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.
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Willis, I didn’t receive an answer to my question, perhaps it was too convoluted. Looking at your “SOURCE”, the map of the Insolation Top of Atmosphere, is described as: “Theoretical insolation at the top of the atmosphere” I have no easy way of verifying the numbers. However, on the same page is a “modeled” Photovoltaic (PV) Solar Radiation map:
http://en.wikipedia.org/wiki/File:Us_pv_annual_may2004.jpg
On this map, since I have a PV system, I can compare this model to reality, and the model overestimates actual output by 36.9%. My question is two-fold:(1) Is all of the ‘data’ on your “SOURCE” page from the same model(s), (2) and if true, how would an error of that magnitude affect the calculations? I assume much less energy into the system, about 27% less.
Willis, great job. You do analyzes I wish I could do. Some of the criticisms above stem from their own misunderstandings, not problems w/yours.
One improvement would be to analyze seasonal energy (enthalpy) changes instead of simple temp changes — you’d need relative humidity or dew-points to do this. There prb’ly isn’t sufficient data for this, tho.
I wonder what legitimate scientists like Pielke Sr, Spencer, Cristy or our resident Leif S. think about this.
Thank you Willis for a nice piece of work, which has got me thinking! Below are my first thoughts (usually the best). Sorry if they are presented in a disjointed way.
Your logic looks correct to me and your low calculated sensitivity is what I would expect to see, bearing in mind how remarkable stable the climate has been over long periods of time.
By focusing on the average seasonal changes this evens out short-term variation. Also if there is energy being held in the oceans over long time periods, then unless the rate of emission is much greater than rate of storage, by using just one year of data the effect will be minimal.
The amount/type of cloud cover is a key element in preventing run-away cooling or warming and perhaps it is the propensity for water vapour to form clouds that causes longer-term climate change?
Water has many strange and unique properties (see link below), not least it’s very unusual phase-change behaviour. Cloud formation depends on many factors, such as amount/type/altitude of aerosol, microscopic ice crystals, ions, high energy particles e.t.c. We need to have a better understanding of how these factors contribute at all spacial scales if we are to understand what’s happening.
Anomalous properties of water
http://www1.lsbu.ac.uk/water/anmlies.html
Observation suggests that systems displaying deterministic chaos seek to maximise entropy. The positive cooling effects of turbulent processes like thunderstorms are an important part of the Earth’s governor – hurricanes too have an important role in this. Again, we need a better understanding of how these systems operate and the amounts of energy expended so that their effects can be properly incorporated into the GCMs.
Thanks again for exposing your ideas to the WUWT ARP (Audience Review Process) – closed science leads to closed minds 😉
Steve Keohane (07:12:11) : edit
Steve, sorry I missed it. The photovoltaic map is how much energy is striking the ground, or more accurately, a flat plate facing southward perpendicular to the noon sun.
The data I used, on the other hand, is the top-of-atmosphere (TOA) insolation. As such, it will be larger than the sunlight that hits the ground, mostly because of reflection by clouds (which is why there is more sunlight in the southwest in your map.)
w.
Willis Eschenbach (14:12:34) :
Plus this bit from your post:
Ermmm…I’m not really measuring anything at all, or even doing much in the way of calculations. I simply assumed a more or less sinusoidal shape for both insolation and temperature. The min. and max. values are whatever you have and whatever they are. That doesn’t make any difference to the point I was trying to get accross. And not making a good job of, sadly.
I know that where I’m sitting (54 degrees north) our max. and min. temps are lagging the longest and shortest day of the year by about 6 weeks. Call it a month and a half, or 45 degrees. And if the system can be modelled as a first order lowpass, which I think is what you’re doing, then phase and magnitude of the output are inextricably linked. And thus I can calculate what the temperature signal would have been if it had been able to follow the input instantaniously. Simply divide by the cosine of the lag.
Willis Eschenbach (16:05:11) :
Which is all we need. for 4 weeks >cos(360*4/52)=0.885 and for 6 weeks >cos(360*6/52)=0.749. Simply divide whatever your sensitivity is by that number and you’ve corrected for lag. So I think your way of doing this is valid because the lag is fairly small and ignoring it doesn’t lead to a big change in outcome. No order of magnitude change anyway. And all that because the time constants of the exitation frequency and the system are fortuitiously similar.
Richard S Courtney (05:34:21) :
“The fine analysis conducted by Willis Eschenbach only concerns the climate sensitivity of the present interglacial state.”
