Evidence that Clouds Actively Regulate the Temperature

Guest Post by Willis Eschenbach

I have put forth the idea for some time now that one of the main climate thermoregulatory mechanisms is a temperature-controlled sharp increase in albedo in the tropical regions. I have explained that this occurs in a stepwise fashion when cumulus clouds first emerge, and that the albedo is further increased when some of the cumulus clouds evolve into thunderstorms.

I’ve demonstrated this with actual observations in a couple of ways. I first showed it by means of average photographs of the “view from the sun” here. I’ve also shown this occurring on a daily basis in the TAO data. So I thought, I should look in the CERES data for evidence of this putative phenomenon that I claim occurs, whereby the albedo is actively controlling the thermal input to the climate system.

Mostly, this thermoregulation appears to be happening over the ocean. And I generally dislike averages, I avoid them when I can.  So … I had the idea of making a scatterplot of the total amount of reflected solar energy, versus the sea surface temperature, on a gridcell-by-gridcell basis. No averaging required. I thought well, if I’m correct, I should see the increased reflection of solar energy required by my hypothesis in the scatterplots. Figure 1 shows those results for four individual months in one meteorological year. (The year-to-year variations are surprisingly small, so these months are quite representative.)

december scatterplot reflected radiation vs sea tempFigure 1. Scatterplots showing the relationship between sea surface temperature (horizontal axis, in °C) and total energy reflected by each gridcell (in terawatts). I have used this measurement in preference to watts/square metre because each point on the scatterplot represents a different area. This approach effectively area-averages the data. Colors indicate latitude of the gridcell. Light gray is south pole, shading to black at the equator. Blue is north pole, shading to red at the equator. Click to enlarge

So … what are we looking at here, and what does it mean?

This analysis uses a one-degree by one-degree gridcell size. So each month of data contains 180 rows (latitude) by 360 rows (longitude) of data. Each point in each graph above is one gridcell.That’s 64,800 data points in each of the graphs. Each point is located on the horizontal axis by its temperature, and on the vertical axis by the total energy reflected from that gridcell.

The main feature I want to highlight is what happens when the ocean gets warm. From about 20°C to maybe 26°C, the amount of solar energy reflected by the system is generally dropping. You can see it most clearly in Figure 1’s March and September panels. But from about 26° up to the general oceanic maximum of just above 30°C, the amount of solar energy that is reflected goes through the roof. Reflected energy more than doubles in that short interval.

Note that as the ocean warms, the total energy being reflected first drops, and then reverses direction and increases. This will tend to keep ocean temperatures constant—decreasing reflections allow more energy in. But only up to a certain temperature. Above that temperature, the system rapidly increases the amount reflected to cut down any further warming.

Overall, I’d say that this is some of the strongest evidence that my proposed thermoregulatory system exists. Not only does it exist, but it appears to be a main mechanism governing the total amount of energy that enters the climate system.

It’s very late … my best regards to everyone, hasta luego …

w.

[UPDATE] A commenter asked that I show the northern and southern hemispheres separately. Here is the Southern Hemisphere

december SH scatterplot reflected radiation vs sea temp

And the Northern. The vertical lines are at 30.75°C, nothing magical about that number, I wanted to see the temperature shift over the year and that worked.

december NH scatterplot reflected radiation vs sea temp

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bacpierre

Remarkable and very instructive information!
Was it really not shown before?

Wyguy

Thank you Willis, a good analysis that an idiot like me can understand. You do good work.

Dear Wiilis, you nailed it! Thanks

That’s really interesting.
Thanks, Willis, you’re doing a great job!

markx

Damn. Those are works of art in themselves!
Talk about a picture (or four) worth a thousand words. This barely needs words at all.
You could not have a clearer picture painted of your equatorial regulatory mechanism.

RC Saumarez

I have some problems with your analysis.
You state that cumulus clouds are relatively short lived. Yet you are, if I understand you correctly, using monthly samples of ceres data.
This suggests that you may be using aliased data, in which case your calculations may not be reliable.

SasjaL

Clouds affecting temperatures are well known to us living far north. A cloudless winter night is noticeably colder than a cloudy one.

