Guest Post by Willis Eschenbach
There is a more global restatement of Murphy’s Law which says “Nature always sides with the hidden flaw”. Parasitic losses are an example of that law at work.
In any heat engine, either natural or manmade, there are what are called “parasitic losses”. These are losses that tend to reduce the temperature differentials in the heat engine, and thus reduce the overall efficiency of the engine. In general, as a percentage parasitic losses increase rapidly with ∆T, the temperature differences in the engine. In the climate system, two main parasitic losses are the losses from the surface to the atmosphere by way of conduction and convection (sensible heat), and the losses from surface to atmosphere by way of evaporation and transpiration (latent heat). Both of these parasitic losses act to reduce the surface temperature with respect to the overlying atmosphere, by simultaneously cooling the surface and warming the atmosphere … nature siding with the hidden flaw to reduce the overall system efficiency. So I decided to see what the CERES data says about parasitic losses. Figure 1 shows the parasitic losses (the sum of sensible and latent heat losses), as a percentage of the total surface input (downwelling longwave plus shortwave).
Figure 1. Parasitic losses (latent and sensible heat loss) from the surface to the atmosphere. Percentage of parasitic loss is calculated as the sum of sensible and latent loss, divided by the total surface input (downwelling shortwave plus downwelling longwave).
I was most interested in how much the parasitic loss changes when the total surface input increases. Figures 2 to 4 shows that situation:
Figures 2-4. Scatterplots, parasitic loss in watts per square metre (W/m2) versus total surface input (W/m2). Parasitic loss is loss as sensible and latent heat. Gold line shows the loess smooth of the data. Red dots show land gridcells, which are one degree square (1°x1°) in size. Blue dots show ocean gridcells.
I was very encouraged by finding this result. I’ve written before about how at the warm end of the spectrum, parasitic losses would increase to the point where most of each new additional watt striking the surface would be lost as sensible and latent heat, and that little of it would remain to warm the surface. These graphs bear that out entirely. Here’s why.
The slope of the gold line above is the rate of increase in parasitic loss for each additional degree of warming. As you can see, the slope of the line increases from left to right, although the rate of increase goes up and down.
In order to understand the changes, I took the slope (change in parasitic loss divided by the corresponding change in surface input) at each point along the length of the gold line for both the land and the ocean separately. Figure 5 shows that result.
Figure 5. Change in parasitic loss (in W/m2) for each additional W/m2 of surface input. “Wobbles”, the looped parts in the two graphed lines reflect subtle changes in the loess smooth, and can be ignored.
Now, what are we looking at here? Well, this is how the parasitic loss changes as more and more energy is input to the surface. Where there is little surface input, the loss is low. In fact, at the South Pole the situation is reversed, and the net flow of energy is from the atmosphere to the surface. This is the result of huge amounts of energy being imported from the tropics.
The key point, however, is that as we add more and more energy to a given gridcell the amount of parasitic losses rises, in perfect accordance with nature siding with the hidden flaw. And at the right hand end of the scale, the warmest end, for every additional watt that is added, you lose a watt …
Is this relationship shown in Figure 5 entirely accurate? Of course not, the vagaries of the smoothing process guarantee that it isn’t a precise measure.
But it clearly establishes what I’ve been saying for a while, which is that parasitic loss is a function of temperature, and that at the top end of the scale, the marginal losses are quite large, close to 100%.
Now, as you can see, nowhere is the parasitic loss more than about 30% … but the important finding is that the marginal loss, the loss due to each additional watt of energy gain, is around 100% at the warm end of the planet. Here is the parasitic loss for the planet as a whole versus total surface input as shown in Figure 2:
Figure 6. Change in parasitic loss (in W/m2) for each additional W/m2 of surface input, as in Figure 5, but for the planet as a whole.Change in parasitic loss (in W/m2) for each additional W/m2 of surface input. “Wobbles”, the looped parts in the two graphed lines reflect subtle changes in the loess smooth, and can be ignored.
