Guest Post by Willis Eschenbach
There’s a new study in PNAS, entitled “Observational determination of albedo decrease caused by vanishing Arctic sea ice” by Pistone et al. Let me start by registering a huge protest against the title. The sea ice is varying, it isn’t “vanishing”, that’s just alarmist rhetoric that has no place in science.
In any case, here’s their figure 4B, showing the decrease in albedo from the “vanishing” sea ice:
Figure 1. Graph from Pistone2014 showing CERES albedo data (green, solid line) for the ocean areas of the Arctic.
The authors say:
Using the relationship between SSM/I and CERES measurements to extend the albedo record back in time, we find that during 1979–2011 the Arctic darkened sufficiently to cause an increase in solar energy input into the Arctic Ocean region of 6.4 ± 0.9 W/m2, equivalent to an increase of 0.21 ± 0.03 W/m2 averaged over the globe. This implies that the albedo forcing due solely to changes in Arctic sea ice has been 25% as large globally as the direct radiative forcing from increased carbon dioxide concentrations, which is estimated to be 0.8 W/m2 between 1979 and 2011.
The present study shows that the planetary darkening effect of the vanishing sea ice represents a substantial climate forcing that is not offset by cloud albedo feedbacks and other processes. Together, these findings provide direct observational validation of the hypothesis of a positive feedback between sea ice cover, planetary albedo, and global warming.
So … how are they going about making that case?
Let me start by saying that looking at albedo as they are doing is a very roundabout and inaccurate way of handling the data. The CERES dataset doesn’t have an “albedo” dataset. Instead, they have a dataset for downwelling solar, and another dataset for upwelling solar. The problem is that when the numbers get very small, the values of the calculated albedos get more and more inaccurate. Albedo is reflected solar divided by downwelling solar. So when you get down to where there’s almost no sunshine, you can get things like a gridcell that averages 0.2 W/m2 of incoming sunlight over some month, and reflects 0.4 W/m2 … giving us an impossible albedo of 2.0 …
It’s not clear how Pistone et al. have handled this issue. The way I work around the problem is to calculate the average upwelling reflected sunlight for the Arctic ocean area, and divide that by the average downwelling sunlight for the Arctic ocean area. This gives me an overall average albedo. I get slightly different numbers from theirs, and I am unable to replicate their results. However, I do get about the same trend that they get over the period, a decrease in the albedo of about 1.5% per decade. However, I don’t particularly trust those albedo numbers, averages of ratios make me nervous.
For this reason, I use a different and simpler measure, one which Pistone et al. mention and quantify as well. This is the actual amount of sunlight that makes it into the climate system. The authors call this the “total solar energy input”, and I will follow the practice. And qualitatively, my results agree with theirs—the amount of sunlight absorbed by the arctic has indeed increased over the period of the CERES data, 2000-2013. Figure 2 shows both the clear-sky and the all-sky arctic total energy input:
Figure 2. Increase in solar energy input to the Arctic ocean areas, 2000-2012. Clear sky in black, all sky in red. Units are area-weighted watts/m2.
In addition to the overall trend in all sky solar input (green line), you can see the peak in energy input in 2007, with the high solar input corresponding to very low ice areas. Overall, Figure 2 shows an even greater increase in energy input than Pistone2014 have estimated over the entire period. They report an increase in Arctic solar energy input over the ocean of 0.21 W/m2 over 32 years … and the CERES data shows an increase of 0.3 W/m2 per decade.
So we’ve established that their first claim, of increasing solar energy input to the Arctic ocean area 2000-2012, is true, and perhaps even underestimated. And this is quite reasonable, since we know the sea ice has decreased over the period … but what about their second claim? As you may recall, this was (emphasis mine):
The present study shows that the planetary darkening effect of the vanishing sea ice represents a substantial climate forcing that is not offset by cloud albedo feedbacks and other processes. Together, these findings provide direct observational validation of the hypothesis of a positive feedback between sea ice cover, planetary albedo, and global warming.