Bill Illis

The Real Earth.
The climate modelers can’t model clouds. Well, it is right there.
It is also says that the cloud feedback is not a linear +0.7 W/m2/C as is assumed in the theory but is a much more complex function depending on temperature that most likely goes strongly negative at the 30C. You now have the short-wave part of the function. Probably easy enough to do the out-going long-wave component now as well. Overall, clouds reflect -54 W/m2 of solar radiation and hold in +32 W/m2 of long-wave for a net -22 W/m2 of impact. One needs both components to arrive a net solution function.

Steve Keohane

Thanks Willis, graphic presentations are the best.

In the areas concerned:
i) In the tropics with a temperature range of 20C to 26C one generally sees low cloud burning off as the temperature rises.
ii) At about 26C cloudiness is at its minimum and reflectivity at its lowest.
ii) From 26C upward higher level convective clouds build up rapidly and reflectivity increases exponentially.
There is no doubt that Willis’s Thermostat Effect is present and highly effective but one needs to extend the general principle across centuries to deal with events such as the MWP, LIA and Current Warm Period.
In itself it is not an adequate explanation for global climate variability over centuries.

markx

Stephen Wilde says: October 6, 2013 at 4:59 am
In itself it is not an adequate explanation for global climate variability over centuries.
True enough. It is more of a very nice explanation for the amazing stability of the system.
What is always being searched for are the events or drivers that force the system away from the base level to which it eventually returns. From these prognostications arose the GHG line of research, but it is hard to visualize CO2 as ‘the’ driver, now, or more so in the distant past. Willis’ charts would indicate that ‘the system’, in terms of both latitude and sea surface temperature, has a lot more buffer in it yet.
An important point of course is that in ‘recent’ times, (the last half million years or so) glacials are the base level, and interglacials (ie, right now) the exception. Makes you wonder how he prospect warming was put up as a disaster. The alternative is …um … chilling.

kirk creelman

Nice work Willis. That!…is a hockey stick.
Do you only count grid-cells that contain water? Why not correct for grid surface area? Seems like the polar grids would be extremely reflective if you did.
Again, nice work. Thanks.

Dixon

That does look compelling Willis, surely water vapour is the planets thermostat? In getting to where Climate science currently is (or is not!), did someone not already set up a simple model with reasonable resolution of land and ocean albedo, air and water thermodynamics and some generalised ocean currents and atmospheric circulation. Add in incoming solar radiation and parameterization of clouds and ice cover? Ideally they would have elevation in too (because I suspect ice coverage at mid and tropical latitudes will be important, especially over long timescales). Did they discard this model because it failed dismally – ran away to a snowball planet, or boiled off the oceans? It seems to me the planet is naturally buffered to the logical extremes of current poles and tropics. Lovelock did something similar with Daisyworld, but in this model clouds and ice would be the white daisies, vegetated continents and open ocean the black daisies. I’m not suggesting you do this – I know how busy you are and really appreciate your observations and writing, I just wish I was smarter and could run the numbers myself or had better access to the literature.

lgl

“And I generally dislike averages, I avoid them when I can”
Hehe, especially since your own work shows an average positive feedback of +0.7 W/m2/C globally. Much better then to try changing the focus to some areas of the tropics where the regulation works. You are only fooling yourself and your hardcore followers.

Mike M

“But from about 26° up to the general oceanic maximum of just above 30°C, the amount of solar energy that is reflected goes through the roof.”
Thus suggesting a reason for what appears to have been an upper limit to earth’s temperature over million of years: http://geocraft.com/WVFossils/PageMill_Images/image277.gif

gopal panicker

i have spent a lot of time in my younger days watching clouds in the tropics…at 7500 ft altitude a lot of them are close by…its fun trying to figure out what they look like…because they change all the time…but trying to calculate this stuff is a fools game

Helium

I might remark on the fact that Roy Spencer has a recent blogpost along similar lines. Might be worth the time to check

lgl says:
October 6, 2013 at 5:48 am
your own work shows an average positive feedback of +0.7
================
that would be consistent with the earth’s average temperature being lower than the local minimum shown in the graphs at around 25C.
notice that the curves are consistent for the N and S hemispheres during the equinox, and substantially different during the solstice. this argues strongly that feedback is not constant, rather it is a non-linear function of temperature.
this non-linear dynamic feedback is not the mechanism that causes the earth’s temperature to vary, rather it is the mechanism that returns the earth’s temperature to the habitable range for life, in the face of other mechanisms that try and force the temperature outside this range.

