altering the albedo.
So this model doesn’t impact on AGW concepts – it’s a much more empirical analysis of temperature based on how much energy from the input source (the sun) gets absorbed by the Earth (determined by albedo). Conceptually, straight forward and hard to refute. The next level of discussion is then to determine what impact various factors (such as CO2, aerosols, etc) have on the Earth’s albedo. It would be interesting is to see if there are any existing studies on that subject.

Willis you said …
“Not is any way, shape, or form. I cannot be strong enough in saying that this work has absolutely nothing to do with the bogus theories and claims of N&Z. It doesn’t confirm them, nor does it falsify them, it has no connection with them at any point.
If that’s not clear enough, let me know …”
It is certainly clear to me who is doing the ranting …

I agree with the conclusion, namely that:
“the climate responds to disturbances and changes in the forcing by counteracting them.”
and that it is all down to albedo variations affecting the amount of solar energy able to penetrate the oceans.
The difficulty is that cloudiness decreased during the late 20th century warming period and is now increasing with a cessation of that warming whereas Willis’s proposition requires more clouds when it is warming so that the warming is offset by the increased albedo.
That is a serious problem which must be addressed.
My solution is to propose that instead of increased cloudiness from warming such warming comes from reduced cloudiness caused by an expansion of the tropical air masses allowing more solar energy into the oceans by intensifying the subtropical high pressure cells, pushing the entire air circulation poleward to give more zonal / poleward jets and reduced cloudiness overall.
That reduction of cloudiness and consequent warming from more energy getting into the oceans is then offset by an increase in the hydrological cycle via my GLOBAL version of Willis’s own Thermostat Hypothesis whereby there is an increase of convective overturning along the ITCZ AND an intensification of cyclogenesis along the more zonal but also more vigorous mid latitude jet streams.
The thing is that such intensification of the hydrological cycle is accompanied by reduced GLOBAL cloudiness because the increased activity is compressed into smaller surface areas by the more zonal air flow configuration.
Thus more energy getting into the oceans is caused by the expanded tropical air masses with a reduction of cloudiness but the poleward shifting of the entire air circulation pattern then increases the rate of energy transfer from surface to space for a zero or near zero effect on the equilibrium temperature of the entire system.
Expansion of the tropical air masses can result either from faster energy release by the oceans OR changes in the vertical temperature profile of the atmosphere caused by variations in the mix of particles and wavelengths from the sun influencing ozone concentrations differently at different levels.
Climate variability is just a consequence of the continual interplay between the solar and oceanic influences as each of them varies in relation to the other all the time. The positions, sizes and intensities of the permanent climate zones shift about over time as part of the balancing process. All observed climate variations can be explained by that mechanism.
Changes in GHG amounts would have a similar effect but too small to measure compared to solar and oceanic variability.
The proposition of Nikolov and Zeller is relevant in that it provides a basic physical mechanism for the necessary redistribution of the surface air pressure pattern but I am aware of Willis’s disagreement on that issue which can be left for another time so as to avoid derailing this thread.

I doubt that it trivial to detect long time constants in a record where nearly all the variance is at intra annual scales. It is practically certain that Eschenbach’s method severely underestimates climate sensitivity. There are several possible ways to demonstrate this:  A sensitivity analysis. If realistic time constants are added to the analysis, do they appreciably change the results. If not, you cannot exclude them. Simulated data. If you repeat the analysis with simulated climate data from a model with known climate sensitivity is the estimate of model sensitivity underestimated. This could be done with anything from an energy balance model to a fully coupled CGM, and does not assume that the models are correct (it is axiomatic that they, like all models , are wrong but possibly useful).  You could try to reconcile your estimate of climate sensitivity with the climate changes over the last 100000 years. Is it possible to generate a glacial maximum several degrees colder than modern with so low a climate sensitivity. I predict Eschenbach will do none of these, prefering to amuse the crowd with cheap numerical tricks. If he could show a climate sensitivity with robust methods, it would be published immediately in Science.  

I’m wondering about something here. It seems to me that this model is time independent, so that you will get the same constant trend forever, and hindcasting you will also get the same constant trend in the past. Which we didn’t have.
So if you do explain the current warming, you will have to explain the previous lack of warming.
Maybe I misunderstand the model.

I said:
“Willis’s proposition requires more clouds when it is warming so that the warming is offset by the increased albedo.”
ferd berple said:
” I don’t see that anywhere in the model.”
I think it is implied by this comment from Willis:
“because the albedo changes to balance things back out.”
Furthermore the observed decrease in cloudiness during the period of a warming troposphere is also contrary to AGW theory. More warmth is supposed to give more evaporation and more clouds which is said to be a positive feedback despite any increase in global albedo.
In reality the troposphere warms when clouds decrease and cools when clouds increase. However I would argue that system energy content remains almost exactly the same because by far the vast majority of energy in the Earth system is in the oceans and the temperature of the troposphere as a whole is related primarily to the rate of flow of energy through it between oceans and space.