The CERES data agrees that the increase in solar energy input from reduced ice cover is not counteracted by Arctic clouds … nor would I have expected it to be counteracted by clouds in the Arctic. As I have discussed, well, more than once, the main climate control system is in the tropics. So if this increase in absorbed energy were counteracted by clouds, my hypothesis is that it would happen be in the tropics. I’ll return to this in a moment.
First, however, they’ve claimed that their results establish the existence of “a positive feedback between sea ice cover [and] planetary albedo”. Since the planetary albedo controls the total solar energy input to the globe, let’s take a look at the same data as Figure 2, total solar energy input, but this time for the entire planet …
Figure 3. Available solar energy at the top of atmosphere (red) and total solar energy input to the globe (blue), 2000-2012. Units are area-weighted watts/m2.
So their claim of increased solar energy input to the Arctic from reduced sea ice is true … but their claim that there is “a positive feedback between sea ice cover [and] planetary albedo” is falsified by the CERES data. The total solar energy input (blue line above), and thus the planetary albedo, is amazingly stable over the time period. There is no feedback at all from the changes in the ice.
To illustrate the stability, Figure 4 shows a breakdown of the total solar input data (blue line above). It’s divided into panels that from top to bottom show the data itself, the seasonal pattern, the trend, and the residuals of the global solar energy input:
Figure 4. Decomposition of the solar energy input signal into trend, seasonal, and residual components. Red scale bars on the right indicate the relative scale of the individual panel. Units are area-adjusted W/m2.
I’ve written before about the amazing stability of the climate system. This is another example. In the past people have objected that the system is forced to be stable, because over time, energy out must generally equal energy in.
But the global solar energy input, the amount of the available solar energy that actually makes it into the climate system, is under no such constraint. There is nothing that it must balance to. Solar energy input is a function of the albedo, which is determined by clouds, snow, ice, vegetation, and wind, and all of these are constantly varying in all parts of the planet … and despite that, the swings of the trend are no greater than ±0.3 w/m2 over the period. The maximum monthly deviation from the seasonal average is a mere one W/m2, and the standard deviation of the residuals (data minus seasonal) is half a watt/m2.
So … how does it happen that we have a strong increase in solar energy input in the Arctic, but the global energy input stays the same?
Well … as I mentioned above, the tropics. Over the period 2000-2012, during which the Arctic received increased solar energy input, here’s what’s happened in the tropics:
Figure 5. Total solar energy input, all skies, tropics. Units are area-adjusted W/m2
As I hypothesized, the control is happening in the tropics. Pistone et al. note that the Arctic solar input is going up because of decreased sea ice … but they did not notice that at the same time, the tropical solar input is going down because of increased clouds. And the net sum of all of the changes, of more energy being absorbed in the extra-tropical areas and less energy being absorbed in the tropics, is … well … no change at all for the globe. It all averages out perfectly, with little change in either the monthly, annual or decadal data.
Coincidence? Hardly.
This is about as neat a demonstration as I can imagine in support of my hypothesis that the system is not ruled by the level of the forcings—instead, it is regulated by a system of interlocking emergent climate phenomena. A number of these phenomena operate in the tropics, and they have a curious property—the warmer the planet gets, the more that they cut down on the incoming solar energy.
So at the end of the day, we find that the claim of the authors that increased solar input to the Arctic is connected to the planetary albedo to be true … except that it is true in exactly the opposite of the direction that they claimed. When more energy is absorbed in the Arctic, less energy is absorbed elsewhere.
In closing, I want to highlight what it was that got me interested in climate science to begin with. I wasn’t interested in finding out why the global temperature had changed by something like ± 0.3°C over the 20th century.
Instead, I was interested in finding out why the global temperature had only changed by ± 0.3°C over the 20th century. I was amazed by the stability of the system, not the fact that it had varied slightly. So let me close with a graph showing the total global solar input residuals, what remains after the seasonal cycle in total solar input is removed.
