Guest Post by Willis Eschenbach
The CERES dataset contains three main parts—downwelling solar radiation, upwelling solar radiation, and upwelling longwave radiation. With the exception of leap-year variations, the solar dataset does not change from year to year over a few decades at least. It is fixed by unchanging physical laws.
The upwelling longwave radiation and the reflected solar radiation, on the other hand, are under no such restrictions. This gives us the opportunity to see distinguish between my hypothesis that the system responds in such a way as to counteract changes in forcing, and the consensus view that the system responds to changes in forcing by changing the surface temperature.
In the consensus view, the system works as follows. At equilibrium, what is emitted by the earth has to equal the incoming radiation, 340 watts per metre squared (W/m2). Of this, about 100 W/m2 are reflected solar shortwave radiation (which I’ll call “SW” for “shortwave”), and 240 W/m2 of which are upwelling longwave (thermal infrared) radiation (which I’ll call “LW”).
In the consensus view, the system works as follows. When the GHGs increase, the TOA upwelling longwave (LW) radiation decreases because more LW is absorbed. In response, the entire system warms until the longwave gets back to its previous value, 240 W/m2. That plus the 100 W/m2 of reflected solar shortwave radiation (SR) equals the incoming 340 W/m2, and so the equilibrium is restored.
In my view, on the other hand, the system works as follows. When the GHGs increase, the TOA upwelling longwave radiation decreases because more is absorbed. In response, the albedo increases proportionately, increases the SR. This counteracts the decrease in upwelling LW, and leaves the surface temperature unchanged. This is a great simplification, but sufficient for this discussion. Figure 1 shows the difference between the two views, my view and the consensus view.
Figure 1. What happens as a result of increased absorption of longwave (LW) by greenhouse gases (GHGs), in the consensus view and in my view. “SW” is reflected solar (shortwave) radiation, LW is upwelling longwave radiation, and “surface” is upwelling longwave radiation from the surface.
So what should we expect to find if we look at a map of the correlation (gridcell by gridcell) between SW and LW? Will the correlation be generally negative, as my view suggests, a situation where when the SW goes up the LW goes down?
Or will it be positive, both going either up or down at the same time? Or will the two be somewhat disconnected from each other, with low correlation in either direction, as is suggested by the consensus view? I ask because I was surprised by what I found.
The figure below shows the answer to the question regarding the correlation of the SW and the LW …
Figure 2. Correlation of the month-by-month gridcell values of reflected solar shortwave radiation, and thermal longwave radiation. The dark blue line outlines areas with strong negative correlation (more negative than – 0.5). These are areas where an increase in one kind of upwelling radiation is counteracted by a proportionate decrease in the other kind of upwelling radiation.
How about that? There are only a few tiny areas where the correlation is positive. Everywhere else the correlation is negative, and over much of the tropics and the northern hemisphere the correlation is more negative than – 0.5.
Note that in much of the critical tropical regions, increases in LW are strongly counteracted by decreases in SW, and vice versa.
Let me repeat an earlier comment and graphic in this regard. The amounts of reflected solar (100 W/m2) and upwelling longwave (240 W/m2) are quite different. Despite that, however, the variations in SW and LW are quite similar, both globally and in each hemisphere individually.
Figure 3. Variations in the global monthly area-weighted averages of LW and SW after the removal of the seasonal signal.
This close correspondence in the size of the response supports the idea that the two are reacting to each other.
Anyhow, that’s today’s news from CERES … the longwave and the reflected shortwave is strongly negatively correlated, and averages -0.65 globally. This strongly supports my theory that the earth has a strong active thermoregulation system which functions in part by adjusting the albedo (through the regulation of daily tropical cloud onset time) to maintain the earth within a narrow (± 0.3°C over the 20th century) temperature range.
w.
As with my last post, the code for this post is available as a separate file, which calls on both the associated files (data and functions). The code for this post itself only contains a grand total of seven lines …
Data (in R format, 220 megabytes)
Thank you Willis,
For over ten years, being an educated sort of layman, I have been trying to explain the increased temp/increased water vapor/increased Albedo, equilibrium scenario. Your post has given me one more arrow in my quiver to further state what I feel as the obvious (in my non-scientific opinion), That is the state of equilibrium will always be the result of increased surface absorption/ reduced radiative reflection, for whatever reason.
Is this the same as the Iris effect? Prof Richard Lindzen
Bad amatuer…BAD BAD AMATUER…shades of Tom Edison, Michael Faraday, and (horrors) the Wright Brothers. Shame on you for making primates out of the Phd’s. Your punishment, watching Lady Gaga, Al Gore, and Ahhhnold Schwartneger give talks on AWG. (Wait, that’s right, under the current administration, “enhanced interrogation” is not allowed. I guess you get by this time!)
Cool Willis. Thanks for your work.
Very interesting. I’m not surprised at the result. A large fraction of reflected SW outgoing suggests dense clouds with high tops, which in turn are unusually cool, and which as a result have a smaller than average LW outgoing.
Here is what I see as two issues to examine.
1) This data doesn’t related directly to the problem of increasing GHGs because that is a long-term trend. This data, I think, exhibit the effect I summarize above, which may or may not result from what you propose. How can you demonstrate that the different time scales involved (GHGs versus your data) are not important?
2) You have shown the correlation, but what can you do to establish causation? You need to show that there is a time lag or something–effect follows cause.
Maybe there is some clarification from the observation of “yellow” areas that seem as if they are pressed against the west sides of continents. Maybe this is a location with different cloud formation properties than other ocean.
I’m a little concerned that -0.65 is still a weak correlation, but then weather data are typically noisy.
The CERES SW window really has a lot of near IR with it (0.3 to 5 micron) and the IR window is close at 8-12 micron, so it’s interesting that you find the 2 bands so negatively correlated.
Maybe a better correlation exists in the more raw data, because you are offered temporally smoothed monthly data. The radiation could well change from orbit to orbit and show as smeared in the final assembled data. Can you get pairs of simultaneous point observations to check this?
Shouldn’t the right hand box of Fig 1 show 390W/m2 ?
Willis
Can you please define the terms SW and LW (I know that it is short wavelength and long wavelength). What I want to know is what is the definition of the wavelengths involved.
Any increase in CO2, and CH4 must, by definition, have an increased absorption waveband and I have yet to see this quantified adequately. Also, from the equations involved, absorption is both temperature and pressure dependent, I have never ever seen any of these models deal with this type of dependency.