It concerns the thermal inertia of this planet but tells absolutely nothing about its climate sensitivity.
You need 155 W for 150 days to heat a 100 meter water column (a common mixed layer depth) 5 C, and that’s what is reflected in this article.
Tropical clouds and thunderstorms are an important regulatory heat
engine stabilising the earth’s climate, as has been well argued in both this article and the previous one.
However the hasty dismissal of the role of the ocean below 10m depth
needs to be challenged. The criticism by Kerr et al. is I believe valid.
Ocean heat capacity is a huge confounding factor in looking at temperature stability and summer-winter range. Dr Eschenbach acknowledges this in allowing for the importance of the continental mass at each latitude band. If you draw a global map of summer-winter temperature range it looks like a smoothed land map. The range correlates very strongly with distance from the sea.
First the ocean has the vast majority of the climate’s heat. And of this nearly all is below 10 m depth. While the ocean does have a variable temperature profile sometimes showing a spike at the thermocline, one does not have to argue (against heat principles) for warm water to descend to the cold depths, in order for there to be a role for ocean deep circulation in climate modulation over the short, medium and long term.
For instance, the global deep circulation – quite different from the surface circulation – is driven by cold water downwelling in places such as the Norwegian sea. Climate changes such as in solar-atmosphere-cloud heat balance cause variation in downwelling which in turn, via changes in ocean circulation over various timescales, affect climate form the tropics to the poles. There is evidence that what is called the Atlantic Multidecadal Oscillation involves linkage between Norwegian Sea downwelling, the resultant South Stream deep current and its surface reaction North Atlantic
Drift. The latter – some data suggests – strengthens and weakens during positive and negative AMO phases respectively.
The variation in Arctic ice cover is probably dominated by this oceanic circulation variation – not directly by atmospheric factors.
(e.g. GEOPHYSICAL RESEARCH LETTERS, VOL. 32, L04602, doi:10.1029/2004GL022112, 2005; http://mgg.coas.oregonstate.edu/~andreas/pdf/K/koesters05grl.pdf.)
In general the major oceanic oscillations have a fundamental effect on climate, in profound way as argued by Tsonis:
http://www.agu.org/pubs/crossref/2009/2008GL036874.shtml
and also
http://www.springerlink.com/content/n7111278w0866276/
Clouds and thunderstorms are clearly an important climate component acting for stabilisation and damping – but to argue that the deep ocean is irrelevant to climate is to risk finding yourself in deep .. er .. water.
Bill Illis (06:31:19)
You da man, many thanks.
w.
lgl (12:54:18)
If we were measuring the temperature of the mixed layer, you’d be right. But we’re measuring air temperature, which is related to ocean skin temperature, and has nothing to do with what’s happening 150 metres down.
As someone who has dived extensively, I am very familiar with the diurnal changes and the vertical temperature profile of the ocean. We’re interested in about the top ten metres or so, that’s where the action of the sunlight is greatest. When diving there is often a pronounced thermocline around that depth. Per your figures, for 155 W/m2 to change that by 5°C it takes about 15 days. This is in reasonable agreement with the seasonal lag in peak temperatures.
Willis Eschenbach (13:55:34):
” 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.”
This is the only real question I have had about this article. I agree with the basic premise and I like the way you have segmented the earth in climate forcing zones.
Willis,
I second Bill Illis on correcting for albedo before you calculate sensitivity. The albedo in the Antarctic is even higher than the Arctic according to the figures I’ve seen (Grant Petty, A First Course in Atmospheric Radiation). Also, when looking at changes in albedo over time, it’s a mistake to calculate an average albedo for the planet as a whole and then use that to calculate a planetary average energy flux. You should use the albedo and insolation by latitude to calculate the total flux.
Other points: the forcing from doubling CO2 is not uniform with latitude. It’s highest in the tropics, ~6 W/m2, and lowest at the poles, ~2W/m2. There’s high meridional heat transfer from the tropics to higher latitudes in both hemispheres. We know this because there is observed excess LW radiation to space from high latitudes compared to absorbed solar radiation. The total flux peaks at about latitude 45 N and S at a magnitude of ~5 PW. That’s about 9% of the total energy absorbed by the planet in each hemisphere. Heat transfer by eddy diffusion in the ocean is at least an order of magnitude faster than static diffusion, possibly several orders of magnitude faster. Heat transfer from the surface down is approximately matched by upwelling from the so-called thermo-haline circulation. We know this because the average depth of the thermocline is constant over time.