Figure 5. Residual total solar input after the seasonal cycle is removed. Dotted lines show the inter-quartile range. Smooth curve is the loess trend line.
The monthly deviation from the seasonal cycle is tiny. Half the months are within a third of a W/m2 of the seasonal average … a third of a watt, to me that’s simply amazing.
Now, you might disagree with my hypothesis that the planet is thermoregulated by emergent climate phenomena such as thunderstorms, El Nino, and the PDO.
But the stability shown in the above graphs surely argues strongly for the existence of some kind of regulatory system …
My regards, as usual to everyone.
w.
AVISO: If you disagree with what I or anyone says, please quote the exact words you disagree with. It allows everyone to understand exactly what you are objecting to.
DATA AND CODE: You’ll need the CERES data (227 Mb) , the CERES surface data (117 Mb) and two support files (CERES Setup.R and CERES Functions.R) in your R workspace. The code is Arctic Albedo.R, it should be turnkey.
[UPDATE]
Well, y’all will find this funny, I assume … following up on the question of the net effect of the loss of the sea ice that came up below in the comments, I decided to see what was happening with the upwelling longwave. We’ve established that the loss of the ice increases the total solar energy input … but what about the energy loss via longwave? (Yr. humble author slaps forehead for not thinking of this sooner …)
As you can see, the change in solar energy input is more than offset by increased losses … so the net effect of the melting sea ice is a net energy loss of 0.05 W/m2 per decade.
Note again the stability over time. Note also that this part of the system is not constrained by any need for solar input and longwave output to be stable, or to have the configuration they have. The average solar input is 30 W/m2, and the average longwave loss to space is 63 W/m2 … and despite the marked changes in ice cover over the period, they’ve only changed about 1% per decade over the period …
Gotta love the climate, always more surprises …
w.
[UPDATE II]
Some folks have said that there is a problem with my area-weighting, so let me explain exactly what I did.
The data exists in 180 latitude bands. The center of the bands start at -89/5° (south) and end up at 89.5° (north). To area-weight the data, we want to adjust the results for each gridcell by the area.
What we want to do is adjust the results to give what you would get if they had the size of the average gridcell. Now the area is proportional to the cosine of the mid-latitude. So what we do is multiply each gridcell result by
area of the gridcell / area of the average gridcell
This give each gridcell the value it would have if it were of average size. The effect of tiny gridcells is reduced, and the effect of large gridcells is increased.
Now, what is the average cell size? Well, if we integrate Cos(x) from zero to pi/2, we get 1. So the average gridcell size is 1/(pi/2) = 2/pi ≈ 0.637.
As a result, the weighting factor by which we multiply the gridcell value is, as you recall:
area of the gridcell / area of the average gridcell
which is equal to
cosine of the gridcell midlatitude / 0.637
Once you’ve multiplied the data by those weighting factors, you can compare them directly, as they are all adjusted to the average gridcell size.
The way to test if you’ve done this correctly is to see if the plain vanilla average of the newly-weighted dataset is correct. For example, see the average available solar (~340 W/m2) and solar input (~240 W/m2) values in Figure 3. They are simple averages of weighted data.
Note that there are two ways to do the weighting.
The first is to do all calculations (trends, etc) using the unadjusted variables. Then to get an average, you use what is called an “weighted mean”, which weights the data on the basis of gridcell area as it calculates the average.
The other way to do it is the way I described above, which converts all of the data to what an average sized gridcell would show. Once you’ve done that, you no longer need to do an area-weighted average, because the data itself is weighted. This means that you can use a normal average, and compare things like trends directly.
So … what I do to check my work is to compare the normal mean of the area-weighted data, with the weighted mean of the original data. They should be the same, and that is the case in this analysis.
Finally, an area-weighted mean uses different weights, where the sum of all of the weights is 1. This allows you to calculate the weighted mean as the sum of the product of the data and the weights. These weights are different than the weights I used to area-weight the data itself. These weights which do not sum to 1. However, the end result is the same.