Note also that across the main part of the range, which is to say in most of the planet except the tropics and poles, about half of each additional watt of energy increase doesn’t warm the surface … it simply goes into parasitic loss that cools the surface and warms the atmosphere.
Best to all,
w.
PS—If you disagree with what I’ve said please quote my words. That lets all of us know just exactly what you disagree with …
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It is high time someone put Willis up for an Hon. PhD.
Might be a problem finding an honest enough University Department, though.
I have to admit that when I first laid eyes on this post, and I saw the word, ‘parasitic,’ in the title, the first thought that came to my mind concerned the intrinsic nature of our Global Warming Warriors.
Perhaps, being parasites themselves, they are incapable of recognizing a parasitic action such as that that insures no heat engine is 100% efficient. They better recognize it soon or they just might succeed in killing their host – modern, affluent society.
Many thanks, Willis. You have a gift for asking the right question and visualizing the answers. Two questions: (1) is Fig 3 supposed to be both land and ocean? It looks like land only (with ocean shown on Fig 4). (2) why does this “diminishing heat gain/increasing parasitic loss remind me of the Stefan-Boltzmann equation? I know that is for radiative losses but it has the same (general) negative feedback relationship. Funny how Nature might do that, notwithstanding the dire prognostications and hand-waving of the alarmists.
Is this Trenberth’s missing heat?
I have been using the CERES data myself for some research lately, so I am trying to get to know more about it. Clearly the below top of atmosphere (TOA) fluxes are all calculated since the satellite can only “see” what is at the top. Others may not be aware the data below TOA is calculated using a radiative model. I always get a bit nervous using model output data rather than actual observations. There are always lots of comments on this forum from people trashing any kind of model output. I asked the folks at CERES for a brief outline of how the data is calculated and here is their kind reply,
“Briefly, we compute “shortwave (solar)” and “longwave (emitted by the earth)” separately by radiative transfer models. The atmosphere is divided into ~50 vertical layers. Spatial and temporal resolutions for the computation depend on data product. Spectral region is separated into smaller spectral regions and absorptions by water vapor, ozone, CO2, and other trace gases are treated with approximations. Scattering by aerosols and clouds are treated by a two-stream approximation. Most inputs come from observations, including temperature, humidity profiles, cloud and aerosol properties.”
I am not saying the computed data is not good, just that people should be aware of what is actually observed data and what is model output.
A second point, what data set(s) did you use for the latent and sensible heat? I may have overlooked some but I could not find any of this direct data in any of the CERES data sets.
Thanks.
Willis E said this “These are losses that tend to reduce the temperature differentials in the heat engine, and thus reduce the overall efficiency of the engine. ”
dS = dQ/T ; ie the 2nd Law of Thermodynamics
In order to reduce Entropy, then one must have an large heat transfer surface and an infinitesimally small difference in temperature across the heat transfer surface, maximizing reversibility. You are only relying on Carnot Efficiency as related to heat engines.
Thermal power generating plants can’t afford large heat transfer surfaces so they accept the entropic inefficiencies (irreversibility) due to large temperature differentials.
I doubt the atmosphere can be solely evaluated using a Carnot Efficiency. It is an immense heat transfer system.
MaxLD says:
March 26, 2014 at 11:48 am
Thanks, Max. I’ve pointed that fact out in a number of posts, that the CERES TOA data is observations, and the surface data is calculated from those observations. I have compared the CERES surface data (where possible) to observations and other forms of estimates and calculations, and they are quite close. So I use them, with caveats, as the best that we have.
You are correct, there is no direct calculation of parasitic loss in the CERES dataset. The parasitic loss is computed as the input to the surface less the radiative loss from the surface. There is an uncertainty in the measurement due to the import/export of warm water from a gridcell, but that appears to be minor in the context of this particular analysis.
Regards,
w.
hi Willis,
An interesting post as always. “Parasitic losses” are, as you say, (“These are losses that tend to reduce the temperature differentials in the heat engine, and thus reduce the overall efficiency of the engine. “) mechanisms by which heat goes from hot to cold without doing any useful work. Could you please clarify what you mean by “useful work” and “efficiency of the engine” in this context?