Willis – I don’t want to knock this, I think what you are doing is fascinating and a truly worthwhile exercise. But I’m not convinced that it shows what you claim that it shows.
Looking at the southern hemisphere, low latitudes (light grey), there is much more cloud in summer (Dec) than in the other seasons. I assume we are looking at cloud cover not snow and ice. There is the same effect in the NH but less marked. To my mind, we are looking at a seasonal effect, and it does not necessarily reflect – in your words – “what happens when the ocean gets warm“. ie, it shows what happens when the ocean warms seasonally and locally, but it doesn’t show what happens when the planet warms up over a multi-year period. The point is that we don’t know what the drivers of cloud cover are, and the absolute sea surface temperature may be a minor driver. If the drivers include, for example, the relationship between various weather factors in neighbouring regions, then no inference can be drawn from your analysis wrt any multi-year period.
Similarly, looking at the tropics, there is a lot more cloud there than elsewhere. That is why your graph shows that “the amount of solar energy that is reflected goes through the roof” in the tropics. We may simply be looking at a regional effect, driven by things like winds and currents and the relationship to nearby regions. ie, the absolute sea surface temperature may be a minor driver. Again, I don’t think that any inference can be drawn from your analysis wrt any multi-year period.
In summary, you appear to be finding seasonal and regional effects, for which there may be seasonal and regional drivers other than absolute sea-surface temperature, and which therefore may have no implications wrt multi-year global temperature changes.
As Stephen Wilde said, “ In itself it is not an adequate explanation for global climate variability over centuries.“.

Mike M says:
October 6, 2013 at 5:55 am
Thus suggesting a reason for what appears to have been an upper limit to earth’s temperature over million of years: http://geocraft.com/WVFossils/PageMill_Images/image277.gif
===========
Agreed. Even if the earth’s temperature rises such that more and more regions become tropical, regionally the oceans will keep temperatures locally below 30C except for those areas away from the oceans.
This also shows how averages can be misleading. having one foot in the freezer and the other in the oven is on average comfortable.
What we are seeing globally is that the north pole is warming, while most of the rest of the globe remains largely unchanged. This cannot be due to CO2, because CO2 is reportedly well mixed.
However, it has been strongly argued by climate science that the MWP was not global, that it was mostly a warming of the N hemisphere. This is similar to what we are seeing now – the warming is regional – specific to the N hemisphere.
This suggests that the MWP and the current warming are related by a common cause. This cannot be human created CO2, because the MWP took place during a period of low industrialization.

David Longinotti

This is good work – very strong confirmation of the regulatory effect at higher sea temperatures. One expects the Dec and Jun plots to be similar but color-inverted because this pair represents similar orientations of the earth’s axis relative to the sun, but with respect to different poles. And this shows up well in the plots. Also, from the plots the southern hemisphere seems to generally reflect more energy at the lower sea temperatures than does the northern – due perhaps to different ratios of sea area relative to land? This effect is strongest in the Sep plot, but seems evident in all of them.

Robin Kool

Hi WIllis.
I share your love for this kind of graphic that organizes a lot of measurements instead of averaging them out.
These graphs are very convincing for your hypothesis of clouds as temperature regulators.
It is great fun to witness your ongoing research. The birth of a theory.

kirk creelman

After further thoughts..and playing devils advocate….
Sea surface temp is closely related to latitude. Therefore, one could replace your graphs x axis with latitude and it would likely look fairly similar. This then just shows that the equator has more clouds, then there is a band of fewer clouds followed by a seasonal mid latitude band of variable cloudiness. This pretty much covers standard distribution of atmospheric cell circulation. No causation in other words.
As for thermo regulation, there is nothing in the charts to show that there is regulation going on. Only that it is max.30c at the equator and less as you move away. One could shift the temperature scale 10 degrees and conclude that “see after 35 we get more clouds so it will never go over 40.
I think you need to show tighter causation and remove the latitude bias somehow.
Cheers
kirk