I’m confused. In your post, Willis, you state “They report an increase in Arctic solar energy input over the ocean of 0.21 W/m2 over 32 years … and the CERES data shows an increase of 0.3 W/m2 per decade.” If I’m understanding what you did correctly, your calculations were for the Arctic ocean only–but Pistone et al.’s 0.21 W/m^2 value is for the entire planet. The effect of the albedo decrease they calculated for the Arctic alone is 6.5 W/m^2, as per the quoted excerpt from their paper you include in your piece. Or am I misunderstanding something?
Another question I had was with regards to the source of your data. Did your calculations make use of the unadjusted SSF CERES dataset, or the EBAF data (adjusted within the range of the error in order to agree with the observed OHC changes)?
Very good article, I have a question:
When you hear claims that UV Irradiance can vary by as much as 15% across solar cycles, how many watts per square meter change does that represent?
”
Box of Rocks says:
February 18, 2014 at 5:10 pm
OH MY –
meant to say –
we can NOT do an energy balance…
[Fixed
”
Energy gain can be by absorption or by collision… Energy loss can be either by emission or by collision… Guess one has to just check the temperature for a whole batch of molecules to get an idea of what’s going on.
Willis,
There is also the Earthshine project that works to quantify things by observing Earthshine from the Moon. They attempted reconstructions as well.
Dromicosuchus says:
February 19, 2014 at 4:12 am
No, both of us are using the same measurement, area-adjusted figures. Both of us are measuring the Arctic regiion. However, because this is such a small region, a large change there doesn’t have much effect on the world. We’re both calculating that smaller effect.
w.
Willis
Now, you might disagree with my hypothesis that the planet is thermoregulated by emergent climate phenomena such as thunderstorms, El Nino, and the PDO.
Careful, I think they’re starting to move the argument on to something akin, except of course this is something to be feared – more money please.
Ironically, wouldn’t you need a model to express your hypothesis and then make predictions based on it?
But the stability shown in the above graphs surely argues strongly for the existence of some kind of regulatory system …
Without doubt.
The earth is not a perfect sphere. Because it spins, it’s wider across the equator than pole to pole. The shape is like a beach ball that is “squashed” very slightly. However, the squash is not very much. Here’s a scale drawing. It shows an ellipse in red, with equatorial and polar radii of 12,756.2 and 12,713.6 km. Then underneath the ellipse is the black line of a perfect circle of average radius, 6367.5 km … can you tell the difference?
As a result, for anything but the most precise of measurements, the error in using an assumed perfect sphere for the earth is trivial.
Gavin Schmidt of climate model fame has kindly pointed me to the actual weights for the oblate spheroid used by CERES. Well, actually, he unkindly pointed me to them, since he did it on Twitter rather than here, where it might have done some good … I did love his tweet:
Anthony invited him to comment here, but he passed. Gavin and I have been kind of distant since he started censoring my on-topic scientific comments at his blog. His science-fu is strong, but he’s a true believer in the church of “temperature is a linear function of forcings”, and he can’t abide people saying otherwise on his blog.
Anyhow, Gavin is 100% correct. But it’s a difference that makes no difference for the type of analysis I’m doing. The variable of interest measured by Pistone et al. was the trend in the total solar energy input to the ocean areas north of 60° N.
Using the old weights based on a perfect sphere, I got
Using the new weights based on the oblate spheroid, I get
The difference in the area of the ocean north of 60*N when calculated using the correct weights recommended by Gavin is 0.7%, seven-tenths of a percent larger than my old calculation. At the other extreme, the difference in the calculated area of the tropical ocean 23.5°N/S using the new weights is -0.4%, four-tenths of a percent smaller than what I used in the head post …
So while there are analyses to be done for which that would be an issue, for my analysis it’s a difference that doesn’t make a difference.
