Guest Post by Willis Eschenbach
This is an extension of the ideas I laid out as the Thunderstorm Thermostat Hypothesis on WUWT. For those who have not read it, I’ll wait here while you go there and read it … (dum de dum de dum) … (makes himself a cup of coffee) … OK, welcome back. Onwards.
The hypothesis in that paper is that clouds and thunderstorms, particularly in the tropics, control the earth’s temperature. In that paper, I showed that a falsifiable prediction of greater increase in clouds in the Eastern Pacific was supported by the satellite data. I got to thinking a couple of days ago about what other kinds of falsifiable predictions would flow from that hypothesis. I realized that one thing that should be true if my hypothesis were correct is that the climate sensitivity should be very low in the tropics.
I also figured out how I could calculate that sensitivity, by using the change in incoming solar energy (insolation) between summer and winter. The daily average top of atmosphere (TOA) insolation is shown in Figure 1.
Figure 1. Daily TOA insolation by latitude and day of the year. Phi (Φ) is the Latitude, and theta (Θ) is the day of the year expressed as an angle from zero to 360. Insolation is expressed in watts per square metre. SOURCE.
(As a side note, one thing that is not generally recognized is that the poles during summer get the highest daily average insolation of anywhere on earth. This is because, although they don’t get a lot of insolation even during the summer, they are getting it for 24 hours a day. This makes their daily average insolation much higher than other areas. But I digress …)
Now, the “climate sensitivity” is the relationship between an increase in what is called the “forcing” (the energy that heats the earth, in watts per square metre of earth surface) and the temperature of the earth in degrees Celsius. This is generally expressed as the amount of heating that would result from the forcing increase due to a doubling of CO2. A doubling of CO2 is estimated by the IPCC to increase the TOA forcing by 3.7 watts per metre squared (W/m2). The IPCC claims that the climate sensitivity is on the order of 3°C per doubling of CO2, with an error band from 2°C to 4.5°C.
My insight was that I could compare the winter insolation with the summer insolation. From that I could calculate how much the solar forcing increased from winter to summer. Then I could compare that with the change in temperature from winter to summer, and that would give me the climate sensitivity for each latitude band.
My new falsifiable predictions from my Thunderstorm Thermostat Hypothesis were as follows:
1 The climate sensitivity would be less near the equator than near the poles. This is because the almost-daily afternoon emergence of cumulus and thunderstorms is primarily a tropical phenomenon (although it also occurs in some temperate regions).
2 The sensitivity would be less in latitude bands which are mostly ocean. This is for three reasons. The first is because the ocean warms more slowly than the land, so a change in forcing will heat the land more. The second reason is that the presence of water reduces the effect of increasing forcing, due to energy going into evaporation rather than temperature change. Finally, where there is surface water more clouds and thunderstorms can form more easily.
3 Due to the temperature damping effect of the thunderstorms as explained in my Thunderstorm Thermostat Hypothesis, as well as the increase in cloud albedo from increasing temperatures, the climate sensitivity would be much, much lower than the canonical IPCC climate sensitivity of 3°C from a doubling of CO2.
4 Given the stability of the earth’s climate, the sensitivity would be quite small, with a global average not far from zero.
So those were my predictions. Figure 2 shows my results:
Figure 2. Climate sensitivity by latitude, in 20° bands. Blue bars show the sensitivity in each band. Yellow lines show the standard error in the measurement.
Note that all of my predictions based on my hypothesis have been confirmed. The sensitivity is greatest at the poles. The areas with the most ocean have lower sensitivity than the areas with lots of land. The sensitivity is much smaller than the IPCC value. And finally, the global average is not far from zero.
DISCUSSION
While my results are far below the canonical IPCC values, they are not without precedent in the scientific literature. In CO2-induced global warming: a skeptic’s view of potential climate change, Sherwood Idso gives the results of eight “natural experiments”. These are measurements of changes in temperature and corresponding forcing in various areas of the earth’s surface. The results of his experiments was a sensitivity of 0.3°C per doubling. This is still larger than my result of 0.05°C per doubling, but is much smaller than the IPCC results.
Kerr et al. argued that Idso’s results were incorrect because they failed to allow for the time that it takes the ocean to warm, viz:
A major failing, they say, is the omission of the ocean from Idso’s natural experiments, as he calls them. Those experiments extend over only a few months, while the surface layer of the ocean requires 6 to 8 years to respond significantly to a change in radiation.