Pamela Gray

Long term land temperature trends still need to be examined in relation to this work. Have you tried narrowing the area to just the tropical equatorial belt to capture straight on solar irradiance? And how far back can you go with data? I would really like to see this measure of cloud presence through several ENSO events. And especially since 1970. A decrease in clouds (decreased reflectance) allows the oceans to recharge and would predict warming to come, something that Tisdale has explained many times. If La Nina events predominated (as could be deduced from decreased equatorial clouds/reflectance), it would predict eventual long term warming to the degree we have experienced. Additionally, the degree of recharge would diminish as the Sun’s angle varies from 90 degrees, so the “sweet” spot would need to be determined.
So narrow the latitude band and plot reflectance against time over several decades or at least for the length of time we have reflectance data?

Robin Kool

October 6, 2013 at 6:28 am
Mike Jonas says: “To my mind, we are looking at a seasonal effect, …”
Hi Mike.
The seasonal effect is very evident at the Poles, and much less so in the Tropics.
Remember, in December the South Pole receives sunlight 24 hrs a day.
In June it is dark 24 hrs a day, ergo: no sunlight to reflect.

Russ R.

It’s pretty evident where the temperature “hits the wall”.
The bifurcation in the northern hemisphere December data plot is a bit odd. Is it possibly due to a a differential between the Atlantic and Pacific basins?

Mike M

ferd berple says: “… has been strongly argued by climate science that the MWP was not global, that it was mostly a warming of the N hemisphere.”
Operative phrase there is “has been”. They are finding more and more empirical evidence that the MWP was indeed global. Back at the peak of the MWP, Western Europe was clearly one of the most advanced regions of human civilization for science and written language so of course there is preponderance of written evidence that a MWP occurred there.
For example, Incans had no written language. Fortunately though, their climate history was written for them in sedimentation:
“These increasingly warmer conditions allowed the Inca and their predecessors the opportunity to exploit higher altitudes from AD 1150, by constructing agricultural terraces that employed glacial-fed irrigation, in combination with deliberate agroforestry techniques. ”
http://wattsupwiththat.com/2009/07/08/the-medieval-warm-period-linked-to-the-success-of-machu-picchu-inca/

bobbyv

elegant

Dare I say that the factor which determines that maximum temperature is the weight of the atmosphere pressing down on the surface water molecules?
For the phase change to water vapour to occur the energy available has to overcome both the natural attraction between water molecules AND the downward pressure that supplements that attracting force.
The greater the weight of the atmosphere the more energy required and the higher the temperature needs to be.
There then comes a point where the temperature becomes sufficiently high that ALL additional energy added is absorbed in the phase change and that is the maximum temperature achievable.

DavidA

If you blew these up to 3m x 3m and put them on the wall in an art gallery I reckon you’d get some good offers.

Crispin in Waterloo but really in Yogyakarta

Willis you ask what else we might get from this data. One thing is (though I love the scatter plots) is to sum the terawatts per latitude and get a plot of reflected energy. This is the same sort of chart that Monckton uses for showing the hotspot is not there: poles on each end, equator in the middle.
I am dying to know if you might demonstrate (by bundling the dots) that the reflection of insolation is the reason the hot spot is not there. There may be, for example, a spike in wattage in the tropics that rises or falls faster than the change in the incident angle of incoming energy.
There could be one terawatt line plotted per deg of average sea temp, or the local grid cell sea temp could be factored in to spot how the reflected energy varies away from the incident angle locally.
The hot spot idea is base on the premise of constant incoming insolation. Maybe it is not so constant. If clouds cool the ground, the IR is simply not there to be captured by the increased CO2. Maybe the CO2 would have created a hot spot after all, but the self-regulation point was reached and heat shedding kicked in.
Thanks for elucidating.

Paul

This is why the warmistas always say that the poles heat more than the tropics.