DeWitt Payne (17:44:10)
The albedo is a response to the forcing, not a forcing. That is why I have not included it.
Cite? Please don’t cite climate models, I’m looking for evidence.
Basically true, but … I don’t see what this has to do with my analysis.
DeWitt Payne (17:44:10) :
Other points: the forcing from doubling CO2 is not uniform with latitude. It’s highest in the tropics, ~6 W/m2, and lowest at the poles, ~2W/m2.
You might want to consider this paper which I stumbled upon a while back
http://ams.confex.com/ams/Annual2006/techprogram/paper_100737.htm
The link is to the abstract, but you can access the full paper by clicking the extended abstract link. The experiment utilized spectral analysis to differentiate the contributions of the various greenhouse gases to downwelling longwave radiation. I would refer you particularly to Tables 3a and 3b which are respectively the seasonal figures for winter and summer. In the cold, air of winter dry CO2 does show a significant contribution to DLW, 34.7 W/m2 of a total of about 150 W/m2, almost 25%. What I found interesting is what happens in the summer when the H2O contribution increases above 200 W/m2. The CO2 contribution decreases not only in relative terms, but also in absolute terms so that it amounts to 10.5 W/m2 out of a total of approx. 270 W/m2. Since this experiment was done in Canada, even the elevated DLW of summer is significantly below the figures I’ve seen quoted for Tropical and subTropical latitudes, which are generally well in excess of 300W/m2. If the suppressive effect of H2O is present at those latitudes, it would seem to suggest that total effect of CO2 would only constitute about 2% the greenhouse effect there and any marginal increases would be even less significant. Admittedly there could possibly be a greater effect from CO2 over large desert areas and the latitude bands in Willis’ graph do seem to suggest that,although that may be mostly a coincidence from what I understand of his analysis.
oops, “cold, dry air of winter”
Richard S Courtney (05:34:21) :
“The paleoclimate record strongly suggests that the climate system is bistable (i.e. stable in each of two states; viz. glacial and interglacial). If this apparent bistability is real then the energy accumulation you assert is an indication of a change from one state to the other.
The fine analysis conducted by Willis Eschenbach only concerns the climate sensitivity of the present interglacial state.
Therefore, your comment is not relevant to the present discussion unless you can provide an explanation for the apparent bistability of the climate.”
Your comment makes no sense. Something had to move the climate from one state to the other, and according to Willis E’s estimate it would take ~300 W per square meter. That’s essentially a second sun in the sky.
Just for general reference, here is a table of the associated black-body (100% emissivity) forcing temperatures associated with the TOA effective solar power radiation (insolation) levels of figure 1 in the main article here. I have calculated these values using 5.670E-8 for sigma, the Stefan-Boltzmann constant. I have also added an estimated background radiation from space, about 4.6E-6 W/m2, to each table value. I believe these temperatures would only be realized on a naked rotating black-body planet with a filtering process sufficient to average the daily energy received. Note that temperatures on the moon reportedly range from -153 to +107 degrees Celsius.
I do not propose to indicate these calculations might be directly applicable to conditions on Earth.
TOA Percent Kelvin Forcing
Insolation Solar Forcing Temperature
W/m2 Constant Temperature (Celsius)
0 0.0% 3.0 -270.2
50 3.6% 172.3 -100.8
100 7.3% 204.9 -68.2
150 10.9% 226.8 -46.4
200 14.6% 243.7 -29.5
250 18.2% 257.7 -15.5
300 21.9% 269.7 -3.5
350 25.5% 280.3 7.1
400 29.2% 289.8 16.6
450 32.8% 298.5 25.3
500 36.5% 306.4 33.3
550 40.1% 313.8 40.7
1370 100.0% 394.3 121.1
Boris (05:16:11) :
You quote me and say as follows:
Richard S Courtney (05:34:21) :
“The paleoclimate record strongly suggests that the climate system is bistable (i.e. stable in each of two states; viz. glacial and interglacial). If this apparent bistability is real then the energy accumulation you assert is an indication of a change from one state to the other.
The fine analysis conducted by Willis Eschenbach only concerns the climate sensitivity of the present interglacial state.
Therefore, your comment is not relevant to the present discussion unless you can provide an explanation for the apparent bistability of the climate.”
Your comment makes no sense. Something had to move the climate from one state to the other, and according to Willis E’s estimate it would take ~300 W per square meter. That’s essentially a second sun in the sky.
***************
My “comment makes no sense”? Please reconsider.