Since that seems to be Gavin’s main objection, I’m a happy man … in any case, my thanks to him for pointing it out. Although his style was more in the nature of “Will no one rid me of this turbulent priest?”, at the end of the day he was right, and someday I might do an analysis where that would make a difference.
w.
RACookPE1978 says: @ur momisugly February 18, 2014 at 9:53 pm
Gail! See the comment immediately above your reply. 8>>>>>>>>>>>>>>>>>
OOPs sorry, I have read enough of your comments to know better, and yes I was replying to him not you.
cd says:
February 19, 2014 at 12:16 pm
Thanks, cd. I have no problem with computer models, I use them and have written them for a host of problems and puzzles.
But the model has to actually model the reality, and the current crop of climate models are not even close.
w.
Malcolm Turner
I couldn’t agree more with the sentiment of your post. They’re getting themselves tied in knots. We’re constantly being told that the more moisture in the atmosphere, as result of an initial perturbation caused by increasing atm CO2, then the greater the greenhouse effect (positive feedback). At the same time, more moisture will mean more rainfall which necessitates more cloud (surely?) which would give us part of the thermoregulator. So which is it? I’m confused and I think despite the best efforts of the warmists to cynically hijack the recent flooding in the UK, the public don’t believe it anymore.
Willis writes “Gavin Schmidt of climate model fame has kindly pointed me to the actual weights for the oblate spheroid used by CERES.”
I certainly sense that some in the AGW camp who ought to know better have great difficulty in assessing what is important and what isn’t. I have been dumbfounded in the past at some of their reasons for glossing over major uncertainty in their results and pretzel shaped logic they use.
This makes a lot of sense. In the Arctic the water is often warmer than the air. So the AGW mantra of less ice = less albedo = warming is over simplistic and wrong. Less ice means heat transfer from water to air leading to IR emission to space, as Willis has now confirmed. This is extremely important.
AGW scientist bandy around claims of positive feedback without apparently having any idea of how profound the implications are of such a claim. A system with dominant positive feedbacks is unstable and either runs away to a fictitious catastrophe (never happened in 4 billion years but apparently now will) or settles into a regular oscillation. The evidence for this in climate history is totally absent, instead – as Willis point out, the climate is stable, not unstable.
So claims of positive feedback are thinly disguised political wishful thinking, are very irresponsible and reveal deep ignorance of the role of feedbacks in thermodynamic systems. They actually reveal contempt for science and absence of real curiosity as to the reality of climate, just politically motivated story-telling for muddle-headed chattering class luvvies who will eagerly accept any pseudo-scientific nonsense to support their left wing political predjudices.
Incoming solar energy to earth sets in motion processes, such as evaporation and cloud formation, which oppose the solar input. Where an input to a system causes an opposing process this negative feedback can be referred to as friction, and, together with being dissipative of heat, are classic ingredients of a chaotic nonlinear pattern-forming system. Such systems can display high Lyapunov stability to perturbation as they tend to converge to attractors. However such dynamics also lead to the chaotic meanderings of climate as first demonstrated by Lorenz. By contrast positive feedbacks suppress such complexity. Positive feedback leads to the expectation of simplicity in climate. Negative feedbacks to complexity. What is the reality? [Its complexity.]
One thing I never did understand about CO2 sensitivity and by extension water vapor/clouds.
If 22.5% or whatever of the sun’s total energy never actually makes it to earth because of the greenhouse gases, where are they supposed to be making up that heat, (almost a quarter of the sun’s total energy to the earth is a lot of energy)
that they can claim the greenhouse effect is warming earth? No one has ever explained to me where they can point to a mechanism that delivers almost a quarter of the sun’s energy back plus some.
I have seen people talk about trapping but you don’t get heat gain when you block 25% of the source heat, giving something whatever temperature, it’s got.
That’s like saying you have a filter that spills a quarter of a tank of energy on the ground, but when you start your heater and run it, it gives off just as much as a full tank does, plus a little.