RC Saumarez

There is a potential problem with the analysis presented in this and earler posts that depends on the temporal scale of the processes involved.
1) Calculations have been on a 1×1 degree grid. Cloud albedo can vary in hours at this scale (60nautical miles). Therefore there is a highly variable downward radiation affecting surface temperatures.
2) The temperature used by historical series have a coarse sampling time and are aliased.
3) Therefore one is trying to resolve processes, i.e.: feedback, that have a scale of hours with data that has much longer sampling intervals.
4) Thuis the temporal scale of the process and the dynamics of the feedback MUST be specified.
5) Calculations of anything related to feedback that uses undersampled data may contain large errors.
Therefore this work needs a clear statement about the exact properties of the data.

Your main point is:
“Note that as the ocean warms, the total energy being reflected first drops, and then reverses direction and increases. This will tend to keep ocean temperatures constant—decreasing reflections allow more energy in. But only up to a certain temperature. Above that temperature, the system rapidly increases the amount reflected to cut down any further warming.”
The graphs don’t show that. At and above that “certain temperature”–say 27 or 28 C–the graphs don’t show a “rapid increase” in the amount reflected, at all; they show a 4- to 5-fold VARIATION in the amount reflected (over the grid), with little or no accompanying variation in sea surface temperature (SST)–that is, no correlation between the two. Similarly, for the two equinoctial graphs (Mar and Sep), in the lower range of sea surface temperatures, below 27 or 28 C, the variation in SST is accompanied by little (or much smaller) variation in the reflected radiation. What you have is basically two straight lines, a horizontal one over most of the SST range, and a vertical one at the high end. That means you have picked the wrong two variables to establish a correlation between, and there are entirely other causes for the variations in both of them. The two solstitial graphs (Dec and Jun) basically show that the north and south hemispheres switch places with respect to the effects of the incident solar energy, at those two points of the year–obviously, the Sun shines more intensely on one hemisphere, then more intensely on the other. And note that the seeming correlation between reflection and STT in those two graphs is in one direction in the north and the other direction in the south–again, no substantial, lasting correlation between the two picked variables at all, over the whole globe.
One can certainly make the case that one is seeing a stable system in these graphs (although they are obviously not the clearest representatives of such global stability, with their swirls and vertical take-off at the highest SSTs), but definitely NOT due the physical cause and effect you are implying.
Again, my Venus/Earth temperatures comparison is the definitive correction to climate science, and it shows no global cloud effect on temperatures, as I just got through commenting upon–again–at Steven Goddard’s site. Clouds and albedo are just another red herring (false “settled science”) in climate science, globally. There are no competent climate scientists, as the above post, and the general belief in false dogma among consensus scientists, once again shows.

MinB

Thanks, DavidA “If you blew these up to 3m x 3m and put them on the wall in an art gallery I reckon you’d get some good offers.”
I’m an artist with exhibits scheduled solid for the next 8 months. I was looking for an inspiration for a new abstract piece, I think I’ll use these scatter plots just for that purpose.

Mike M

Paul says: “This is why the warmistas always say that the poles heat more than the tropics.”
I thought everybody was on board with that? But anyway, in their case, not “always”… not when discussing how tornado and hurricane energy are reliant upon the differential between the temperature / humidity of air masses. More warming in the higher latitudes produces a smaller difference = warming is good!