Thanks
this graph look like the sperm whale.
%3Bhttp%253A%252F%252Fwww.dailymail.co.uk%252Fnews%252Farticle-2370470%252FHeart-warming-moment-lost-baby-sperm-whale-jumps-joy-5ft-waves-reunited-family.html%3B634%3B417
http://wattsupwiththat.files.wordpress.com/2014/03/scatterplot-parasitic-loss-vs-total-surface-input-global.jpg
Paul Westhaver says:
March 26, 2014 at 11:59 am
Thanks, Paul. I am far from the first person to discuss the Carnot efficiency of the climate seen as a heat engine. In Bejan’s work I find, for example:
and
Best regards,
w.
Willis:
I was reading on the CERES literature about the data and comparison to observation. They state that 26 stations were used to compare the global 1×1 grid cell data to observations. I could not find a list of where these stations are located Maybe I overlooked something. 26 stations around the globe is not a lot. I wonder if any of them are in the Arctic. It would be very hard (costly) to set up observing sites there just for CERES data usage.
Interesting. The total surface input equals the absorbed solar (by the surface). The downwelling longwave (atmospheric radiation) is no surface input. Net surface LW radiation is upwelling (cools the surface, warms the atmosphere). So, the “parasitic losses” percentage of the total surface input (absorbed solar) is much higher. Not parasitic at all. They’re the main surface cooling mechanism.
Michael D says:
March 26, 2014 at 12:11 pm
In terms of the greenhouse effect, the efficiency can be thought of as how hot the greenhouse effect can make the surface with respect to the atmosphere. This temperature difference ∆T is what ultimately drives the circulation of the atmosphere and the ocean.
However, there are a number of ways that heat escapes or otherwise interferes with the surface heating. In addition to parasitic losses, we have things like dust devils and a host of other emergent phenomena that spring up and cool the surface when it gets too hot.
My main point in this piece is to point out that these parasitic losses, like most parasitic losses, increase with temperature, with the corollary that at the high end of the scale almost all of any increase in forcing does NOT go into warming the surface.
Instead it is lost as either sensible or latent heat, which decreases the ∆T between the atmosphere and the surface.
w.
Re OldSeaDog’s comment and in the light of UWA’s behaviour regarding the Lewnatics fakery, “honest enough University Department” methinks might almost be considered an oxymoron.
Thanks, Edim, but I fear I don’t understand any of your claims. Comments follow.
Edim says:
March 26, 2014 at 12:25 pm
No, the total surface input is the sum of solar and longwave.
Say what?
True … so?
Edim, if you think that the only thing warming the surface is the absorbed solar, I fear you are beyond help. For example, we know (from measurements) that the ocean constantly loses about 400 watts per square metre (W/m2) of radiated energy.
We also know (from measurements and estimates) that the parasitic losses about about 100 W/m2. So the ocean is losing a total of about half a kilowatt per square metre.
However, we also know from measurements that the ocean only receives about 170 W/m2 of solar energy … so if your crazy theory were correct, what keeps the ocean from freezing? If your theory were correct it the ocean would have a NET loss of about 330 W/m2, so why isn’t it frozen solid?
I must confess, this idea that longwave radiation can’t warm the planet is bull goose looney but damn hard to kill. Everyone seems to agree that longwave radiation can warm them, common sense shows up that. And we all know that everyday objects far from a big fire are all heated by nothing but longwave radiation, sometimes to the point where they burst into flame.
But somehow, some folks think that although we have experience with LW warming all kinds of objects, it can’t warm the earth itself … and they often are totally impervious to logic of any sort.
So, let’s see what category Edim is in … Edim, what keeps the oceans from freezing if (as you claim) LW can warm you and me and all kinds of inanimate objects but it can’t warm the planet?
w.
“Others may not be aware the data below TOA is calculated using a radiative model.
glad you asked the CERES folks.
I’ve been trying to explain this to WUWT readers and folks who use CERES data or ANY satellite data for that matter
READ THE ATBD.