I have always found this argument to be specious, for several reasons:
1 The only part of the ocean that is interacting with the atmosphere is the surface skin layer. The temperature of the lower layers is immaterial, as the evaporation, conduction and radiation from the ocean to the atmosphere are solely dependent on the skin layer.
2 The skin layer of the ocean, as well as the top ten metres or so of the ocean, responds quite quickly to increased forcing. It is much warmer in the summer than in the winter. More significantly, it is much warmer in the day than in the night, and in the afternoon than in the morning. It can heat and cool quite rapidly.
3 Heat does not mix downwards in the ocean very well. Warmer water rises to the surface, and cooler water sinks into the depths until it reaches a layer of equal temperature. As a result, waiting a while will not increase the warmth in the lower levels by much.
As a result, I would say that the difference between a year-long experiment such as the one I have done, and a six-year experiment, would be small. Perhaps it might as much as double my climate sensitivity values for the areas that are mostly ocean, or even triple them … but that makes no difference. Even tripled, the average global climate sensitivity would still be only on the order of 0.15°C per CO2 doubling, which is very, very small.
So, those are my results. I hold that they are derivable from my hypothesis that clouds and thunderstorms keep the earth’s temperature within a very narrow level. And I say that these results strongly support my hypothesis. Clouds, thunderstorms, and likely other as-yet unrecognized mechanisms hold the climate sensitivity to a value very near zero. And a corollary of that is that a doubling of CO2 would make a change in global temperature that is so small as to be unmeasurable.
In the Northern Hemisphere, for example, the hemispheric average temperature change winter to summer is about 5°C. This five degree change in temperature results from a winter to summer forcing change of no less than 155 watts/metre squared … and we’re supposed to worry about a forcing change of 3.7 W/m2 from a doubling of CO2???
The Southern Hemisphere shows the IPCC claim to be even more ridiculous. There, a winter to summer change in forcing of 182 W/m2 leads to a 2°C change in temperature … and we’re supposed to believe that a 3.7 W/m2 change in forcing will cause a 3° change in temperature? Even if my results were off by a factor of three, that’s still a cruel joke.
Thanks for the additional info, Willis.
Especially the info on your dt calculations.
If I have this right, for any particular latitude band, you are calculating
Tave_summer = [Tmar + Tapr + Tmay + Tjun +Tjul + Taug] / 6
Tave_winter = [Tsep + Toct + Tnov + Tdec +Tjan + Tfeb] / 6
dT = Tave_summer – Tave_winter
If you will humor me, I have a couple of additional questions.
How are you calculating T for any particular month in a particular latitude band?
Which data series are you using?
How do you extract the data for a particular latitude band?
Are you using the same method to get a summer and winter RFave with dRF = abs(RFave_summer – RFave_winter)?
And as someone asked above,
Are you using the TOA (Top of Atmosphere) insolation or insolation at ground?
From you comment on clouds as feedback and your wikipic,
I’m guessing TOA.
johnnythelowery (06:42:54) : Said
“I miss Manuel already. His Iron sun and all that(what ever that is-still can’t figure out what the hell he’s barking on about!). Can I petition for a month long ban instead of life time. I’m sure he’ll behave in the future. It’s just to see a fellow realist get a smack down here at WUWT.”
Can I put in a plea for a months ban as well? As you say Anthony he is always polite so that helps the nature of the general discourse. Even better, in my old school they used to promote the bad boys to positions of responsibility. How about asking Manuel to provide the material for his own thread? We can read, learn, then go wildly off topic 🙂
tonyb
The annual sensitivity is dT/dF for the 6 month extremes… but what of he _daily_ sensitivity? The day-night temperature swings in deserts can show about 40 K change from about 1000 W/m2 forcing… still only 0.045 K.m2/W, but obviously the transient admittances are even more important on this short time scale. I don’t have a conclusion, just a suggestion that you dig a bit deeper.
Willis,
You are dealing with a cyclic system, and not permitting it to equilibrate. Apart from the transfer of energy from the high to low insolation areas, winter temps are warmer than the winter solar flux could sustain because the earth is coming off a summer. Summer temps are cooler than the additional flux would support for the inverse reason. Calculating the sensitivity as the seasonal difference underestimates vs an increase in both over many cycles.
I concur with Goddard that looking at something like mutli year changes in solar flux due to solar cycles would be more productive.