If there are two states then each state has a climate sensitivity. In the absence of other knowledge, there is no reason to suppose that these sensitivities are the same (and it is unlikely that they would be).
Also, something has to induce a transition between the states. And there is no reason to suppose that the sensitivity during a transition would be the same as the sensitivity in either state (and it is unlikely that it would be).
But you are using “Willis E’s estimate” for one state and applying it to both states and the conditions during transitions. Thus, you estimate “it would take ~300 W per square meter” to achieve the transition”.
In other words, you are assuming that “Willis E’s estimate” is applicable to all the conditions of both climate states and their transitional conditions when Willis E does not make such an assumption (he only considers the present state).
The assumption is an adoption of your own: n.b. it is not part of Willis E’s analysis.
Your assumption is very unlikely to be correct.
You say your assumption indicates a need for “~300 W per square meter” to change the system from one state to the other, and this is confirmatory that your assumption is not correct.
So, as I said, “your comment is not relevant to the present discussion unless you can provide an explanation for the apparent bistability of the climate.”
And that explanation must include a justification of your assumption that “Willis E’s estimate” is applicable to all the conditions of both climate states and their transitional conditions.
Richard
One point that needs to be stressed is that Willis’ analysis uses empirical, real-world observations (and so do the Idso’s “simple” analyzes). This bypasses all the “theories” — theories must agree w/real-world observations, not the other way around. There may be issues with what data Willis used and how, etc, but for the “theories” to come up w/sensitivity values so much greater than empirically-derived ones strongly suggests there is something basically wrong and/or grossly incomplete w/the “theories”.
I hope I’m not stating the obvious.
Re: Willis Eschenbach (Mar 2 19:15),
This an assumption on your part for which you provide insufficient justification.
Measured IR spectra looking down from altitude show a much larger dip in emitted flux in the CO2 band at low latitude than at high latitude (Petty, A First Course in Atmospheric Radiation, 2nd edition, figures 8.2 and 8.3, pp223, 225,6). The cause is that the difference in temperature between the effective emission altitude at 667 cm-1 for CO2 and the surface temperature is much higher in the tropics than at high latitudes. If you plug the numbers into MODTRAN, not only is the forcing from doubling CO2 lower, but it takes a smaller change in surface temperature to restore total LW Iout to the original value. MODTRAN is not a climate model. It’s a radiation transfer model that has been validated against observation many times.
Boris (05:16:11):
(reply to Richard S Courtney (05:34:21) )
“Your comment makes no sense. Something had to move the climate from one state to the other, and according to Willis E’s estimate it would take ~300 W per square meter. That’s essentially a second sun in the sky.”
Help me out here. Your reading of Willis E’s climate heat interpretation is one of the following:
(a) for the earth’s climate to drop to glacial again, the sun will have to temporarily leave the solar system, or
(b) you dont believe in ice ages.
To say “something” has to move the climate suggests one has been beguiled by the spurious concept of “forcings”. A system with chaotic-nonlinear / nonequilibrium pattern dynamics, produces system changes between attractors intrinsically or internally. External factors do of course exert an entraining effect. (Although whether you call a factor external or internal depends on what you include in your system.)
Notwithstanding the heat inertia, the nonlinear climate system obeys the log-log power law that states that global climate temperature fluctuations include frequent small ones (e.g. ENSO oscillations), fewer bigger ones (LIA, MWP) and even fewer really big ones _glacial – interglacial. These are indeed as Richard Courtney says, attractors (“strange attractors). It can be a red herring to be fixated on forcings since such systems produce switches / flips intrinsically.
How – where does all the heat go? Thats the challenge to find out. When all is said and done, the future understanding of climate (so far unreached) will be one based on understanding the chaotic nonlinear nature of the system. Not just paying lip service to it, but built on it. The recent work of Tsonis is a good start.
http://www.agu.org/pubs/crossref/2009/2008GL036874.shtml
The “constructal law” proposed by Willis E and Bejan is also pointing in the right direction.
Willis,
Hope you are still following this thread still. I re-read both your articles, the paper by Bejan, and then thought about it in the context of our discussion re the atmospheric window. I concluded that:
1. There is clear evidence to support the atmospheric window (at the lower end at least) and this is easily available.
2. The behaviour of the atmospheric window, in WINTER, is the primary driver of Earth’s thermostat.
Too long to post here and you need all the pictures along with the explanation so please take a look:
http://knowledgedrift.wordpress.com/2010/03/03/theory-of-earths-thermostat-it-is-the-poles-in-winter/
Phlogiston:
I completely agree your comments at (13:26:33).