Henry Clark

Negative feedback is definitely observed, as in feedback which relatively opposes the temperature change which would occur from an external forcing change in the absence of feedbacks. Negative feedback is a dampener, resulting in low climate sensitivity.
If ocean temperature increases, it is one of the factors on cloud cover. For example, as a thought experiment, if the oceans were magically cooled all over their surface to just slightly above freezing, evaporation would plummet towards relatively nil; cloud cover would diminish to little; and, with few white clouds, Earth’s albedo would approximately halve towards 0.15 or so, much less than the normal value of around 31% to 35% average reflectivity, which in turn would lead to more sunlight absorption opposing the original magical cooling.
Of course, the preceding is a simplified thought experiment (like cooling still further would cause a different effect of albedo increase by ice growth, “snowball Earth”). But the point is that, if all else was equal, “trying” to cool the ocean surface results in an opposing effect of decreased albedo (increased absorption of sunlight). Conversely, “trying” to warm the ocean surface results in an opposing effect of increased albedo (decreased absorption of sunlight).
Dr. Lindzen once noted how ocean surface temperatures near the equator appear to never have been much higher than now in billions of years of past Earth history, supporting negative feedback as if a thermostat. I forget the exact figure, but it was something like never more than a couple degrees Celsius higher, based on mineral deposits IIRC, mentioned in some early article of his. (Others have observed that even the era of the dinosaurs had its extra warmth primarily by warming further from the equator, including arctic warming).
In a later 2010 report to part of Congress, Dr. Lindzen made a presentation (with the most relevant section on pages 35 through 47) in which negative feedback seen in CERES and ERBE data fit a low estimated climate sensitivity of around 0.22 K per W/m^2 radiative forcing change (as in 0.8 degrees Celsius for a 3.6 W/m^2 change).
A copy of that report is within http://wattsupwiththat.com/2010/11/18/profess-richard-lindzens-congressional-testimony/
at http://wattsupwiththat.files.wordpress.com/2010/11/lindzen_testimony_11-17-2010.pdf
Especially considering the limited number of actually significant digits in the prior example, more a single significant digit then the nominal 0.22 K per W/m^2 written above, it approximately or nearly overlaps the low end of Dr. Shaviv’s approximate estimate of 0.26 to 0.44 K per W/m^2 climate sensitivity (of 0.35 +/- 0.09 K per W/m^2).
The latter is discussed at http://www.sciencebits.com/OnClimateSensitivity . Climate sensitivity, to be most precise, is not exactly a constant over different time scales and magnitudes, not just a simple linear response. Still, the approximation is often not too bad if properly observing low climate sensitivity and not falsely assuming it to be high. A number of illustrations, over time periods of a few years to vast eons, are in figure 2 of the prior link, showing how observation-based climate sensitivity estimates become relatively consistent (and low) once properly considering cosmic rays. That is since the larger forcing of TSI+GCR variation makes low climate sensitivity fit historical records, unlike CAGW dogma of pretending nothing other than near-constant TSI matters. (And illustrations in http://img176.imagevenue.com/img.php?image=81829_expanded_overview_122_424lo.jpg highlight why to consider both).
With low climate sensitivity from negative feedback, a large powerful forcing is required for a small change in temperature, and that is what is observed in the historical record over the centuries.

Theo Goodwin

Brilliant, brilliant work, Willis. You are showing the climate scientists what genuine physical science looks like. Your work on clouds alone, not to mention your thermostatic hypothesis, is the best empirical work on how clouds change in response to temperature and how those changes can affect temperatures. The very existence of your work drives home just how uninterested mainstream climate scientists are in the facts of cloud behavior even though those facts alone could reveal whether increased manmade CO2 causes warming.
For all those who have no idea what a physical hypothesis is nor any idea what evidence for a physical hypothesis looks like, please study Willis’ Thermostatic Hypothesis and then this article for an excellent example of physical evidence.

Markopanama

Once more Willis is corroborating what we here in Panama experience daily. Over the course of a year, average day and night temps generally (8 months) don’t vary by more than one or two degrees F. The maximum variation is no more than ten degrees, and that is a lot. One thing you never see in Panama is a weather thermometer, nor are temps reported on the news.
That a thermostat is working is blindingly obvious to anyone who lives in the tropics. Clouds cover varies wildly, as does rainfall (from 200 to over 300 inches per year) depending apparently on the ENSO cycle. Interestingly, the temps are constant whether we are getting the Norherly trades off the Caribbean between November and May, or the huge thunderstorms off the Pacific when we are sitting under the ITCZ during the rainy season.
What effect the thermostat has on global weather is a matter for exploration, as Willis has started to do. Personally, my hypothesis is that for global climate to get seriously off course, as in warming, you would see changes in the tropical thermostat first. That the water vapor/cloud thermostat has operated over many millions, if not billions of years, neatly explains the stability of Earth’s climate through asteroid strikes, volcanic havoc, continental drift, changing GCRs etc.
Occam’s razor rules.

Dave in Canmore

I love the fact that you have dispensed with averages as well. When trying to identify a real life process such as a thermoregulatory mechanism, averages will lead you away from the mechanism not towards it. More scientists should ask themselves if an average has any physical meaning in the real world.