“What I’ve done is hindcasting, because from the past albedo and the sun’s annual variations I’ve hindcasted past temperatures, with a very good degree of accuracy.”
That is very important.
It follows that if one could accurately measure changing global albedo from whatever reason one could assess whether energy input to the oceans is increasing or decreasing at any given time.
At some stage it should then be possible to ascertain the level of albedo that represents a stable system.
Then, linking climate zone positioning to albedo level as modified by ocean cycles would give a reasonable method of anticipating regional climate changes.
Currently, I observe increasing cloudiness, greater jetstream meridionality and cooling mid latitudes with a slight equatorward drift of the climate zones.

Too bad I don’t have time now to study this in detail, it looks really, really interesting. I’d have one suggestion though – what about instead of dividing the earth to two hemispheres, dividing it to sea and land? Different sensitivities for land and sea make a bit more physical sense than different sensitivities for two hemispheres.

Willis, I can’t comment on the formula other than that it has a delightfully convincing clarity.
As a child and country bumpkin I was always being told that nature abhors a vacuum. Not in the Aristotle sense but as a metaphor for the fact that nature always seemed to rebalance itself in the countryside around us. I’m a fan of yourThermostat Hypothesis as illustrated by tropical cloud formation. I like the idea that the climate contains homeostatic mechanisms.
The first thing I noticed in this and your previous post was that the time span, 1984 to 1998, was the same as the test case for your theory that “changes in albedo help regulate the temperature and keep it within a narrow range”, using the eruption of Pinutabo. I was suprised that only one comment in the first thread mentioned Pinutabo.
Like many others I considered this latest formula an addition to your Thermostat Hypothesis as neatly explained in an earlier post:
http://wattsupwiththat.com/2009/06/14/the-thermostat-hypothesis/
If “climate scientists” were truly open to new ideas they would be very excited by a hypothesis which demonstrates that carbon dioxide from fossil fuels will not make the planet uninhabitable even though it might bring an end to grant money burning holes in their pockets.

Ok, so I’m a little confused – on the one hand, a short term analysis clearly shows that a simple model can replicate observations but Willis seemingly accepts this is not going to demonstrate how ice ages occur, i.e. climate sensitivity over longer timescales.
Either the climate and our available data is ‘isolated’ into the now familiar cycles, and is chopped up for analysis ‘within’ those cycles – OR, the climate is taken as one big fecking cycle (i.e. ice age+ scale) with sub-cycles within and we ‘look’ at the whole thing. This seems to be the way of some of the thinking – but I feel it is wrong, the subcycles are the things to concentrate on in respect of anthropogenic influences as it is reasonable to assume that if there is a significant anthropogenic influence it will be evident within any sub-cycle? – i.e. whether the temps are going up or down, if they are going up, the AGW effect will increase the rate, if they are going down, the AGW effect will decrease the rate.
I think what Willis has done is demonstrate that short term cycles are easily replicated with a simple model but as others have commented, this is of no real ‘use’ if there are ‘other’ effects which the model does not and cannot consider.
I agree with Willis that his work appears to demonstrate a ‘low’ overall sensitivity (but only over the short timescale) and to me, this low sensitivity is reasonably logical. However, we KNOW that something(s) MUST happen to cause the KNOWN greater range in temperatures and these
something(s) must kick the sensitivity up (or down) as they occur.
I am sure folk here understand the +ve and -ve feedback analogies using a concave or convex surface respectively? (I trust I don’t need to explain this!) but the way to think of the whole climate might be to think of a rippled bowl, with crests and troughs circular and radiating out from the centre.
If you consider the depths/heights of the troughs and crests as being variable – its easy to see how the earths climate can ‘drop’ into a different ring around the centre and the climate within this ‘ring’ will be slightly different.
Taking my rather wittering analogy a stage further, the different rings (i.e. distances from the centre) could be comparable to major cycles, like Milankovich, etc…..
We all know about the change in the earths axial tilt, etc, effects of the moon-earth distance, etc,etc – if you take my analogy even further, these major astronomical/planetary type changes are tilting the plane upon which the bowl sits – thereby tipping the ball into the next trough/ring.
My (probably badly made) point is that the climate needs to be considered within each phase of its development and cannot be viewed as a whole ‘range’.
Gawd, I hope this makes sense (it made sense in my mind! LOL)

Another reference. I know I’ll meet a lot of resistance from laymen here including the author but there really is nothing new in this posting. Albedo is just another unit of measure for the earth’s equilibrium temperature and it should therefore come as no surprise that they should line up perfectly.
http://hyperphysics.phy-astr.gsu.edu/hbase/thermo/grnhse.html
My emphasis:

