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.)
Figure 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
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.
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Remarkable and very instructive information!
Was it really not shown before?
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!
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.
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.
Clouds affecting temperatures are well known to us living far north. A cloudless winter night is noticeably colder than a cloudy one.
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.
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.
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.
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.
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.
“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.
“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
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
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
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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
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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.
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.
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.
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
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?
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.