Jim G

Willis,
I keep looking for something simple, like a nice large sample size analysis of cloud cover vs surface temperature. There should be some sort of sinusoidal mechanism ie, temp goes up, clouds build, temp goes down, clouds dispate, temp goes back up, etc., etc. Did I miss it somewhere? You have explained all the downdwelling/radiative/reflective/yata yata. What about some direct stuff for us old engineers. The how and why analysis are great, but does it work? Need data showing it working.

Henry Clark says:
“Dr. Lindzen once noted how ocean surface temperatures near the equator appear to never have been much higher than now in billions of years of past Earth history, supporting negative feedback as if a thermostat. I forget the exact figure…”
Prof Lindzen states that the planet’s temperature at the equator has not changed by more than ±1ºC over the past billion years. I can get you the exact quote if you like.

Paul Linsay

“Stephen Wilde says:
October 6, 2013 at 7:23 am
Dare I say that the factor which determines that maximum temperature is the weight of the atmosphere pressing down on the surface water molecules?”
I think that you are wrong here. If what you say is true it would be impossible to boil water at sea level anywhere.
The maximum temperature is determined by the solar flux which in turn reaches its maximum in the tropics. The observed temperature is the equilibrium point between the solar flux and evaporation. The heat carried away by evaporation just balances the heat input of the solar flux. If you put a pot of water on the stove but set the heat to a very low level, it won’t boil for the same reason, though it will be warmer than room temperature.
The exact temperature of the air will be determined by the humidity of the air, which is determined by air pressure, and by the wind speed across the surface of the water.

Jim G

Willis,
Idea. What if you take your existing data, pick some specific location, put time on the x-axis and reflective data on the y-axis-left and temp on the y-axis-right. Do this for several specific locations. Same data, different presentation. Do a few different locations again. Assumption you are using now is the same, ie reflective data= more or less clouds. Kind of ignores your other radiative factors in that you are not showing possible effects of cloud composition, altitude and thickness but I’ll bet there is a sinusoidal mechanism going on over time and something we might learn from it regarding your regulatory engine..

The Ghost Of Big Jim Cooley

Too late Willis, Bob Geldof says our time is up! http://www.dailymail.co.uk/news/article-2446613/The-end-world-nigh-says-Bob-Geldof-predicts-climate-change-wipe-humans.html#comments Here in England, we call people like this a ‘prat’.

HankHenry

Studies have demonstrated that earthshine on the moon is variable not constant. This means that earth’s albedo is not constant. Not only is there a daily and annual variance but a longer term variance which at this time would best be described and categorized as “natural” variance. While not tremendous the effect on climate and climate models is probably important. It is also not an unknown phenomenon being first considered by Galileo himself.

Henry Clark

dbstealey says:
October 6, 2013 at 8:50 am
Prof Lindzen states that the planet’s temperature at the equator has not changed by more than ±1ºC over the past billion years.
Indeed. Actually that sparked my memory enough to do a keyword search successfully finding the following again:
http://www.cato.org/sites/cato.org/files/serials/files/regulation/1992/4/v15n2-9.pdf
“Global Warming: The Origin and Nature of the Alleged Scientific Consensus” by Dr. Lindzen
noting
There is ample evidence that the average equatorial sea surface has remained within plus or minus one degree centigrade of its present temperature for billions of years

Coldish

If the gridcells are each one-degree by one-degree quadrilaterals, their area varies systematically with latitude from a maximum at the equator to a minimum at the poles. I don’t know how that affects your scatter plot, but I think I’d be happier with an equal-area grid.

I know this is off topic even though related to the contents of the post, but I can’t help but think of two things looking at the Figure 1 scatterplots: the elevator scene from “The Shining” and a Rorschach (or Rorschenbach) test. Top left I see an alligator snapping turtle, hawksbill sea turtle, or any raptor. My work here is done.

Interestingly you can see the difference due to the south pole having a persistent ice cap and the north pole having transient periods of open ocean with less reflective ice in general.
At least that’s the biggest thing that stood out to me as interesting.