An issue of major concern is the possible effect of the burning of fossil fuels and other contributers to the increase of carbon dioxide in the atmosphere. The action of carbon dioxide and other greenhouse gases in trapping infrared radiation is called the greenhouse effect. It may measurably increase the overall average temperature of the Earth, which could have disastrous consequences. Sometimes the effects of the greenhouse effect are stated in terms of the albedo of the Earth, the overall average reflection coefficient.

richardscourtney says:
June 1, 2012 at 4:10 am
“You make a good point in your post at June 1, 2012 at 2:57 am but, with respect, you misstate it.”
I didn’t misstate anything. I parroted, with citations and quotes, an award-winning online physics reference used by millions of people annually. If you believe there were any misstatements I suggest you take it up with the creator of the resource whose contact information is listed at:
http://hyperphysics.phy-astr.gsu.edu/hbase/hframe.html

Contact
Carl R. (Rod) Nave
Department of Physics and Astronomy
Georgia State University
Atlanta, Georgia 30302-4106
Email: RodNave@gsu.edu

richardscourtney says:
June 1, 2012 at 2:51 am
—————————–
Apologies for missing your earlier post.
Eschenbach has produced a method that is incapable of finding the correct climate sensitivity. He and you appear to be incapable of realising that. He is not the first to fall into this trap: Schwartz (2007) created a method with similar failings. The comment by Foster et al (2007) on Schwartz (2007) (http://www.jamstec.go.jp/frsgc/research/d5/jdannan/comment_on_schwartz.pdf) is relevant to Eschenbach latest half-backed effort.
You seem allergic to the idea that climate is more complex than a one-box model. How long would I have to search before I could find a quote from you or your fellow lobbyists proclaiming that climate models are insufficiently complex? Do you not notice the contradiction here, or do you not care? To claim that a one -box model is sufficient, is to claim that either all components of the climate system (such as the subsurface ocean, and the atmosphere) warm at the same rate, or that the more slowly changing parts of the system cannot subsequently affect the other parts. Which of these two absurd positions do you hold?

“If the temperature is only influenced by albedo and TSI”
I would say that temperature at the surface is set by surface atmospheric pressure and TSI but albedo changes the amount of solar energy (TSI) that gets into the oceans AND is involved in the rate at which energy flows from oceans to space.
Low albedo allows more energy into the oceans due to the widening of the equatorial air masses but also represents a faster hydrological cycle working to reduce or cancel out the effect of more energy into the oceans.
High albedo allows less energy into the oceans due to the narrowing of the equatorial air masses but also represents a slower hydrological cycle working to reduce or cancel the effect of less energy into the oceans.
Thus high sensitivity to albedo changes but low sensitivity overall because the albedo changes apply a negative system response to any other forcing effect.
Oceanic heat release from below and solar changes from above (other than raw TSI) both work to alter the width of the equatorial air masses in relation to the size of the polar air masses. Sometimes offsetting and sometimes supplementing one another in a constant dance around the equilibrium system energy content set by surface pressure and TSI.
When the polar air masses are ‘winning’ the troposphere is cooling and when the equatorial air masses are ‘winning’ the troposphere is warming.

Global warming theory depends on increased GHGs reducing Albedo (clouds and ice surfaces and vegetation).
Low cloud cover declines and high cloud cover increases which provides 1.0 W/m2/C of feedback (and results in 0.6C of the 3.0C per doubling expected). Ice and vegetation are lower and take longer to have an impact. Clouds might only take a day or two.
—–
Now the Earth’s Albedo certainly does change through time. How much does it increase in the ice ages for example. What about the Cretaceous when there is no ice and the ocean covers 35% of the continents. Snowball Earth conditions produce an Albedo of 50% versus 30% today.
Clouds are the big uncertainty. They are over 50% of the total Albedo at -53.0 W/m2. Doubled CO2 +3.7 W/m2. The cloud feedback signal can easily impact your doubled CO2 temperature impact by +/- 100%.