Thanks, Willis. Nice work, very clear, however, your results are showing a negative feedback mechanism that tends to stabilize the system. It does not directly address the effect of adding greenhouse gases to the atmosphere, or have I missed something?
bones, he addresses the effect of adding greenhouse gases indirectly. We know they have been added, but the negative correlation between LW and SW persists.
I believe your third cartoon “My View” should have 390 as the surface radiation.
Interesting post Willis
Charlie A says: January 7, 2014 at 9:35 pm
Shouldn’t the right hand box of Fig 1 show 390W/m2 ?
Yes, Charlie is correct. To correspond to Willis’ narrative that an increase in GHG causes a change in albedo rather than a change in surface temperature, the upward LW radiation from the surface should be the same as the “Equilibrium” left panel before the increase in GHG. The GHG absorption in the left panel is 150 W/m2 (ie, 390-240), and is 152 W/m2 is the middle panel that has increased GHG, an increase of 2 W/m2. The right panel is supposed to have the same GHG absorption as the middle panel, but with the incorrect number it has 392-238 = 154 W/m2, or an increase of 4 W/m2 over the left panel case. Correcting the upward LW to 390 W/m2 in the right hand box will make the increased GHG absorption over the left panel case equal 2 W/m2.
dalyplanet says:
January 7, 2014 at 10:21 pm
[Thanks, fixed. -w.]
You have a major error here. You have conserved energy flux, whereas you should conserve energy. The area of the incoming flux is the cross-sectional area of the earth. The area of outgoing flux is the earth’s surface area, which is a factor 4 smaller.
Willis,
with regard to the cloud thermostat, the time of day that clouds form is a factor even if the amount of cloud is only marginally increased. Earlier cloud formation leads to greater cooling even if cloud mass is not greatly increased.
Increased radiative gases should cause clouds to form a few minutes earlier after dawn over the oceans in the ITCZ.
Been puzzling lately about an aspect of the greenhouse effect as taught me in college many solstices ago. The story was that greenhouse glass (or gas) was permeable to shortwave incoming radiation but blocked outgoing longwave , and that the shortwave was somehow “converted” to longwave after it was absorbed inside.
Being young and impressionable and knowing well how hot my car got in Davis summers when the windows were closed, I was convinced.
Materials generally emit radiation wavelengths according to their temperature, but different materials have very distinct preferences for wavelengths and tend to both absorb and emit in the same bands. Outside these bands they seemingly ignore the radiation.
How then does a material convert shortwave to longwave?
Water (both surface and clouds), water vapor, and ice all have similar optical properties. they just luuuuv longwave radiation. CO2 loves it as well. They don’t care a fig about shortwave. Except for strong reflectance from clouds in the visible range (an unrelated property), they let it pass through.
All this may be a propos in a roundabout way because to examine the relationship between reflected shortwave and “upwelling” longwave, one must consider the sources. About half of TSI is longwave in the first place. The clouds, water vapor, atmospheric ice, and greenhouse gasses catch it and start flinging it around. The ocean surface catches all that comes its way in the first millimeters and flings it back.
If the extreme negative correlation in the tropical oceans means greater cloud reflectance and less escaping longwave, it could be that the LW escape is short circuited in a more intense photon food fight between the ocean and clouds and the reflection is incidental.
Unless you can explain to me how SW is “converted” to LW…
phillipbratby says:
January 7, 2014 at 10:42 pm
In the CERES data, both the incoming flux and the outgoing flux are averaged 24/7 over their particular gridcell. They are not general measurements of the total global flux. As a result, there is no such error as the one you imagine.
And in general in other datasets, all incoming and outgoing fluxes are calculated on a 24/7 basis, and are adjusted for the situation that you mentioned.
Scientists may be wrong, and often are. But when you think you’ve uncovered a “major error”, something really obvious, well, you should check your facts very carefully before uncapping your electronic pen …
w.
I also have a layman’s question that I’m sure someone has the answer to but I haven’t noticed it being discussed. The simplified explanations of “the Greenhouse Effect” talk about the Earth absorbing incoming solar SW radiation and emitting LW radiation, some of which is absorbed by “greenhouse” gases such as water vapor and carbon dioxide, which retards the escape of this LW radiation into space and thereby warms the Earth. My question concerns incoming solar LW radiation. Common sense suggests that greenhouse gases in the atmosphere also absorb incoming LW, thereby preventing it from reaching and warming the ground. If the concentration of greenhouse gases rises, they should absorb more of this incoming LW and prevent that from reaching the ground, resulting in cooling.
I’d like to know whether the total amount of LW at frequencies that can be absorbed and emitted by CO2 reaching the top of the atmosphere from the Sun is greater than the total emitted from the Earth’s surface over an equivalent period and whether this could lead to increasing “greenhouse” cooling rather than warming. And I’d like to know how the absorption and emission of this radiation is accounted for by conventional atmospheric greenhouse theory.
Where’s the non-radiative surface cooling by the atmosphere?
http://pmm.nasa.gov/education/sites/default/files/article_images/components2.gif
The non-radiative fluxes dominate.
Surface heat exchange (cooling side)
Convection and evaporation (sensible and latent): 59%
Radiation (incl. directly to space): 41%
Sorry, I have to ask this. How does CO2 absorb long wave radiation from the surface?
CO2 in the atmosphere is warmed by kinetic collisions with other molecules to local air temperature. The properties of CO2 indicate that the CO2 will be RADIATING over some 3,800 lines covering 13 to 17 microns. This same band of radiation is emitted from the surface.
If the CO2 happened to absorb some of that radiation when it has already emitted an equivalent amount of radiation then there will be no change to the energy levels in the CO2.
My understanding is that the surface does not emit in 2.7 and 4.3 micron bands so there is no effect there.
Please, just what energy is CO2 absorbing from the surface? Reflected sunlight? I really would like to know as all my studies just leave me more baffled.
Willis said:
“When the GHGs increase, the TOA upwelling longwave radiation decreases because more is absorbed. In response, the albedo increases proportionately, increases the SR. This counteracts the decrease in upwelling LW, and leaves the surface temperature unchanged”
All my work since 2008 has been based on that proposition and I have stated it multiple times in multiple locations.
Where we differ is that I see the ultimate determinant of the set point surface temperature as atmospheric mass held within a gravity field and irradiated from an external source.
Is the reason for that difference that Willis still gives undue prominence to the assumed need for GHGs to initiate the necessary convective overturning ?
It isn’t a matter of ‘pressure’ since ‘pressure’ is merely a proxy for the combined effect on density of mass and gravity.
It is varying mass densities caused by uneven surface heating that sets up the convective circulation which then applies the negative system response whenever the combined thermal effect of radiation and conduction goes out of line with the amount of energy required to maintain radiative balance for the whole system.