Grizzled,
How hot do you think it would get in the desert, if the sun stayed up high in the sky for 30 hours instead of just 8? Maybe 90C?
You can’t draw any conclusions about sensitivity until the system gets closer to equilibrium. I’ve fried eggs on top of Coleman coolers in the desert.
Tonyb
Regarding Oliver. He’s got his own Headline/Blog and Comments thread regarding his Neutron Star surrounded by an Iron casing theory of the center of the sun. Check it out. it’s very interesting. Don’t know why he wouldn’t listen to Anthony.
http://tallbloke.wordpress.com
Willis
I observe many climatologists to be confused about what is meant by “falsifiable.” As an effect of this confusion has been to base ultra-expensive public policy proposals upon unfalsifiable and thus unscientific climate models, I’d like to dispel their confusion. I hope you won’t be offended if I use a critique of your article as the vehicle for an attempt at doing so.
You’ve stopped short of providing a falsifiable hypothesis. To make your hypothesis falsifiable, you’d need to cast it into the form of a predictive model. Each prediction of such a model would state the outcome of an independent statistical event. The totality of such events would form the statistical population of any study in which your model would be tested. In a falsifiable hypothesis, the set of all possible outcomes would be described in sufficient detail for the actual outcomes to be measured.
tallbloke (02:14:54)
Always good to hear from you, tallbloke.
Yes, heat does mix down in the ocean. But as you point out it is a slow process, because it is opposed by the tendency of warm water to rise.
My point is that the earth is basically in equilibrium. This means that whatever energy enters the ocean is matched by energy leaving the ocean. That means that, albeit with a slight (one month) lag, all of the solar energy striking the ocean heats the air.
Yes, that lag also means a slight reduction in a temperature average that is centered around the peaks in insolation as I have done. But because the lag is short (one month), that reduction is not large, on the order of 10%.
While this is true, it does not affect my analysis. My analysis is based on equilibrium conditions.
Agreed. This is inevitable when the earth warms or cools. But my analysis is not looking at long term warming or cooling of a degree or less. I’m looking at the annual changes.
There are a couple parts that you are overlooking. First, a main temperature control mechanisms is the emergence of reflective clouds and thunderstorms with increasing temperature. This does not “redistribute heat within the Earth-Ocean climate system” as you say above. It prevents heat from entering the system. The same is true about the wind-driven increase in ocean albedo. This also does not redistribute heat, it reflects heat out of the system.
The second is that when warm wet air is taken aloft in the core of a thunderstorm, it bypasses the majority of the greenhouse gases. This means that much more of the heat that it contains is free to radiate to space. Again, this is not a “redistribution”, it is an increased loss to space.
Again, this is a misconception. The cloud/thunderstorm does much more than redistribute heat. It actively increases heat loss from the system as a whole.
My best to you,
w.
Wiilis,
If I have understood you correctly you are looking at the ratio of the principal 12 month components of the seasonal variation of the flux (F’) to the seasonal variation of the temperature (T’).
F’ = T’*Y {where Y is the admittance}.
Or T’=F’/Y
Now for this sinusoidal component we have:
F’ = F*e^(iwt) {where F is the amplitude of that component, i is root -1, w the angular frequency and t the time.
and T’ = T*e^(iwt+p) {where T is the amplititude, and p the phase angle}
so T*e^(iwt+p) = F*e^(iwt)/Y
or T*e^(ip) = F/Y where Y is a complex number {the vector e^ip is just a rotation, it has unit length}
Now for admittances in parallel (as in this case) Y is additive
Let us say:
Y = Ys + Ye {where Ys is the admittance into space and Ye the sum of the admittances into the environment}.
I think you are looking for Ys = Y-Ye {where Y is your measured F/T}
The climate sensitivity (CS) when given as degrees K per doubling equates to
Ys = 3.7W/CS so CS = 3.7W/Ys
Now for your value of 0.15K, your recovered value for Ys is:
Ys = 3.7/.15 =~ 25W/K
Now the admittance of 1 m^3 of well mixed water is approximately
4200000*2*pi/(365.25*24*3600)) for a cycle with a period of one year
=~ 0.84W/K
and guestimates for the total Admittance for the ocean could range from 42 to 84 W/K
similarly the Admittance of the atmosphere is around 3W/K and the earth’s is very varied and not all that big.
So Ye is ~ 3W/K over land and (45-87)W/K over the oceans.