Excellent paper, and thanks very much for it. One of Irving Copi’s elements of a successful hypothesis — the one too many climate scientists forget or ignore — is simplicity. All other things being equal (and that’s something you show pretty well), the simpler model, has to be the best. This approach looks like a bloody good bet to confusticate and bebother The Team. If albedo and insolation are good enough to explain observations on their own then, in logic, anything else should be considered superfluous … at least until somebody shows that some of the various forcings improve the model. Apparently, they don’t … at least in relatively recent times. I accept that the model’s not predictive, but surely insolation follows some fairly well-known trends. And I imagine future albedo can be predicted from trends as well … within limits: testable over the next decade or three, and subject to correction with real-time measurements as they come in. I suppose one could estimate albedo and insolation in past as well, though maybe without much precision. (Better than tree rings, anyhow.) This looks like a significant advance: something against which a lot of dodgy ‘research’ might be tested. One wonders why it hasn’t been done before (or, if it has, in which swamp the results were buried). Very well done, and I hope you’re able to whack a few thick skulls with it.

richardscourtney says:
June 1, 2012 at 8:19 am
————–
If Eschenbach had done his analysis on a week of hourly data from Epsom, he would have found a time constant of a few hours, with no evidence that longer time constants are required. Would you still claim that a one-box model was sufficient, even though the results of hourly, monthly and annual data all suggest different time constants?
I hope the advice you claim to give to MPs is of better quality than what you write here. Or does advising MPs amount to sending uninvited letters?

Sunlight and albedo seem to be necessary and sufficient variables to explain the temperature changes over that time period.
And presumably, Svensmark can explain a good deal about the albedo.
BREAKING NEWS – CERN Experiment Confirms Cosmic Rays Influence Cloud Seeds
http://wattsupwiththat.com/2011/08/24/breaking-news-cern-experiment-confirms-cosmic-rays-influence-climate-change/

“since in general the albedo decreases when temperature goes down.”
Does it ?
Cloudiness decreased during the late 20th century warming and is now on the increase again:
http://wattsupwiththat.com/2007/10/17/earths-albedo-tells-a-interesting-story/
“This means that when the eruption happens and drives up the albedo, the albedo elsewhere on the planet must be reducing to compensate.”
Most likely warmed air resulting directly or indirectly from the eruption descends elsewhere and the adiabatic warming in the descending column reduces cloudiness there to offset the increased cloudiness caused by the eruption or its products.

Willis: I don’t get the point.
Since any strictly monotonic function can replace exp(-1/ τ), there is no reason to think of τ as a time constant; it’s merely a fitted parameter to make b = exp(-1/ τ), and a = λ/ τ where a and b are the coefficient in a standard vector linear autoregressive model. You could have b=3^τ and a=sqrt(τ),
Why would you want to do this? there is no principled reason to prefer one pair of invertible equations to another, subject to the constraint that if you search hard enough you can find some reparameterizations where the estimation procedure is unstable, and those you would prefer to avoid.
The estimate for τ has no meaning other than it is the estimate that gives the best fit with this model. It’s not “months” or “years” or anything like that.

Paul Vaughan asked:
“Are you sure global albedo is the right metric?
(…or are you just attempting simplified narrative?)”
Since albedo either increases or decreases (never remaining the same for long) the right metric is the netted out result of all factors influencing albedo globally.
If the right observations are recorded accurately enough over a long enough time I am sure that the relationships I describe will become apparent and widely accepted.
Since I first promulgated such ideas there have been numeroius papers which appear supportive and many contributors here and elsewhere have been setting out similar if less complete formulations.
A few years ago my propositions were ‘way out there’. Now, not so much.

richardscourtney says on June 1, 2012 at 8:36 am
“There is no “ACTUAL KNOWN sensitivity”.
Each climate model uses a different value of climate sensitivity.
Willis has assessed reality so a climate model can be tested against Willis result.”
Some simple questions: If there is no actual known sensitivity then why is Mr. Eschenbach projecting his ‘real world’ assessment into the future? That doesn’t make any sense. Besides CO2 is still increasing and if Mr. Eschenbach is already claiming a 3°C/century trend for the Northern Hemisphere I would not want to know what the trend will be when CO2 has doubled. That’s gonna be catastrophic for the Northern Hemisphere.
How would you establish sensitivity when CO2 is still increasing? Even if CO2 will stabilize in the atmosphere next year (for example) can we be sure that the warming stops immediately or is there still some more warming in the pipeline (what some well respected climate scientists claim) when climatic conditions turn to warming again?
What Mr. Eschenbach has done is making a climatic sensitivity assessment of some real world data in the early phases of CO2 increase in a “Cold” Earth.

D. J. Hawkins says:
June 1, 2012 at 4:59 pm
“Please re-read his post. Willis isn’t talking about 0.3°/C per decade, but 0.3°/C per doubling of CO2. If he is correct, I can live with that.”
Have you seen Figure 1 closely and what it reads underneath? It is claiming a 0.3°C/decade trend for the NH.
Mr. Eschenbach is wrong if he means a 0.3°C per doubling of CO2. It means a negative feedback (probably due to water vapor – what else?) of more than 75%. And that is 100% wrong. It isn’t happening now and it won’t happen in the future.
I’ve explained that here: http://wattsupwiththat.com/2012/05/29/an-observational-estimate-of-climate-sensitivity/

oops, I wrote: A change in forcing has about 90% of its total effect during the month of the change in forcing (the 90% approximation is from your spreadsheet, showing the decay of the effect in subsequent months.)
Rereading the spreadsheet, I see that was wrong.
Willis wrote: Matthew, the standard form for exponential decay over time is exp(-t/tau),
I appreciate that. but since t is held constant, the functional form of the function of tau is irrelevant, and as I wrote any pair of invertible transforms is equivalent to the linear vector autoregressive model.