GHGs and especially water vapour are merely lubricants for the convective process.
The visible climate response from our perspective is shifting climate zones but the effects of variations from sun and oceans are so huge that we could never identify our miniscule contribution.
This post from Willis is the ultimate logical conclusion to be derived from his initial thermostat hypothesis (which was limited to tropical convection) but still requires recognition of the physical processes behind it all.
This is good demonstration Willis. Probably the most direct evidence yet of regulation happening.
Perhaps a finer colour scale would help the colour guide jumps from -0.6 to -1 which is a huge difference and makes it a but hard to judge how well it correlates.
I’m not surprised though , this is very much in line with what my volcanic stack plots showed (though this is much more concrete proof). I showed it was mainly tropical ocean with ex-tropics showing less recovery and stability. I also showed NH was less stable and linked this to larger land area.
The volcanic data is a nice complement to this though because it shows the response to a strong and specific perturbation, not some hypothetical degree of centennial scale change.
http://climategrog.wordpress.com/?attachment_id=310
What did surprise me in your graph is four decorrelated areas against the major continents. The Peruvian region is readily understood as upwelling cold water of La Nina providing a strong (non radiative) external input the disrupts the broader correlation.
However, the other three did surprise me, seeming just a clear and strong.
There would seem to be a relationship with the major ocean gyres pulling down colder polar waters into the loop. This again would suggest that the feedback is primarily sensitive to impinging radiation than SST itself.
I think these four zones that you have found demonstrate and importan phenomenon and should provide key insight into how this regulator works.
Nice work.
”In the consensus view, the system works as follows. When the GHGs increase, the TOA upwelling longwave (LW) radiation decreases because more LW is absorbed. In response, the entire system warms until the longwave gets back to its previous value, 240 W/m2. That plus the 100 W/m2 of reflected solar shortwave radiation (SR) equals the incoming 340 W/m2, and so the equilibrium is restored.”
While this is perhaps the most succinct explanation of the consensus view I have ever seen it glosses over several key points that expose some of the additional problems with the view:
In the consensus view, the system works as follows. When the GHGs increase, the TOA upwelling longwave (LW) radiation decreases and downwelling IR increases because more LW is absorbed. The increased downwelling radiation decreases the surface net radiation transfer to the atmosphere by radiation. Assuming no other energy transfers from the surface to the atmosphere increase, the surface warms and due to the Stephan-Boltzmann Law must emit more radiation. The entire system warms until the longwave gets back to its previous value, 240 W/m2. That plus the 100 W/m2 of reflected solar shortwave radiation (SR) equals the incoming 340 W/m2, and so the equilibrium is restored.
This portion seems to be shared by both views:
”the TOA upwelling longwave (LW) radiation decreases because more LW is absorbed”
Is there any real world evidence for this?
Another view:
When GHGs increase, both the TOA upwelling longwave (LW) radiation and downwelling longwave (LW) radiation increase because more LW is absorbed therefore more LW is emitted, not being a black or grey body GHGs emit what they absorb* (as opposed to emitting in proportion to their temperature). The increased downwelling radiation decreases the surface net radiation transfer to the atmosphere (slows the cooling) by radiation causing more energy to be transferred to the atmosphere by other processes like evapotranspiration thus keeping the surface temperature relatively unchanged since it is temperature gradients that drive heat transfer not radiation balances. The increased water cycle activity (i.e.: evaporation) increases the albedo of the atmosphere decreasing the solar energy absorption thus leaving the temperature of the atmosphere relatively unchanged as well (the increase in LW is offset by the decrease in SW). So, if there were a panel in figure 1 for this view the numbers would be around 101,241, & 390.
* More technically correct would be to say they may emit IR due to energy gained by absorbing IR or through collisions depending on a host of variables.
I favour your explanation. I have always had grave doubts about the claimed amplification of CO2 warming by water vapour since this would be potentially dangerous for our water planet. Any forcing that raised the temperature and resulting evaporation could trigger runaway warming by means of this positive feedback loop. Given that our climate is remarkably stable, positive feedback seems very unlikely.
Water vapour is a GHG, so there must be another mechanism to limit or prevent the amplification scenario. This is cloud formation which acts as a cooling sun shade through reflection of incoming shortwave. Furthermore, cloud formation removes water vapour GHG from the atmosphere. This, I think, is the GHG warming limiter or thermostat.
I guess the GHG induced warming increases water vapour but also convection, transporting the vapour to higher in the atmosphere where it condenses to form clouds. In a dynamic process, this may not even be noticeable.
Dear Willis, very fine work. Thanks
The GHG model predicts the famous hot spot over the tropics and increased humidity, neither of which have ever been found. This alternative mechanism has no need for these effects.
Note that beneath a completely transparent atmosphere the job of adjusting albedo is dealt with by winds causing the uplift of surface dust.
We can see some evidence for that on Mars which lacks water.
Periodically, the Martian winds become strong enough to create planet wide dust storms. That is the convective adjustment process in action on a dry planet.
Willis writes “In the consensus view, the system works as follows. When the GHGs increase, the TOA upwelling longwave (LW) radiation decreases because more LW is absorbed. In response, the entire system warms until the longwave gets back to its previous value, 240 W/m2.”
Although this description isn’t strictly incorrect it is simplified to the point where it is misleading. You only need to change it a bit to actually make it the consensus view, however. Something like this…
In the consensus view, the system works as follows. When the GHGs increase, the TOA upwelling longwave (LW) radiation decreases because the average altitude increases at which it can leave and this greater altitude is colder.
In response, the entire system warms until the temperature of the new higher average altitude is such that the LW leaving gets back to its previous value, 240 W/m2.”
Personally I think the consensus view itself is a crock because its just one part of a complex process that naturally maximises its entropy and hence “the whole system” doesn’t want to warm.
great work again willis . the climate “scientists” will not like it though.far too simple and no funding required for carrer extending “research”.
On Lovelock’s Daisy world the white daisies are favored as radiative forcing rises because they reflect more sunlight thereby maintaining surface temperatures.
Clouds are the white daisies on Earth.
All 3 diagrams are wrong.
Let us consider the system called “GHGs” in the pictures. According to the pictures it absorbs 390 W/m² and emits 240W/m² (averaged values over 24 hours).
Therefore it “keeps” 390 – 240 = 150.
Where can this “kept” power (W/m² is a power unit) go ?
Well the only place is the heating of the whole atmospheric column.
An atmospheric column of 1 m² with a pressure of 1 atm weighs about 10 000 kg.