Here is what most people dont get.
1. When you use satellite “data” you are using a data PRODUCT, not observations
2. The observation is a voltage on sensor cell.
3. That observation is turned into a data product by applying PHYSICAL MODELS
4. IF you accept the data product as truth, you are epistemically committed to the
truth of the model.
Example: I shoot a laser at the moon. I measure the transit time. I accept a physical model
that dictates a speed for that signal. I also accept a model that says D=R*T. using
those two things I calculate the distance. When I use this distance I am commited to
two other truths: the speed of the signal and the model of D=R*T
So, what physical models are absolutely required to calculate data products?
Radiative Transfer Models:
Yup, the same physics that says doubling C02 will add 3.7 Watts to the energy balance
of the planet.
The same physics that says C02 warms the planet it does not cool the planet.
The same physics we use to design attenna for IR missiles, cell phones, radars.
Think of it this way
The satellite sensor records the signal AFTER it leaves the atmosphere.
Any inferences about what happens below this depends upon modelling.
how signals pass through the atmosphere. radiative transfer equations.
Everyone who uses and relies on satellite data is a closet AGW believer. They just dont know it.primarily because they dont read ATBDs. They just find data and use it without following it back to the original bits.
So, next: Is this an example of Prigogene’s self-organized structures emerging to increase the efficiency of thermal loss? You have documented an increase, and the increase appears to have some structure. If that structure can be connected to secondary measurements of dissipative quasi-particle structures (their frequency of occurrence, their strength) such as thunderstorms, large scale convective cells, tropical storms, cloud/albedo systems (which provide yet another highly nonlinear self-limiting mechanism) you might actually be able to provide a compelling argument that the climate is a self-organized system that more or less provides a “governor” that limits the temperature gain from any possible forcing that doesn’t move the entire system into an entirely novel dissipative regime. It is basically a strong argument for quasi-invariance of the primary attractors because if you add heat/surface radiative forcing, you simple increase the efficiency of surface loss mechanisms within the nonlinear structures that short-circuit the “simple” radiative loss mechanism. Even if there is additional e.g. water vapor feedback, it is simply canceled as it occurs and fails to actually heat the surface (by much).
Once again, one thing that puzzles me about the CERES data is, however, the lack of a substantial disparity between land surface and ocean, and between different kinds of land surface. In this case the deserts are clearly visible on the toplevel map — as one would expect, there is little latent heat transfer in a desert — and there is maximal transfer over the tropical oceans and a surprising large transfer over tropical rain forest, almost matching the ocean. However, this doesn’t seem to have much effect on the combined results — land, ocean and both together have almost the same general structure, although there is small bobble in the middle forcing region that might be exactly this, a limiting of the loss even for higher forcing in subtropical deserts that is then overwhelmed by the tropical rainforest returning to ocean-like behavior for the latitude (as the forcing is I’m guessing roughly monotonic in the latitude, so you could make the same diagram with latitude as the horizontal scale with only a small distortion of the scale).
If this slight subtropical/temperate flattening associated with middle latitudes/forcing does indeed reflect the lowered contribution of low-humidity deserts, it suggests that global warming from additional backradiation forcing should occur primarily (or most efficiently) in those climates, where there is reduced ability to transfer energy via latent heat. But those are precisely the climates that have the most efficient direct radiative loss, as there is little water vapor or cloud structure to feed back whatever additional radiation one develops due to CO_2 alone. Deserts seem to be the place where direct CO_2-linked warming should most easily be observed and where the effect should be maximal.