D. J. Hawkins says:

As one note, global humidity is more or less the same over the last 40 years, so the primary feedback mechanism of the AGW thesis is conspicuously absent.

Ah…No it’s not:
http://www.sciencemag.org/content/310/5749/841.abstract
http://www.sciencemag.org/content/323/5917/1020.summary
The water vapor feedback is now well-verified. Those who desire a low climate sensitivity basically have to put all their hopes in a strongly-negative cloud feedback.

Willis, I have tried to think of an internal control for you analysis.
Would it be a lot of work to just analyze the belly of the beast between the Tropics of Cancer and Capricorn? Here I would expect the time constant to be smaller than when comparing the the hemispheres. In this band one should get the least swing between winter/summer.

Willis , this is very interesting. It does suggest that climate is inherently stable and dominated by strong neg feedbacks , not the artificially invented positive feedbacks fed into the models.
One correction in your text:
“But the calculations using the given time constants and sensitivities were able to capture both hemispheres very accurately. The RMS error of the residuals is only a couple tenths of a percent.”
Err, wasn’t that “a couple of tenths of a degree” ?! Not quite the same level of accuracy.
“The fit is actually quite good, with an RMS error of only 0.2°C and 0.1°C for the NH and the SH respectively.”
One thing you do need to add for this to be meaningful is some uncertainty calculation. What is the uncertainty of the source data and how do changes within that range affect your results.
In fact, someone else pointed out that using 3.2 W/m2 gave a significantly higher climate sensitivity ( 1.6 C IIRC). So what is the uncertainty in that figure and how does its range affect your result?
This is one of the biggest problems in climate “science”, there is a total lack of regard for uncertainty evaluation ( or totally fictitious ones are often provided when they are given).
One other thing you could try is to separate out the tropics rather than doing a simple NH,SH split. The tropics have a 6m cycle in irradiance, not and annual one. This may account for the way your fits have noticeable deviations near the ends of the ellipses.
It would also seem to be a significant omission that you do not seem to state anywhere just what “temperature” you are using in all this.
Overall this is a great article. The astounding simplicity and the very small residuals suggests you are on the right track.
One more point, forcing due to doubling CO2 is referring to pre-industrial levels. The next doubling will have less effect. Atmospheric CO2 conc is well above the “linear” log relation to gas concentration where each doubling causes the same effect.
Nice post.

“Matthew, the standard form for exponential decay over time is exp(-t/tau), where “t” is the elapsed time. ”
For those having trouble grasping this , it should be written exp(-delta_t / tau), since in this case the formula is given in a iterative form, so delta_t is the time interval from T(n) to T(n+1) ie , in this case one month. The exponential is dimensionless as it should be and tau is in the same time unit as the “1”.

D. J. Hawkins says:
June 1, 2012 at 6:14 pm
“As one note, global humidity is more or less the same over the last 40 years…”
Can you back that claim with sources? I can and it’s the opposite of what you are saying.
– Dai 2006 – Recent Climatology, Variability, and Trends in Global Surface Humidity.
Take a good look at Figure 11. It shows global humidity. What’s the trend?
– Willett et al 2008 – Recent Changes in Surface Humidity: Development of the HadCRUH Dataset.
“Between 1973 and 2003 surface specific humidity has increased significantly over the globe, tropics, and
Northern Hemisphere.”