The specific heat capacity of air at 0°C is Cp ~ 1000 J/kg/K. We neglect here the variation with temperature because we only want an order of magnitude.
So in 1 second (1 W = 1 J/s) the atmospheric column with base of 1m² will increase its temperature by 150/(1000 x 10000) = 0.000015 °C.
Using here dQ = Cp . m . dT.
How long would it take for the column to reach 450 °C where it would basically burn everything and boil the oceans ?
Well 450/0.000015 = 30 000 000 seconds = 1 year.
As the oceans are obviously not boiling, the pictures are wrong and in reality if the ground emits 390 W/m², then whatever the GHG emit (here 240 W/m²) is also what they absorb (here 240 W/m²)
Up until now I knew negative feedbacks would dominate because the climate signal appeared to me to have the features I expect from a system with strong negative feedback. There was no concrete proof I was right, but experience and judgement told me I was.
Now you have shown me that there really is proof for what I would at best describe as a “well founded hunch”.
I’ve recently been working on uclimate.com and through that work I’ve not only discovered just how many sceptics are actively blogging, but as the “links” page shows, sceptics are far more active than warmists. That backs up my perception that the warmists have gone into retreat.
Willis, your code ran a treat, no messing, very nice. I see you’ve change the range of colour scale which is better, but it would be much better with more than six fixed increments. It can’t see where to change that. Is it hard-coded in the map library you use?
Willis, you’ve made the same mistake again, using real data and finding a stable system. You need a proper model where any stability is just the the Global Warming Tiger lulling you into a false sense of security before it pounces….
Willis
In your diagrams you depict in coming solar as being reflected off the top of the cloud.
You depict incoming solar as reflecting off the surface and then it appears that it passes straight through the cloud and out into space..
Why is not some part of the solar that is reflected off the surface onto the underside of the cloud, reflected back off the underside of the cloud downwards back to the surface.
If a cloud, its top, can reflect incoming solar back out to space, why cannot a cloud, its underside, reflect reflected solar from the surface back towards the surface?
After all even on a cloudy day with low level cloud it is not dark which suggests that solar is being rflected from the underside of a cloud back towards the surface. Further when a cloud interrupts solar, it is not pitch black in the shaddow area of the cloud. This suggests that either some part of the incoming solar penetrates its way through the cloud, or some solar that has been reflected from the surface, interacts with the underside of the cloud and is re-reflected back towards the surface thereby illuminating the surface in a diffused manner.
TimTheTolMan said:
“In response, the entire system warms until the temperature of the new higher average altitude is such that the LW leaving gets back to its previous value, 240 W/m2.”
Yes, as I’ve said so many times, the higher radiating altitude becomes warmer and so lets energy out faster whereas the AGW view is that the higher radiating altitude is colder and so lets energy out more slowly.
The higher, warmer, radiating point removes the need for any significant surface warming but does involve circulation adjustments.
You probably say this because someone told you that half of the incoming solar radiation is in the infrared. But this is the near infrared, it is not longwave infrared. The proportion of solar radiation with wavelength greater than 5 microns is negligible in comparison to the radiation emitted from the Earth’s surface itself. It’s safe to say that if we detect radiation shorter than 4 microns then it is from the Sun (or a rocket engine or a furnace) and that infrared radiation above 5 microns is from the Earth or its atmosphere.
All warm bodies emit electromagnetic radiation. The distribution of that radiation accords with Planck’s Law and depends only on the body’s temperature and its emissivity. To find where the peak emission will be simply divide body’s absolute temperature into 3000. For example, a body at a typical Earth temperature of 300K will have a peak emission of 3000/300 = 10microns. On the other hand the Sun, with a surface temperature of 6000K, will emit its peak radiation at 3000/6000 = 0.5 microns. This is Wien’s Law (or more exactly an approximation to it. Use 2897 instead of 3000 for a precise answer).
You can see from the above that a material will emit according to its own temperature. Since the Sun at 6000K does not manage to heat the Earth to 6000K but only to, say, 300K, then the Earth radiation will be LW and the Sun’s radiation is SW.
In Willis’s Fig 1 diagrams just replace the vast majority of what he terms GHG absorption with conductive absorption by the mass of the atmosphere and then there you have it.
If there is too much atmospheric absorption the surface radiates more out than comes in so the system cools and if there is too little atmospheric absorption the surface radiates less out than comes in and the system cools.
Convection changes to negate the thermal changes either way.
You have to consider the system as a whole and not just the surface because the practical effect of atmospheric mass floating above the surface is to ‘smear’ the location of the surface up through the vertical column.
That is why you cannot apply S-B at a surface beneath an atmosphere containing any mass at all.
Whoops, a typo:
if there is too little atmospheric absorption the surface radiates less out than comes in and the system WARMS.
“if there is too little atmospheric absorption the surface radiates less out than comes in and the system WARMS.”
That’ll that new “convection absorption” I presume. So once the surface warms due to lack of “convection absorption”, according to S-B it will emit LWIR which will get conventionally absorbed by the atmosphere and re-radiated.
We are back to the usual physical description.
StephenWilde, as always, I find it very difficult to understand what you are trying to say. What for example is ‘conductive absorption’, a term meaningless to me?
The important thing to understand is that the radiation from the surface of the Earth, or anything else for that matter, depends only on that body’s own temperature and emissivity. Nothing else! It doesn’t care what is happening in the atmosphere somewhere else. It is not effected by convection, evaporation etc., just its own intrinsic properties of temperature and emissivity. It’s quite simple really, why make it more complicated.
By the way, what is meant by “an atmosphere containing any mass at all”. Are there some atmospheres with no mass?
richard verney says:
In your diagrams you depict in coming solar as being reflected off the top of the cloud. ….
Once it interacts with Earth , rather than flying past, SW will either be reflected (after one or many reflections) or be absorbed. In the latter case it ends up as heat. You don’t need a ray diagram for each photon.
‘conductive absorption’ (not convective absorption) is just conduction but I added the term ‘absorption’ to match the term ‘GHG absorption’ used by Willis.
Gases absorb energy by conduction from a surface and such absorbed energy is not available for radiation out whilst it remains absorbed.
The length of time that energy is stored by the atmosphere’s mass before it is returned to the surface determines the scale of the mass induced greenhouse effect.
Convection both takes away upwards the energy conducted to the air at the surface and then returns it again on the descent half of the cycle for a zero net energy exchange with the surface.
The time taken for the convective cycle creates the greenhouse effect and radiative gases speed that cycle up so as to offset the slowing of energy transmission caused by their re-radiation back to the surface.