So over the oceans T = 2K could imply an oceanic flux amplitude of 90-176 W {I have left out all the per metre squared bits too save mess}
Now it is likely that you will find that on the western margins of the temperate oceans the ocenic flux amplitude will well exceed the solar amplitude. This is to be expected due to flux from the atmosphere which has passed over a region of high temperature amplitudes. The reverse effect is likely to be found over the eastern seaboards of the contintents.
I think that well isolated parts of the temperate oceans have T=~2.5K, so it is quite possible that almost the entire flux is oceanic or , Y =~ Yo {the oceanic admittance}.
Now the figures for the oceanic admittance are guestimates but figures much lower than 40W/K seem unlikely to me.
Now you are looking for Ys = Y – Ye, but Ye = Yo + Ya {Ya = atmospheric admittance} is likely to be bigger than Y over parts of the ocean and almost equal to it in isolated parts of the ocean. The reason it can be bigger is that the local Y = F/T {where F is the local solar flux amplitude} ignores the additional flux from the atmosphere as it passes from land to ocean.
Over the land Y will be greater than Ye {Ye =~ Ya} where prevailing winds come from the ocean and will decline in value towards Ye in isolated continental regions {actually really only in Mongolia/Eastern Siberia do they get close}.
The atmospheric Ya is a common factor in Ye across the globe and simple calculation implies that if over land Ys was zero then Y=Ye and a 150W value for F would imply a maximum for T ~ 150/3 = 50K (which is only around 1.5 times the Siberian amplitude, so the slack there is just 1.5W/K . The IPPC’s CS of 3K equates to 0.8W/K which is perhaps a little low. I am not going to argue about precise values for F as they differ from TOA insolation value anyway.
Unfortunately the problem is ill-conditioned in that over the oceans Y and Ye are similar in magnitude and Ye can be greater than Y=Fsolar/T locally, and the uncertainties in Ye are large and you need to determine the reciprocal of Y-Ye to find CS = 3.7W/(Y-Ye).
Now in all the above I have only dealt with the amplitudes of the variations, This is justified becuase we are treating Y = F’/T’ {variations in amplitude} as a stand in for Y = dF/dT {i.e linearity has been assumed over the ranges of the amplitudes}, the mean values of total Flux and absolute surface tmperature are of no interest, we only need the amplitudes of the local variations.
So readers be warned, arguments based on the total values of solar flux and surfaces temperatures are not necessarily relevant here, we are looking only for the slope dF/dT. So for instance the average flux from say the equator to the pole is of no interest only the amplitudes of any seasonal component of such fluxes would be relevant.
Alex
Willis Eschenbach (02:22:25) : “I am looking at changes in average temperature based on changes in average forcing.”
What I was getting at wrt clouds is this : if a change in GCRs, say, caused a change in cloud cover at a point in time during your experiment, then it would alter the temperature without altering TOA insolation. In the context of your experiment, that’s a forcing that isn’t an insolation feedback. That would invalidate your basic assumptions.
Assuming that such [non-feedback] forcings are not an annual phenomenon, doing your experiment over multiple years could eliminate them as a possible factor.
Willis “By looking at the lag between peak insolation and peak temperature (about a month), it appears that if the season’s insolation forcing were to continue at a constant value the majority of the equilibration would occur on the same timescale.”
Sounds reasonable, but I’m not sure that’s a valid assumption. Analogy : Water on a stove takes a long time to boil, but stops warming almost immediately when removed. [“almost” = heat in transit in the pot].
toyotawhizguy (02:00:19)
Well, if William Connolley says it’s raining, the first thing I do is look out the window. I see you are following in his footsteps. There is no such thing as “HadCM3” data.
HadCM3 is a climate model. Climate models do not output “data”, they output the results of the theories of whoever programmed the model. I know that Connelly thinks that the outputs of models are “data” … but that’s just a measure of the depth of his delusionary belief system.
In any case, the atmospheric absorption is meaningless for my analysis. I am looking at the relationship between TOA forcing and temperature. As such, the absorption by the atmosphere is only one of a host of things that go into determining the final temperature. These include albedo changes, airborne dust, tropical-polar heat fluxes, annual changes in the jet stream, and a host of other phenomena. But although they can explain the relationship between the forcing and the temperature, they don’t change the relationship.