Willis Eschenbach says:
June 1, 2012 at 6:04 pm
“I see that you don’t like them, and I see that you think if you say that very loudly and with great vehemence, it will make you right … unfortunately, your passion is not relevant.
In the other thread you refer to, you gave the standard explanation, which is that water vapor will be the dominant feedback, and it is strongly positive. Me, I think that the dominant feedback is clouds and thunderstorms, and they are strongly negative.”
First the evidence:
Schmidt et al 2010 – Attribution of the present‐day total greenhouse effect.
“The actual mean surface temperature is larger (by around 33°C, assuming a constant planetary albedo) due to the absorption and emission of long‐wave (LW) radiation in the atmosphere by a number of different “greenhouse” substances.”
That’s all we need 33°C. Without “greenhouse” substances Earth would be -18°C. It’s not it’s 15°C. Every well respected climate scientist accepts that.
Here is another graph coming from Roy Spencer’s Climate Confusion
http://www.klimaatgek.nl/klimaatimg/lapse%20rate.jpg
It simply states that if clouds were removed from the atmosphere and everything else stays equal the temperature will rise to 60°C due to the greenhouse effect. That given fact is known in the climate world and accepted by many, if not all, climate scientists.
So clouds do cause a 58% cooling ((60-15)/78(total greenhouse warming)x100%) and not the 45% I claimed. I made a calculation error there. Yes clouds cause cooling (58%) (which I accept), but the net effect will be warming on top of the 2xCO2 warming effect or the total warming from 2xCO2 and water vapor together. Nobody knows that exactly. (Schmidt et al 2010 “For instance, one cannot simply take the attribution to CO2 of the total greenhouse effect (20% of 33°C) and project that onto a 2 × CO2 scenario.”) The extra clouds won’t cause the huge negative feedback you believe in. At least not in the real world.
Now to some of your quotes: “Sunlight and albedo seem to be necessary and sufficient variables to explain the temperature changes over that time period.”
Just to name a few papers: Solanki 2003 – Can solar variability explain global warming since 1970?, Lockwood 2008 – Recent changes in solar outputs and the global mean surface temperature. III. Analysis of contributions to global mean air surface temperature rise, Benestad 2009 – Solar trends and global warming, Pittock 2009 – Can solar variations explain variations in the Earth’s climate?, etc etc etc. If you want some more just ask for it. The list is so long that one can rule out that the Sun will be sufficient enough to cause the temperature changes over that time period.
And: “For example, I have held that the effect of volcanoes on the climate is wildly overestimated in the climate models, because the albedo changes to balance things back out.”
What causes the albedo to change? I can see Pinatubo very clearly here:
http://www.drroyspencer.com/wp-content/uploads/UAH_LT_1979_thru_April_2012.png
but not in cloud variations here:
http://isccp.giss.nasa.gov/zD2BASICS/B8glbp.anomdevs.jpg
Furthermore: “I can’t, and I say that the reason is that the clouds respond immediately to such a disturbance in a thermostatic fashion.”
Name your source for that statement please. I cannot see the cloud response in my presented graph. Can you?
How can clouds respond to such a disturbance when you have just ruled out aerosols, volcanic forcing and indirect aerosols? It is aerosols emitted by volcanoes which cause volcanic cooling.
http://vulcan.wr.usgs.gov/Glossary/VolcWeather/description_volcanoes_and_weather.html
“increases in volcanism that could have thrown more airborne volcanic material into the stratosphere, thereby creating a dust veil and lowered temperatures.”
Where are your sources/evidence for your claims? No computer models please.

richardscourtney says:

The ‘tropospheric hotspot’ is missing. That missing elevated temperature at altitude in the tropics is the anticipated result of a water vapour feedback.
You have linked to abstracts of papers which claim to have determined increased water vapour at altitude in the tropics. But there has been no accelerated warming at altitude relative to the surface in the tropics. In other words, the increased humidity has NOT provided a positive feedback.
So, if the papers you cite are right then you have cited evidence which shows
The water vapour feedback is now REFUTED.

That is very impressive amount of incorrect science to pack into just a few sentences!
(1) It is quite debatable that the “hotspot” is missing. The analyses / re-analyses of the different radiosonde and satellite data sets show quite different results for the multidecadal trends in the tropical troposphere. This is because both the satellite and radiosonde data have serious issues that can produce artifacts in these long term trends. And, in fact, for fluctuations in temperature on monthly to yearly time scales where artifacts are not an issue in the data, the tropical tropospheric amplification is well-confirmed.
(2) The “hotspot” (enhanced warming at altitude predicted for the tropical troposphere) is not a result of the water vapor feedback, i.e., it has absolutely nothing to do with water vapor absorbing additional greenhouse gases. Rather, it is just a result of the basic physics of the lapse rate as long as it follows the moist adiabatic lapse rate. Hence, your reasoning that this “refutes” the water vapor feedback is completely spacious.
(3) As Isaac Held has explained, although the predicted enhancement of warming at altitude is predicted to increase the water vapor feedback somewhat over its value in the absence of this effect, it also produces the lapse rate feedback, a negative feedback in the climate models that occurs because the “hotspot” means the surface does not need to warm as much as it otherwise would in order to increase the radiation emitted back out into space and restore radiative balance. And, in fact, it turns out that this lapse rate feedback produced is predicted to be a bit larger in magnitude than the enhancement of the water vapor feedback. Hence, the net effect of the purported absence of the “hotspot”, were it to prove real, would be that the climate models are probably slightly underestimating, not overestimating, the climate sensitivity.