To ensure that my view is not misunderstood, I again summarise it here as follows.
The basic assumption used in the numerical climate models is that change to climate is driven by change to radiative forcing. And it is very important to recognise that this assumption has not been demonstrated to be correct. Indeed, it is quite possible that there is no force or process causing climate to vary. I explain this possibility as follows.
The climate system is seeking an equilibrium that it never achieves. The Earth obtains radiant energy from the Sun and radiates that energy back to space. The energy input to the system (from the Sun) may be constant (although some doubt that), but the rotation of the Earth and its orbit around the Sun ensure that the energy input/output is never in perfect equilbrium.
The climate system is an intermediary in the process of returning (most of) the energy to space (some energy is radiated from the Earth’s surface back to space). The Northern and Southern hemispheres have different coverage by oceans and, therefore, as the year progresses the modulation of the energy input/output of the system varies. Such a varying system could be expected to exhibit oscillatory behaviour and it does: the mean global temperature increases by 3.8K from July to January and falls by the same amount from January to July each year.
Hence, the system is always seeking equilibrium but never achieves it.
Iimportantly, the oscillations could induce harmonic effects which have periodicity of several years. Of course, such harmonic oscillation would be a process that – at least in principle – is capable of evaluation.
However, there may be no process because the climate is a chaotic system. Therefore, the observed oscillations (ENSO, NAO, etc.) could be observation of the system seeking its chaotic attractor(s) in response to its seeking equilibrium in a changing situation.
Very, importantly, there is an apparent ~900 year oscillation that caused the Roman Warm Period (RWP), then the Dark Age Cool Period (DACP), then the Medieval Warm Period (MWP), then the Little Ice Age (LIA), and the present warm period (PWP). All the observed rise of global temperature in the twentieth century could be recovery from the LIA that is similar to the recovery from the DACP to the MWP. And the ~900 year oscillation could be the chaotic climate system seeking its attractor(s). If so, then all global climate models and ‘attribution studies’ utilized by IPCC and CCSP are based on the false premise that there is a force or process causing climate to change when no such force or process exists. Indeed, glacial and interglacial states may be the result of there being two chaotic attractors.
It seems likely that the climate system exhibits both harmonic oscillation and chaotic attractor seeking.
But the assumption that climate change is driven by radiative forcing may be correct. If so, then it is still extremely improbable that – within the foreseeable future – the climate models could be developed to a state whereby they could provide reliable predictions. This is because the climate system is extremely complex. Indeed, the climate system is more complex than the human brain (the climate system has more interacting components – e.g. biological organisms – than the human brain has interacting components – e.g. neurones), and nobody claims to be able to construct a reliable predictive model of the human brain. It is pure hubris to assume that the climate models are sufficient emulations for them to be used as reliable predictors of future climate when they have no demonstrated forecasting skill.
Hence, empirical assessments such as those of Idso and that of Eschenbach (above) are essential if we are to evaluate the validity of the assumptions which form the basis of existing numerical climate models.
Richard
Willis,
Very elegant idea but I have a couple questions.
1. Why focus on temperature rather than energy?
2. Why focus on atmospheric temps rather than ocean heat content?
3. Isn’t it stealing a base to assume that the northern hemisphere is completely separated thermally from the southern hemisphere?
It seems obvious that you are on the right track, or at least one of the right tracks, but wouldn’t it be better to correlate global cloud cover to ohc? Is that intractable?
Steve Koch (21:44:02) : edit
I would prefer to, but we don’t have the data for that.
I would prefer to, but we don’t have the data for that.
As far as I know, the amount of energy exchanged between the hemispheres is trivially small compared to the amount of energy contained in the hemispheres. If there is data that says otherwise, I’d love to see it.
Even with the current argo floats, we still have only limited coverage for ocean heat content. More to the point, correlating cloud cover with ohc doesn’t give us sensitivity. Likely worth doing, just not what I was doing.
Thanks for the interesting questions,
w.
DeWitt Payne (12:04:21)
Here’s a map of the albedo in February and August.
Note that the albedo is highest in the Southern Hemisphere in February, which is when the sun is warmest in the Southern Hemisphere. Brazil and Southern Africa are white, high albedo.
In the Northern Hemisphere summer, on the other hand, the albedo is high. In August, the upper parts of Africa and South America have high albedo.
Now, unless you want to claim that the changing albedo north and south is making the sun move north and south, I think I’ve made my point.