Exactly as proposed by Willis but he doesn’t seem to acknowledge the role of conduction.
“By the way, what is meant by “an atmosphere containing any mass at all”. Are there some atmospheres with no mass?”
I was pointing out that the amount of mass is not critical but that some mass is needed for the conductive interaction with the surface.
When one considers concepts such as a perfectly transparent atmosphere then that is implicitly an atmosphere with no mass at all because any mass at all prevents perfect transparency.
It was not me who first started using such unrealistic terminology.
At noon I am measuring a clear sky at -30°C, the ground is 7°C and the air temperature is of 9°C. When it is cloudy at Noon the cloud temperature is 5°C and the ground and air temperatures are 8°C.
A big change in sky temperature doesn’t make a lot of difference to the ground and air temperature.
”
phillipbratby says:
January 7, 2014 at 10:42 pm
You have a major error here. You have conserved energy flux, whereas you should conserve energy. The area of the incoming flux is the cross-sectional area of the earth. The area of outgoing flux is the earth’s surface area, which is a factor 4 smaller.
”
You’ve got it backwards. Incoming flux is like sunlight hitting a disk of radius R, area PI*R^2, while outgoing flux is from the whole surface of a sphere, 4*PI*R^2.
That’s a lot of words to say “heat causes clouds”. This is hardly a new hypothesis for us on this side of the fence.
Willis,
One of the things I’ve noticed is that when one goes to the simplified Stefan’s law model concepts, they fail to realize that for a given altitude ‘shell’ of atmosphere, when additional GHGs are added, not only is more radiation absorbed, but also the emissivity increases, requiring less temperature to emit the same amount of power. What’s more, that radiation amount is increased for upward as well as downward, requiring more energy transport to that shell in order to maintain the same temperature. Finally, that shell is not really like a solid surface at a given temperature but has only a very small amount of absorption and emission according to the spectrum of the combined GHGs and its temperature so adding GHGs require the increase in the emissivity factor – which is really just an engineering kludge when what is really happening is highly wavelength dependent.
Note that the increased radiation does not totally compensate for the added GHG absorption. Also, what is absorbed tends to be absorbed quickly and emitted quickly so far as distances go. Strong absorption areas of the spectrum have very short paths anyway. As one travels upwards though the pressure drops and the spectral lines get narrower, affecting a smaller amount of the spectrum.
Your basic model idea is very much along the ideas I’ve concluded (and have not had any time to work on for a few years now – which is along Lindzen’s IRIS theory ). Keep up the good work, I think you’re on a roll.
Cloud feedback is Negative.
The -1.0 W/m2/century SW reflectance trendline on a temperature change calculated of 0.3C/century signals a feedback value of -3.33 W/m2/K. The IPCC AR5 report put the cloud feedback at +0.7 W/m2/K.
Using this -3.33 W/m2/K value for the cloud feedback drops CO2 climate sensitivity to 0.75C per doubling from the theory’s 3.0C per doubling.
Suppose that the bulk of the inter-month cloudiness-anomaly variation is random. A consequent reflected-short-wave-radiation variation and, I assume, opposite surface-temperature anomaly variation would likely result in the negative correlation between upwelling long- and short-wave variations that Mr. Eschenbach illustrates.
And that would occur even in the absence of any dependence of albedo on temperature.
Of course, this causation-direction assumption ignores Mr. Eschenbach’s previous observations concerning earlier tropical-thunderstorm occurrence on hotter days. Still, there must be some random (or at least chaotic, which is the same thing for present purposes) component to the albedo signal.
I assume there’s no really good way of teasing these different-causal-direction effects apart, but perhaps someone can see how the data’s time scales might tend to favor one over the other?
“Gases absorb energy by conduction from a surface and such absorbed energy is not available for radiation out whilst it remains absorbed.”
I think this is convection. Normally, convection includes advection and diffusion. The latter is neglibile – still air is a very fine insulator.
http://en.wikipedia.org/wiki/Convection
There’s no conduction in the atmosphere, stop the movement of air and heat transfer reduces drastically (basically stops), except for evaporative or radiative transfers.
Max Hugoson says: @ January 7, 2014 at 8:49 pm
Bad amatuer…
>>>>>>>>>>>>>>>>>>>
It could be worse. Listening to This could be the punishment.
Kevin Kilty says: @ January 7, 2014 at 9:20 pm
Very interesting….
2) You have shown the correlation, but what can you do to establish causation?
>>>>>>>>>>>>>>>>>>>>
Have you read Willis’s The Thermostat Hypothesis and Further Evidence for my Thunderstorm Thermostat Hypothesis
This is the last of several essays/papers on this subject by Willis.
Willis,
I hope you will address MikeB’s comments, as they form the basis for practical infrared thermometry and photography, which in turn, is verified through contact thermometry. Specifically, what is the mechanism behind this shift in wavelength?
Scientists on both side of the debate are focused on understanding the role of cloud formation in regulating the energy budget. Unless I’m mistaken, none of these studies postulate that increased cloud formation causes a shift in the wavelength of emitted energy.
Kelvin Vaughan says:
At noon I am measuring a clear sky at -30°C, the ground is 7°C and the air temperature is of 9°C. When it is cloudy at Noon the cloud temperature is 5°C and the ground and air temperatures are 8°C, A big change in sky temperature doesn’t make a lot of difference to the ground and air temperature.
And what is the sky temperature on a clear, dry day? (Well away from direction of sun)
“Gases absorb energy by conduction from a surface and such absorbed energy is not available for radiation out whilst it remains absorbed.”
Energy is energy. Some energy absorbed by a molecule due to heat or thermal collisions will be radiated. Some energy absorbed by a molecule as radiation will be converted to thermal and not be radiated. How a gas acquires energy does not determine how that gas radiates energy.
Richard111 says:
January 8, 2014 at 12:02 am
Actually, the surface emits at all frequencies, but the relative amount in those 2 bands is insignificant when compared to the amount at 15 microns.
CO2 both absorbs and emits in the same frequency band – IR at about 15 microns. When the temperature of the air is lower than the temperature of the surface, CO2 absorbs more than it emits. When the ground is cooler, then the CO2 emits more than it absorbs. What most people miss is that the majority of the radiation is absorbed less than one foot from the surface.
Kevin Kilty says:
January 7, 2014 at 9:20 pm
“Very interesting. I’m not surprised at the result.”
Comon’ Kevin, you’re not surprised because you’ve had a good education on the subject from Willis over the years. It’s not being trumpeted by the mainstream of climate science. Basically no one in the IPCC cadre is buying into this – it kills the golden goose. Willis’s theory has caused a lot of heartburn in the “community”.