Willis,
As usual, a very thought provoking post. What you touch on here I see as an extension of your post on ‘The cold equations’ (Jan 28 2011). Together these seem to point to a very good path for growing a model from the simple to the complex by adding terms to eliminate discrepancies. What I like about your approach is that it can be directly related to physical quantities. With an electrical background I kind of see it as building up an ‘analog computer and solving the equations digitally. The climate system is obviously a system of many modes, each having its own time constant. But it is still frequently found informative to explore simple single time constant approximations and then extend them.
Ok. So I took your single time constant model which seems to show encouraging results and looked at it as an energy storage unit of capacity C=mass times heat capacity., a current source (in electrical terms , which is the solar energy input. And a coupling out of the system. This output coupling is the parameter which determines your tau value. This coupling in the present case is a function of Co2, moisture and all the rest. Your model assumes this constant at some value (a place to start). When I use The sigma*T^4 formula for energy out. I find that I have to adjust (epsilon if you like) to a value of ~ 0.6 to get the temperature to rise to the measured level.
An extension here could be this as adjusting the temperature to the TOA level. A resistance to TOA and a small atmosphere storage reservoir could be added to incorporate a more physical model. Also the ocean could be broken into shallow /deep storage with resistance between.
In the ultra simple model above The heat capacity adjusted to roughly the equivalent of 70 M depth of water matches the temperature phase and amplitude.
This is all pretty quick, so I hope there are not too many mistakes.
I see Bart is on the thread. Help us out here Bart, I think this is along the lines of the systems analysis approach that you advocate.
The Matlab/Octave code for a crude step integration solver is attached. The result is the figure below
load alb_temp;%load year,albedo,solar flux,avg temp,for globe,nh,sh.
% from W. Eschenbach post may 31,2012.
%These data are in a 10 column array named at;
%C=1e4;%Guess 1 atm air columnheat capacity
C=2.9e9/15;%700M depth of water(adjusted by divisor)
sigma=5.67e-8;%Boltzmann constant
%B=0.3;%Bond albedo
Tn=260;%Start the calculation at this temperature
%otherwise build up ts long due to T^4 (not a lineat eq).
delt=1;%time increment (mo)
t=at(:,1);
B=at(:,3);
nsam=length(t);
%T=at(8,:);%global average temperature (C)
T=zeros(size(t));
I=(1-B).*at(:,6);%average global solar flux (W/M^2)
Tm=at(:,9);%global temp
%hold
for n=1:nsam;
Tn=Tn+3600*24*30*delt*(I(n)-0.615*sigma*Tn^4)/C;
T(n)=Tn;
endfor
plot(t,T-273,’r’)
hold
plot(t,Tm,’b’);
plot(t,(I-mean(I))/10+mean(Tm),’g’)

Hi Willis,
As argues before, with the annual cycle you are just calculating the frequency response of a simgle frequency, , which doesn’t have an effect on multidecadal periods. Other people also arrived at 0.1 K/wm-2 for the annual cycle so your value isn’t new either
http://members.casema.nl/errenwijlens/co2/Climate_sensitivity_period.gif
I suggest you read the recent paper by J. H. van Hateren who considers the complete spectral response one of the conclusions reads
” The transient climate response (response after 70 years of 1 % yearly rise of CO2 concentration) is 1.5 ± 0.2 °C.”
http://rankexploits.com/musings/2012/empirically-based-estimate-of-climate-sensitivity/
the online paper
J. H. van Hateren, 2012, A fractal climate response function can simulate global average temperature trends of the modern era and the past millennium, Climate Dynamics, 10.1007/s00382-012-1375-3
http://www.springerlink.com/content/348g07361627360x/fulltext.html

Steve Keohane says:

Sorry to disrupt your fantasy, I did not cherry pick anything. Here is an updated version of that graph, I simply stored these two graphs when I came across them in 2008 and 2012, I did not generate them. http://i48.tinypic.com/2qlfnzn.jpg
I understood them to be US gov’t data.

In other words, you came across some data that agrees with what you want to believe. So, despite the fact that it disagrees with lots of data better suited for the purpose of looking at long-term trends and you have no idea where it is from or what the caveats and issues associated with it are, you conclude things from it that are in contradiction both with what the scientific community has concluded and basic physical principles.
If that is not a cherry pick, I don’t know what is!

Willis Eschenbach says:

So it’s claiming that observations show a constant increase in relative humidity, and it says that the models agree with it. But you say the models show stable or decreasing relative humidity …

Actually, I think the quote that you took from Soden is just poorly worded. If you read it in the context of the rest of the paper, it is clear that he is not saying they show a constant increase in the relative humidity. He is saying that they show an increase in upper tropospheric moisture that is equivalent to what you get if you assume that the relative humidity remains constant as things warm. He certainly should have worded that better, but if you read the rest of the paper, it will be obvious that this is what he was saying. [I talked about even slightly decreasing relative humidity as being compatible with the models because Dessler and coauthors wrote a paper in which he found a small decrease in relative humidity with time from the satellite data and thought that this was perhaps a bit incompatible with what the climate models predicted. However, in another paper a few years later, they actually checked what various models predicted and found that overall on average they did predict a slight decrease in relative humidity (although I think, within the variability of the models, it also included a completely stable relative humidity).]