So that’s obviously not flying or people would have heaters like that everywhere
I have read people say this and that, but I’ve never understood the whole thing in the first place.
When I was in business school I did work in some plant nurseries, and actually worked in some green houses, but I doubt that makes the climate elite think I know what plus or minus means lol!
Anyway keep up the good fight all.
@Gail Combs says:
Is the increasing amplitude of the cycles in the tempurature data for the last 65 mm years a function of the effects of age upon the samples or is there a theory as to why the the temperature anomalies are becoming greater as we near the present?
The fundamental effect of “climate change” is based on CO2 trapping IR. This should result in warming of the surrounding air. Models say it should warm such and such (2.1C since 1978), actual observations show less than half that (0.7C). Something is causing this. Options are:
The models are wrong, including the radiative transfer ones.
During this time, incoming solar to the tropics has decreased (thunderstorms etc).
The amount if IR (longwave) in the 13 to 18 micron range, radiated by the solar heated earth, the range that can be absorbed by CO2, is less than it is said to be, especially over the tropical sea.
Passing over the radiative models for now, the second and third one are appropriate for this thread.
Do you see any evidence that there is decreased incoming solar energy to the tropics, especially the tropic oceans, over this time frame, which would counteract that IR backscatter from CO2? In theory, it should happen, since water cannot be heated by IR, only a small top layer might be heated, result, evaporation, the cloud shows up a minute earlier, blocks the sun, reduces incoming solar slightly, hence counteracting the CO2 effect. Since the shade shows up slightly earlier, the total heat at the surface and hence the total evaporation may not increase, only the timing would change. One might be able to spot it from satellite pictures, the clouds at the equator would be slightly closer to the rising sun, since they would show up slightly earlier in the morning (say on the 10:55 line instead of the 11AM line). How much earlier would the cloud have to show up to counteract 1.4C of expected mid altitude air temperature from CO2 absorption?
Second, there was a post on Judiths blog by (or claiming to be) an IR astronomer. While it wasn’t completely correct, it did point out something, and that is that the IR that can be absorbed by CO2 looks to be only able to be given off by objects at a temperature of about 115F and up. Water, even tropical water, doesn’t get that hot, and most of the solar coming in is aimed at tropical water (kinda hard to miss). How much IR in the 13 to 18 micron range does the tropical ocean give off? If it does not give off much, then this area, the primary heat absorbing area of the planet, isn’t much effected by increasing IR backscatter from CO2 since there may not be enough IR at the proper frequencies for CO2 to backscatter. The models may be assuming a blackbody (see “spherical cow”), essentially land, whereas the ocean is not such, it is what it is. What is needed here is actual measurements of the amount of IR at various frequencies given off by the tropical ocean, not some computer simulation. You know, REALITY.
John West says, February 18, 2014 at 9:37 am:
“You’re not comparing NET heat fluxes; from the guestimate you linked the NET IR is 396-333=63 up, the 333 back-radiation (GHE) merely slows the radiant cooling from the surface which without it would be losing heat radiantly at 396 W/m2, but with it at only 63 W/m2 on average.”
Hahaha! Yeah, we know, this is exactly the way you people see it. Only, your alleged 333 W/m^2 don’t slow any cooling. That’s just what you SAY they do. To hide what you’re in fact suggesting they do. Because, as you know all too well, in reality they do not in any way at any time obstruct any flow of energy LEAVING the surface by way of radiation. No, they ADD energy to the surface, extra energy (from ‘somewhere’), it is a direct POSITIVE energy transfer making the surface warmer in ABSOLUTE terms (not relative). Because of these extra 333 W/m^2 down from the cooler atmosphere, and nothing else, the global surface of the Earth is able to reach beyond the ‘solar’ 255K and all the way to 288K.
But such a positive energy transfer from one system to another with such a direct result (warming) is physically defined as HEAT and does not and cannot in nature occur from cooler to warmer.