I think there is a misunderstanding in Willis’s CERES analysis. The upwelling LW channel produced by CERES is Surface IR which is confined to the window wavelength range of 8-12 μm, this range is unaffected by GHGs. The expectation is therefore that if the cloud concentration goes up backscatter to space of incoming SW will increase but backscatter of LW towards the surface and absorption of the surface LW by the water droplets in the cloud will also increase. This means that the presence of the clouds will reduce the upwelling LW at the same time as it increases reflected solar leading to the negative correlation. This effect has nothing to do with GHGs.
Just thinking aloud… Condensed water vapour can form a dispersion of sub-micron liquid droplets. which would appear invisible or very slightly misty at most. These would no longer have the GHG properties of the water vapour. They would still scatter incoming solar radiation. So although we talk about clouds, these are collections of much larger droplets and may not form unless there is appropriate seed particles for nucleation to occur. The point is that I don’t think you need actual clouds to achieve the effect that Willis describes. You just need to block or scatter the incoming SW.
Robert Clemenzi says:
January 8, 2014 at 6:22 am
Richard111 says:
January 8, 2014 at 12:02 am
My understanding is that the surface does not emit in 2.7 and 4.3 micron bands so there is no effect there.
Actually, the surface emits at all frequencies, but the relative amount in those 2 bands is insignificant when compared to the amount at 15 microns.
Please, just what energy is CO2 absorbing from the surface?
CO2 both absorbs and emits in the same frequency band – IR at about 15 microns. When the temperature of the air is lower than the temperature of the surface, CO2 absorbs more than it emits. When the ground is cooler, then the CO2 emits more than it absorbs.
Not correct because the emission by the CO2 is not immediate and is orders of magnitude slower than loss of energy by collisions to surrounding molecules when in the lower troposphere. In that region of the atmosphere CO2 always absorbs more than it emits.
What is meant by surface.
Surely it’s not skin surface. It’s not being measured. It’s not increasing.
If what is meant is surface air temperature. Highest surface temperature is
not increasing.
So that leaves higher average surface air temperature. Which is increases in
average in higher air temperature and/or less cooling of coldest/colder air temperature.
The fact that one isn’t getting highest *ever* air temperatures nor highest *ever* skin
surface indicates problem with idea surface getting warmer. Which leaves us with reduction
coldest ever coldest air/skin surface temperature and/or less cooling of average cool
temperature.
And it doesn’t seem this the argument which is being made and until make this the argument
they wasting their time. Or there is no evidence of anything else.
An increase in clouds, whatever the cause, results in blocking surface IR and increasing reflectivity. The negative correlation says nothing about the greenhouse effect.
Hi Willis,
Very nice graphics. A couple of comments:
1. High latitude regions in winter have zero upwelling short wave (24/7 darkness). The correlation between SW and LW should then fall to zero, because upwelling LW would depend only on surface temperature and the the presence/absence of clouds. Right?
2. High latitude regions with snow/ice cover during the non-winter months will have high albedo, even with a clear sky, so the SW/LW correlation again will drop, since albedo (upwelling SW) will not be as much influenced by cloud cover, while upwelling LW will be.
3. Land areas outside the polar regions will have somewhat lower correlation because the clear-sky surface albedo is greater than the clear sky ocean albedo (which is very low); once again the influence of clouds is somewhat reduced compared to most ocean areas.
“Gases absorb energy by conduction from a surface and such absorbed energy is not available for radiation out whilst it remains absorbed.”
Huh? It certainly is “available” for radiation, but that radiation (should it happen) will be in accordance with the material properties of the gas, or liquid, or solid; far more important than the Plank temperature in this context.
Pretend that we know what happens to all the incident LW, that it gets absorbed and involved in a food fight between atmospheric and surface H2O, which happens to adore it, until scraps fly back to space.
What of the SW? It’s a lot more skittish. Most (?) of it gets reflected off clouds and ice and bright land and various shiny things. Water in its various forms does not absorb it efficiently. Does anything? Dirt? The ground and metals certainly warm in the sun but is that from LW or SW?
So now the SW enters the ocean where it passes through some 100 meters but is refracted, reflected, prismaticly separated, and generally dissipated by dissolved and suspended stuff. Perhaps the oceans are the SW-LW converters?
Good work, Willis.
The phrase “removal of the seasonal signal” begs the question of what the data looks like seasonally. Would it be possible to see the correlation map for Dec-Jan, Mar-Apr, and/or June-July?
I am also concerned about the blending of all 24 hrs into one graphic. Your thermostat hypothesis operates on a time scale as short as 15 minutes. Reflected solar SW is a daylight process. Emitted Longwave is a 24 hrs, with power that veries by temperature. Integrating the fluxes over the day ought to give a good answer, but I still have the question whether we are missing something important at hourly scale. But given CERES data isn’t hourly, (only the GOES-converted data is hourly), the data may not be available.
On the diagram, I bristle at the Trenberth diagram which uses clouds as a one-way mirror on the SW ray path. LW is also affected by clouds. LW is absorbed by clouds and emitted by clouds. Clouds have a thickness and a temperature difference across the top and bottom. Maybe as viewed by the CERES instruments, integrated across the 24 hrs, it make no difference to your work.
Thanks Willis, this article is very good.
You keep on driving nails to shut down the CAWG coffin.
Your graphs show that anti-correlation is the dominating norm between incoming SW and outgoing LW. More evidence that there is at least one regulator (governor, thermostat) in our climate system. Lindzen pointed to another. Probably there are more, but we are too invested in throwing money after CO2 as a the direct control for global temperatures to let it go.
TomVonk says:
January 8, 2014 at 2:00 am
Tom, it appears you haven’t realized that those are by no means the total system diagrams, so let me be the first to inform you—there was no attempt to cover anything but the two outgoing radiation streams (LW and SW) and the incoming radiation.
So no, the diagrams are not wrong, they were never meant to show the other details.
w.
@Geoff Sherrington:
The “yellow” areas near continents are places where the respective ocean gyres puts cold water off shore. Very low evaporation. Leads to very low rainfall in the land next to them and sometimes a Mediterranean or desert climate zone. I would interpret this as saying that very cold water areas can’t make much cloud.
@Greg:
I can attest from personally jumping into it that the yellow area off of N. California is darned cold. The temps run about 45 F on a warm day… It’s the return path of polar cold water toward the equator for another round of heating and recirculation…
@gymnosperm:
The way SW is converted to LW is that a molecule has several “modes” of oscillation. Especially those with three atoms in them. A SW is absorbed, and sets the whole thing wobbling and spinning and even the ends bouncing in and out. Some of those modes have lower energy levels than the original SW. They can emit a LW photon of that sized energy package.