Finally, FWIW (which may not be much), the model results from the NCEP Reanalysis Model are here … they show variations but no overall trend in either relative or specific humidity over the last decades.

Yes, which is why this NCEP reanalysis has been so popular with AGW skeptics. But, there are apparently known severe issues with the long-term trends in that reanalysis and it is contradicted by lots of other evidence from satellites (and other reanalyses too, I think) that show the moistening trend.

During the summer we must get much more moisture in the air than in the winter … but despite that, the resulting temperature is well modeled using a constant climate sensitivity. This observational evidence strongly supports the secondary role of water vapor in determining the temperature.

Statements like this drive me batty. If you think the seasonal cycle is in contradiction with the role of water vapor, then you should be able to demonstrate this, for example, by showing that climate models exaggerate the seasonal cycle as a result of the important role that the water vapor feedback plays in them. But, of course, that isn’t true since, as I noted, the analysis that I know of that looked at seasonal cycles that I linked to previously concluded that it supports climate sensitivity right in the IPCC range.

You still haven’t grasped the nettle, Joel. I’ve hindcasted the temperature, with shocking accuracy, using nothing but the clouds and the sun. This means that whatever other feedbacks and mechanisms might be involved, there is very, very little left for them to explain … and thus it indicates that the other mechanisms play only a very small role in determining temperature.

It may shock you but it doesn’t shock me. Yes, a simple model with a single time scale can do a good job at modeling the seasonal cycle, which is undoubtably dominated by solar effects. As to how well you did with the overall trend, I already told me the reasons for being skeptical about that; I doubt if the albedo data is even good enough to get that without large error bars.
And, your model doesn’t speak at all to what feedbacks are or are not present.

joeldshore
“Actually, I think the quote that you took from Soden is just poorly worded. If you read it in the context of the rest of the paper, it is clear that he is not saying they show a constant increase in the relative humidity. He is saying that they show an increase in upper tropospheric moisture that is equivalent to what you get if you assume that the relative humidity remains constant as things warm. He certainly should have worded that better, but if you read the rest of the paper, it will be obvious that this is what he was saying. [I talked about even slightly decreasing relative humidity as being compatible with the models because Dessler and coauthors wrote a paper in which he found a small decrease in relative humidity with…”
OOPS! someone better tell lacis and hansen. They assume something a bit different, where by rising T causes rising humidity and dwindling cloud cover in order to have an unstable positive feedback sufficiently strong to explain how a 1 deg C rise in co2 forcing will cause a 3-6 deg C total temperature rise. It seems that if RH stays constant, the water vapor feedback from a 5 deg C rise over the entire atmospheric column only adds about 30% more h2o vapor which is far less than a doubling and is in fact less than the effect of the co2 doubling – so much for the largest official ipcc feedback.
Hey, your co2 doubling + h2o vapor at constant RH(assuming a 5 deg C T rise) gives you a good 5 or 6 W/m^2 and you only need an additional 20 W/m^2 or so to get to the 5 deg C rise.
And, oh, you also need to explain why there would be a cloud decrease with a substantial increase in h2o vapor in the atmosphere and a slight rise in T. That means since we’re currently at around 62% cloud cover that this is as much as we can get. Drop the T and you start to lose cloud cover. Raise the T (accordning to lacis and hansen) and you start to lose cloud cover. Evidently, the only way Earth can get more than this 60% cloud cover is to have something other than h2o clouds – like venus. SARC OFF/

The use of 10 years of data given the method used by Willis doesn`t negate the criticism leveled at his previous post. What he has modeled is the annual variation in temperature of each hemisphere.
First of all, The procedure he used fits high frequency data, with the high amplitude of oscillation, about 20 and 10C peak to peak, using a very simple model, over a period of 10 years, to find a parameter that drives a global temperature trend which measurements show is 0.1 – .2C. The residuals in his fit are much higher than that.
Second using a single lag time for the model is no way to estimate the driver of a long term global temperature trend which takes decades or centuries to reach equilibrium, while short term annual oscillations dominate the data that you are using. Whether one uses a single year or 10 years of data makes no difference to that argument. The only thing you will find is the relationship between the forcing variables and the high frequency oscillations they are causing.
This post is one of the clearest examples of quackery and pseudo science I have seen on this web site..