The whole concept of ‘heat goes both ways, only more heat goes from hot to cold than from cold to hot’ is purely a ‘climate physics’ invention. Cold can never under any circumstances make hotter even hotter by transferring energy to it. It is unheard of in physics! In no physics textbooks anywhere will you find such a process described or even hinted at. Because it doesn’t exist. It doesn’t happen.
You can’t make a hotter object than you even hotter by adding your ‘colder’ energy to it. It sounds fine, but in nature this is simply impossible. What you have to do is somehow make less energy LEAVE the hotter object per unit of time. The only energy able to make the hotter object even hotter coming IN, is energy from an EVEN hotter object (or from its power source). What you as a colder object need to do is obstruct or reduce the flow of thermal energy escaping the hotter object.
The easiest way to do this is via temperature (radiation) gradients. Works the same way as any potential gradient: gravity, voltage, pressure. If you’re somehow less cold, the temperature difference between you and the hotter object becomes smaller and less energy will thus flow per unit of time from it to you.
What the believers in the wonders of ‘back radiation’ do here is misinterpret the common radiative heat transfer equation, P/A = ε * σ (T_1^4 – T_2^4), in naïvely thinking that the two T-terms somehow represent physically real flows of energy, as if (and here I will copy mathematician Claes Johnson’s words:) “the [objects] were connected by a two-way highway with trucks transporting energy in both directions. There is no experimental evidence of the existence of such a two-way stream of light quanta.” They of course do not. They are simply steps on the way to find the actual flow of energy between the objects, the one we’re actually hoping to determine, the answer to the equation: P/A, the ‘heat’. T^4 does not in itself bear a physical meaning in the sense of describing a phenomenon. It is just temperature raised to the fourth. So to find P/A, we only need to know the temperature of the two objects (and the emissivity of the hotter one, the one emitting the energy).
In other words, we need to drop the whole ‘back radiation’ nonsense and concentrate on temperature gradients. Follow the HEAT. There is no global extra flux of 333 W/m^2 flowing down from the atmosphere to the surface. This is ‘climate physics’ mumbo jumbo. The only real flux is the 63 W/m^2 going UP.
Willis, in a discussion elsewhere of Leif’s steady-forcing autoconsensus, I attempted a précis of your position about as follows:
(assuming any variance introduced by sol, albedo etc.) The result seems to be that high latitudes are in IceBox or HotHouse bistable states, while parrots and parrotfish carry on unperturbed. An amusing film loop!
How badly and baldly does this overstate, understate, or misstate your case?
Brian H says:
February 23, 2014 at 5:38 am
It’s not bad at all, well done … however, it misses some essentials:
1. The emergent governing mechanisms operate in many places and temporal and spatial scales. It’s not just tropical thunderstorms, although they are the largest player.
2. The apparent ~30°C limit of the tropical oceans is an extreme case. Most places the emergent governing phenomena operate in areas without a clear upper limit.
3. The periodic emergence of the El Nino warm-water pump, which pumps excess heat from the tropics to the poles, is a second major player.
4. The periodic shifting of the bi-stable state of the PDO alternately either impedes or enhances the flow of heat to the poles.
5. I assume that there are further emergent systems operating at the poles, including the “polar vortex” phenomena, which also act to stabilize the temperature away from the tropics … perhaps if I’d lived there for decades instead of in the tropics I’d understand them better …
So those are a few things I’d add …
Good question, thanks,
w.
The bistable states I referenced are terms that apply to paleohistory, with tropical summers at the poles at one end (HotHouse, global average ~24°C) or current iced year-round poles at the other (IceBox, GAT ~14°C), with minor variations in the latter that swung us between e.g. the Michigan glaciation and the Holocene interglacial. As Rutan and many others note, CO2 isn’t even reliably correlated with those swings as an effect, much less a cause or “forcing” (that unphysical term the AGW-pushers are dependent on forcing us to accept . “The Forcing is with us!” they fantasize.)