Also note that an atom or molecule could absorb a SW and be unable to emit LW (say, being a He atom) and yet it could whack into an Ozone or CO2 or H2O and transfer some of the energy to that other molecule, which could then emit a LW photon to dump that part.
It is more rare, but also possible for two LW photons to be absorbed, then one SW photon emitted.
Greg says:
January 8, 2014 at 2:15 am
The colors are set in the file “CERES Functions.R”. It’s not part of the map library, it’s set by statements like:
Chop and change as you wish …
w.
Willis, As always I’m glued to your dissertations. As a long retired military forecaster I have a direct question for you. To keep my hand in this I’ve purchased one of Anthonys touted Davis Instruments, a fairly sophisticated one. I measure incoming shortwave radiation everyday. Here in New Zealand it’s fascinating to watch how it changes with not only higher relative humidity (downward), high cirrus (downward) and general cloud cover (downward). Should you graph the values they go up and down like a yo-yo. My question concerns the values. On a low humidity day and cloudless sky, readings of 1500 w/m2 are common; much higher than what you indicate and many texts indicate. Why the discrepancy?
richard verney says:
January 8, 2014 at 2:40 am
It’s just a simplistical diagram. You are right, there is scattering both on the downwards and upwards paths. Numbers quoted are therefore net numbers …
w.
It is interesting that most of the -1 areas in figure 2 are between the horse latitudes and generally follow the upper flows of the Hadley cells.
gbaikie says:
January 8, 2014 at 7:57 am
What is meant by surface.
As far as the surface IR measured by CERES it refers to the temperature of the solid/liquid surfaces of the earth, it does not refer to atmospheric emission (which doesn’t exist in this wavelength range except for ozone which is corrected for using other satellite measurements of ozone).
Rob Ricket says:
January 8, 2014 at 5:53 am
Yes, and I hope that when people ask me questions, they quote whatever they are talking about. Both of us look to be disappointed in this interchange.
Look, Rob, I run on limited time. I have a day job, I do the scientific research, I write it up, and I answer questions. Somewhere in there I sleep, but not much.
So if you, or anyone else, want to get a comment from me, then you need to quote, cite, or otherwise indicate what you are talking about. I’m not going to run off and root through MikeB’s comments, and reply to one of them, only to find out that the comment I replied to wasn’t the comment that you were referring to.
I’m doing the hard part in this game, folks, the least you can do is do your damn homework, identify whatever it is you are talking about, and cite, quote, or otherwise identify it.
w.
Robert Clemenzi says:
January 8, 2014 at 6:22 am
I don’t believe that for one minute. Citation?
My bible in these matters, “The Climate Near The Ground” by Geiger, says that going the other way, downwelling radiation, the situation looks like this:
Layer thickness Percent share of downwelling radiation
1st 87 metres above the ground — 72%
Next 89 metres above the ground — 6.4%
Next 91 metres above the ground — 4%
So the majority (72%) of the downwelling radiation comes from the first 300 feet of atmosphere above us, and 82% comes from the first thousand feet. Given that, the idea that the upwelling radiation is absorbed in a single foot of atmosphere seems highly unlikely.
w.
Phil. says:
January 8, 2014 at 7:33 am
Nonsense. If that were the case, the upwelling radiation measured by CERES would be on the order of 390 W/m2, the average radiation of the surface.
But the CERES data says the outgoing IR totals 240 W/m2, not 390, and that’s just what we’d expect. And I can produce for you a very nice map showing exactly how much of the surface radiation is absorbed in different parts of the world. It matches very nicely with the amount of our favorite GHG, water vapor.
Sorry, but you seem to have misread something, because your claim is completely false.
w.
“I hope that when people ask me questions, they quote whatever they are talking about”
I agree. Of course I don’t care much for the way many of the websites work. People should be able to highlight some words and then go something like CTL r and have the quote appear in the reply box. Maybe there’s a way to do that here, but I don’t know what it might be.
Willis top post: ”In response, the albedo increases proportionately, increases the SR. This counteracts the decrease in upwelling LW, and leaves the surface temperature unchanged.”
This would imply in effect the Tmean is forever fixed at ~288K (the thermostat set point) and anomaly about the set point would be zero mean with fixed hysteresis. Thermometer evidence shows Tmean is not a fixed set point. Anomaly reports show monthly differences unlike thermostat fixed hysteresis.
Comments?
Stephen Rasey says:
January 8, 2014 at 8:42 am
As you are the second person to comment on this, I’ve changed the diagrams for greater clarity.
w.
Dave Dardinger says:
January 8, 2014 at 9:18 am
Highlight the words you are interested in, press CONTROL-C, go down to the comment box, press CONTROL-V …
w.
Trick says:
January 8, 2014 at 9:20 am
I would comment, but I’m totally unclear what you mean. Bear in mind what I said above:
w.
“Chop and change as you wish …”
Thanks, I added two more colors but I still only get six in the legend range, yet I can’t see where the number of intervals is assigned.
However, I see the legend numbers are not too accurate, lots of crude rounding going on.
maxcolor=.25,mincolor=-1,roundto=2,legendlabel=””
There is a world of significance difference between -0.6 and -1, can you say exactly what interval is getting coloured as “-1” in your graph?
I think this would really be a lot better if it had a continuous colour scale (or at least 10-20 nuances). As it stands it could be over-selling the result.
No knocking it, there is clearly some good information presented but I’m sure you don’t want to give a false impression that there are large swathes with CC near -1 if that’s not the case.
Isn’t there a question here about the direction of causality? Willis is interpreting the anti-correlation between upwelling SW and LW as support for his theory about cloud formation acting as a thermostat (a theory that I find compelling). But there is also a simpler explanation for this anti-correlation. Where clouds block incoming solar the planet below warms less, leading to less outgoing LW. It seems likely to me that this direction of causality (where cloudiness is the initiating cause) dominates the data, making it hard to say anything about what causality might be going on in the other direction (where cloudiness is the effect).
Would be similar to the correlation between temperature and CO2, where the paleo-data is dominated by the direction of causality where rising temperatures cause CO2 to bubble out of the oceans, making it difficult or impossible to discern causality in the other direction. CO2 certainly COULD be having a warming effect, and we know on theoretical and experimental grounds that it should have a small forcing effect, but the paleo-data gives us almost no information about its net effect.
I think the thermostat hypothesis is correct but I’m not sure that this particular anti-correlation provides much or perhaps even any evidence for it.