Since the tropics and subtropics represent the region of greatest annual insolation (by a pretty good margin) due to both the planetary Jacobean and because of the increasing angle of incidence as one moves towards the poles, the idea of self-organized structures merely linearly strengthening to provide an exponential attenuation of the warming effect of additional forcings and effectively limiting the probable temperature rise from any sort of additional forcing everywhere but in deserts or at the poles is an attractive one. Deserts might get a bit warmer, unless/until circulation patterns shift so that they are no longer deserts. The poles are one end of the heat transfer and dissipation cycle, and they could get a bit warmer. But all of the tropics and most of the temperate zone has (if your analysis is correct net negative feedback, reinforcing the idea that has been proposed in several places that the climate will warm strictly less than the amount predicted by analyzing CO_2 forcing alone. Instead of every additional watt/m^2 of CO_2 forcing being accompanied by a watt of additional water vapor forcing, the total effective forcing of an additional watt of CO_2 forcing is anywhere from 0.0 to 0.7 Watts of actual forcing, depending on where you are. This data suggests that the total warming from additional CO_2 that by itself might have warmed the planet by 1.5 C will only warm it by anywhere from 0.5 C to 1.C. Which actually does not badly correspond to the actual temperature data over the entire industrial era.
The really nice thing about this is that you (can) use data from one part of the globe effectively to make inferences about another part of the globe. You don’t have to assert a feedback to 1 degree of CO_2 linked warming globally as a guess — you can just look at what the feedbacks actually are someplace where the temperature is 1 degree warmer, as determined by the ratio between incoming and outgoing surface radiation. Not only do you get “water vapor” feedback, you get a very accurate picture of total feedback from all sources directly from the CERES data, ready to be plugged into even a very simple single layer model to get a very simple estimate of the plausible range of global warming. The data already knows everything you need to know to handle the global problem.
rgb
Paul Westhaver says:
March 26, 2014 at 11:59 am
While I am not totally comfortable with Willis’ used of the term “parasitic losses” here, as to me that implies an “intent” to the system as in an engineered design, this is just a semantic quibble on my part. I think his general point is well taken.
By analogy to an engineered system, let’s take the boiler in a steam-turbine generator. Any thermal losses from the boiler directly to ambient are considered parasitic losses, meaning energy put into the system that is unavailable to do what the system is designed to do: generate mechanical (and possibly then electrical) energy through the turbine.
If we had a poorly insulated boiler, significant energy would be convected away to the cooler atmosphere. If the outside were wet, as in the case where it was raining on the boiler, there would be significant evaporative energy transfer to the atmosphere as well. In such an engineered system, it would be worth some cost and effort to reduce these losses.
Note that neither of these losses have anything to do directly with the actual thermal-to-mechanical conversion process in the turbine. But what these losses do is to reduce the thermal energy available at the input to this process.
I view Willis’ use of the term “parasitic losses” as a bit of a metaphor, because it is not clear what they are losses “from” in a natural system. But still, these transfers do serve to reduce and limit the temperature at the high end of the natural system (compare our equatorial temperatures at midday to those of the moon…).
I must confess, this idea that longwave radiation can’t warm the planet is bull goose looney but damn hard to kill. Everyone seems to agree that longwave radiation can warm them, common sense shows up that. And we all know that everyday objects far from a big fire are all heated by nothing but longwave radiation, sometimes to the point where they burst into flame.
But somehow, some folks think that although we have experience with LW warming all kinds of objects, it can’t warm the earth itself … and they often are totally impervious to logic of any sort.
Damn skippy. You can show them pictures of it taken with IR cameras. You can show them broad spectrum spectrographs that directly measure not only the existence of the downwelling radiation but its actual spectrum, complete with CO_2 and water vapor bands and ozone/oxygen notches. You can show them arithmetic that indicates that without this downwelling radiation the sun alone might make it a lot hotter during part of the day in part of the globe, but it would get a lot lot colder everywhere else and all the rest of the time for a pronounced net cooling. And you’ll still have folks asserting that downwelling LWIR can’t have anything to do with surface temperatures.
They’ve obviously never heard of energy conservation or the laws of thermodynamics.
I feel your pain. I literally don’t know what to do with them (or for them, as they are to be pitied and helped as much as they can). I sometimes think that they are ringers who come to the site just to ensure that its science is never taken seriously, because there is often a sort of religious contempt for algebraic argument or even common sense that accompanies their assertions. But sometimes one does get such a comment from somebody who lacks the certainty that their own arguments, generally formulated in the absence of ever having taken a halfway decent physics class, are all that likely to be right and who are willing to learn.