The hockey team could label their their AGW theory as Pride and Prejudice
John of Kent (02:12:07)
I agree that both of those may certainly have some effect over the long term, although there’s more to learn. I suspect that that those are among the reasons for the long term drifts in the cloud/thunderstorm controlled equilibrium temperature.
However, on a day to day basis, both clouds and thunderstorms are controlled by temperature. That’s why you see them in the tropics mainly in the afternoons, while the mornings are clear. It’s not because there’s more cosmic rays in the afternoons …
Vukcevic (02:47:48)
Temperatures of the lower layers are immaterial until they get to the skin surface. When they are in the lower layers, they are totally insulated from the atmosphere.
When they reach the skin surface, they can then exchange energy with the atmosphere.
But again, this doesn’t affect my analysis. I am looking at annual changes, not the long term changes that you reference.
Eschenbach: I am looking at the relationship between TOA forcing and temperature.
I guess that brings up another question. Are you modeling the RF based on an assumed or averaged Solar Constant (‘So’ in the wiki article on insolation) or are you using a measured value? If you are using measurements, which data series?
davidmhoffer (04:08:08)
Willis,
I agree entirely, with one caveat – the “sweet spot” (usually called the “atmospheric window”) only exists when the sky is clear. This is because clouds are essentially black bodies for all longwave frequencies. Since cloud cover on the earth is on the order of 60%, this is far from a trivial factor.
I have not thought through all of the implications of this for my theory, however. Many thanks for the new idea.
w.
TLM (04:28:52)
I understand that you think that. However, your heartfelt opinion on the matter is not that useful. I have pointed out that all of the sunlight hitting the ocean heats the atmosphere (albeit with a slight lag of about a month). This indicates that a change of e.g. 3.7 W/m2 should not take long to warm up the planet either. I know that you claim it will take decades. But since the sun striking the planet warms it immediately, and the stored heat from such a change comes back out with only a one month lag, you’ll need more than your opinion to claim it will take a decade for the earth to react to a change in forcing.
Thank you for sharing, but you misunderstand the purpose of my posting here. It is not to claim that they are 100% correct and accurte. It is to expose my ideas to the critical glare of public scientific criticism. This is called the “scientific process”.
However, it is not forwarded by claims about who you might or might not find “worth reading”. If you have something scientific to add, please bring it on. Your un-cited claim that the earth is extremely slow to respond to a change in forcing is both unscientific and contradicted by our experience. The surface air warms and cools very quickly, we see it every day. And the stored heat comes back out with only about a month’s lag. Neither fact supports your argument.
Peter Sørensen (04:32:46)
I’m not taking about the maximum heatflux. I’m talking about the average heatflux, which is a very different beast.
I agree, it’s one of my main complaints about the climate models. However, in the narrow temperature ranges we’re talking about, I don’t think that is a major issue.
Robert of Ottawa (04:54:48)
Yes, it is Watts per square metre.
Steve Fitzpatrick (05:09:44)
I’ve never read anything that suggests that a significant amount of heat is transported from one hemisphere to another. Do you have a cite for that?
Also, while heat is stored in the ocean and then released, it is not accurate to say it is “released in the winter”. The lag between the peak insolation shows that as soon as the insolation starts to drop, the ocean begins releasing its heat. This only makes a small difference in the winter/summer averages.
johnnythelowery (07:06:08)
Wasn’t me, but like you, I certainly thank whoever it was.
Rienk (08:02:36)
Not sure how you are measuring this, but a lag of a month in a cycle with a period of a year seems like only 30° to me, and six weeks is 41.5°.
However, I also think your number (70% drop in signal from a 45° phase lag) refers to the peak signal, not the average signal. Please recompute the change in the average signal from such a lag when the average is centered around the peak in the un-lagged signal, and contains a half cycle.
cal (08:03:47)
The problem with your example is that unlike with the climate, energy is added during both the positive and negative swings of the current. In addition, because of the very high frequency of the cycles, there is almost no temperature change in the filament with time. Neither of these are true in the current situation.
Because of this, it doesn’t parallel the situation we are investigating, so we can’t use it to help understand the situation.
Pascvaks (09:10:11)
Unfortunately, data from that period is extremely scarce. We don’t know how much the globe changed winter to summer back then. So, good idea, but no data.
Ron Broberg (11:34:14)
As mentioned above, I used the HadCRUT3 absolute temperature set available here.
I used area-weighted averaging to extract the various values.
Yes.
TOA