So cross your fingers.
rgb
Willis, it’s not my crazy theory. The only surface input is the absorbed solar. This input is balanced by the surface outputs: evaporation, convection and net surface LW radiation.
http://science-edu.larc.nasa.gov/EDDOCS/images/Erb/components2.gif
The downwelling LW is only one ‘side’ of the LW radiative heat exchange at the surface – the net LW flux is upwelling and is a surface output.
Interesting. Willis gets 18.4% parasitic loss. A month or two ago I posted on WUWT a back of the envelope calcualtion for carnot efficiency for the global atmosphere of 20%, reducing to 18% due to global warming. Co-incidence, or perhaps the parasitic loss is the flip side of the carnot efficiency of the atmospheric heat engine?
Dear Edim,
That’s fine, but in that case one has to be very precise in what one is saying and make sure that you’re saying things in the same way that they are being said in what you are addressing.
Obviously you are interested in adding the word NET in front of each term in the energy flow. Equally obviously, Willis was not using that word. He was summing all of the downward terms into a total incoming/forcing (consistent with the usage of the term in much of climate science). He was then focussing on the DIFFERENCE between the measured downward forcing and the observed upward radiation, and (if I understand correctly) interprets this difference as the upward total heat loss in non-radiative channels, since CERES permits the direct observation of the heat loss in the radiative channels. His conclusion is that at some point, adding to the surface forcing does not increase the upward radiation at all — the surface reaches a constant temperature and additional forcing is eliminated by means of the alternative channels of conduction, convection, and latent heat, with the latter being the most important especially in the tropical ocean. So increasing the forcing (solar plus downwelling LWIR simply doesn’t chance the surface temperature (according to CERES) — the additional power goes directly into latent heat and vertical heat transport that short circuits the partially blocked radiative loss mechanism.
If all you are arguing about is the inclusion or lack of inclusion of the term “net”, then please adjust your usage to conform to Willis’s because right or wrong, it is clear enough and it is, after all, his post and thread.
rgb
Just found this post on climate change, and thought your readers would find it interesting and worth comment:
http://www.transitionnetwork.org/blogs/rob-hopkins/2014-03/prof-myles-allen-climate-change-flooding-and-carbon-capture-silver-bullet
Well done Willis, great addition RGB, it really is the only thing that explains how a crazy metric such as average annual global temperature could be as stable as it is.
v/r
David Riser
Curt says:
March 26, 2014 at 12:47 pm
Paul Westhaver says:
March 26, 2014 at 11:59 am
While I am not totally comfortable with Willis’ used of the term “parasitic losses” here, as to me that implies an “intent” to the system as in an engineered design, this is just a semantic quibble on my part. I think his general point is well taken…..
___________________________________________________________________________
Curt your point is well taken. I am elevating the notion of entropy production as a measure of efficiency to defeat so called “common- sense” assertions wrt heat transfer efficiency.
I recall be shocked as a young mechanical engineering student to discover that it is not in the interest of energy producers to seek max temps in a heat source and min temps in the low temp reservoir to yield max bang for your buck,
Yes you do increase heat transfer “rates” but at a huge cost.
The notion of reversible processes and entropy was introduced by Clausius and Kelvin around 1865 and it is an absolutely counter intuitive concept. All heat transfer systems are now evaluated based on minimizing entropy in the most cost effective manner possible. So Entropy is the true measure of efficiency. That makes the assertion that max delta T yield highest eff a fallacy limited to a categorical calculation, which is why I added the disclaimer of Carnot efficiency.
The most efficient processes are those which produce the least “disorder” from a second law perspective. That concept eludes most people and they are willing to buy into the popular phase repeated by Willis. If we speak in common parlance, we can get away with terms like “parasitic”. As scientists we rely on the 1st Law AND the Second Law of thermodynamics. The heat has to go somewhere, especially if a process is irreversible. Besides the atmosphere is an enormous heat transfer surface with relative low deta Ts from a heat engine perspective.