“This would imply in effect the Tmean is forever fixed at ~288K”
Do you understand what correlation coefficient means. If not, you will need to understand the post and the graph.
Willis, as per your request, this is the comment from MikeB that I was referring to:
About half of TSI is longwave in the first place
You probably say this because someone told you that half of the incoming solar radiation is in the infrared. But this is the near infrared, it is not longwave infrared. The proportion of solar radiation with wavelength greater than 5 microns is negligible in comparison to the radiation emitted from the Earth’s surface itself. It’s safe to say that if we detect radiation shorter than 4 microns then it is from the Sun (or a rocket engine or a furnace) and that infrared radiation above 5 microns is from the Earth or its atmosphere.
All warm bodies emit electromagnetic radiation. The distribution of that radiation accords with Planck’s Law and depends only on the body’s temperature and its emissivity. To find where the peak emission will be simply divide body’s absolute temperature into 3000. For example, a body at a typical Earth temperature of 300K will have a peak emission of 3000/300 = 10microns. On the other hand the Sun, with a surface temperature of 6000K, will emit its peak radiation at 3000/6000 = 0.5 microns. This is Wien’s Law (or more exactly an approximation to it. Use 2897 instead of 3000 for a precise answer).
How then does a material convert shortwave to longwave?
You can see from the above that a material will emit according to its own temperature. Since the Sun at 6000K does not manage to heat the Earth to 6000K but only to, say, 300K, then the Earth radiation will be LW and the Sun’s radiation is SW.
Are you saying that cloud formation changes the frequency of the Earth’s emitted energy, or are you simply saying more clouds reflect solar SW radiation, but are transparent to emitted LW radiation?
Willis Eschenbach says:
January 8, 2014 at 9:16 am
Phil. says:
January 8, 2014 at 7:33 am
“I think there is a misunderstanding in Willis’s CERES analysis. The upwelling LW channel produced by CERES is Surface IR which is confined to the window wavelength range of 8-12 μm, this range is unaffected by GHGs.”
Nonsense. If that were the case, the upwelling radiation measured by CERES would be on the order of 390 W/m2, the average radiation of the surface.
No, because the window wavelength range of 8-12 μm is only part of the emissions from the surface. CERES explicitly states: “Each CERES instrument measures filtered radiances in the shortwave (SW; wavelengths between 0.3 and 5 μm), total (TOT; wavelengths between 0.3 and 200 μm), and window (WN; wavelengths between 8 and 12 μm) regions.” They also perform numerous calculations on the raw data so there is scaling going on.
But the CERES data says the outgoing IR totals 240 W/m2, not 390, and that’s just what we’d expect. And I can produce for you a very nice map showing exactly how much of the surface radiation is absorbed in different parts of the world. It matches very nicely with the amount of our favorite GHG, water vapor.
They term it “Surface Upwelling Longwave Radiation (rlus) Wm-2” so it is not subject to absorption by GHGs.
Sorry, but you seem to have misread something, because your claim is completely false.
Not according to the CERES site. Perhaps you’re using a different product, which data are you using?
Using this -3.33 W/m2/K value for the cloud feedback drops CO2 climate sensitivity to 0.75C per doubling from the theory’s 3.0C per doubling.
degrees kelvin. Natural variability alone per century is at least this much, and we don’t know how to predict the background natural variation “at all”.
Which is right at the lower bound, from the sound of it, of the new values snuck into AR5.
I’d suggest that this be stated, however, as a range.
This is the sort of thing that one does have to wonder about. Again, looking at the fluctuation-dissipation theorem one should actually be able to find the time-signature of causality in this, although it is going to be much more difficult because heating in one place (say, the tropical ocean) can easily cause cooling somewhere else because of lateral transport of the water vapor before the clouds form. This is obviously the case for nearly all of the clouds forming over the land masses, for the monsoon, etc. There is substantial bulk transport of both latent heat, LWIR emission (rom the clouds “created” from warmed ocean water elsewhere) and albedo.
The best place to look for the signal probably is the monsoon. Those are persistent long-time scale phenomena, and one would expect to see a consistent variation of SW/LW radiation from precisely this lagged heat transport from their primary oceanic vapor sources. Of course extracting any kind of signal from their substantial chaotic variation would be very difficult, and there could easily be other factors that are equally important obscuring the signal).
My recollection is that this is very much like what Roy Spencer did in a short time study of much the same thing (but only in the context of specific regional weather). There the causal time signature was very clear, and he also found the negative lagged correlation suggesting natural negative feedback. It would be interesting to see if this holds globally — instead of doing static correlation do lagged correlation and see if fluctuations are correlated in a lagged manner.
rgb
“I think the thermostat hypothesis is correct but I’m not sure that this particular anti-correlation provides much or perhaps even any evidence for it.”
Since >SST will cause evap, will cause cloud, it’s rather chicken and egg.
The primary driver must be changes in isolation even in the tropics. Perhaps something can be gained for looking at the annual cycle rather than dumping it. If more cloud happens when there’s more insolation, it implies a feedback.
Otherwise we could look at non seasonal changes in insolation:
http://climategrog.wordpress.com/?attachment_id=310
Greg says:
January 8, 2014 at 9:38 am
“Not too accurate”? “Crude rounding”? Take a breath, old son, and back off the insults, your complaint generator is set way too high. I’m happy to field comments and questions, that’s what science is about … but calling my work “not too accurate” and “crude”? Not polite, particularly when you don’t understand what you are looking at.
I use “roundto” to set the number of decimals displayed in the legend. If you don’t do that, you get numbers on your graph like “0.1544398264” in the display, and a graph containing something like that looks … well … crude. However, the variable “roundto” doesn’t affect the calculations, just the display.
In addition, if you think increasing the number of decimals displayed would make the slightest difference to the legend in Figure 2, think again. See below for why.
Consider Figure 2 above. The legend is accurate to 2 decimals. In fact it’s accurate to a hundred decimals, because when you divide the given range (from -1 to 1) into 5 equal intervals, you get 0.4000000… for the width of each interval. Since R doesn’t print trailing decimal zeros, this comes out at “0.6”, “0.2”, etc. So changing the roundto to 5 wouldn’t change the displayed output.
Regarding your other question, the colors show points on the scale, not intervals. The legend (with colors for say 1, 0.6, 0.2, etc) shows the color that is associated with that specific number.
All the best,
w.
If there would be only albedo increase as a feedback to the forcing induced by more longwave absorption then the model presented here could be valid. But there are other phenomena that need to be taken into account in the feedback mechanisms such as Planck’s response, change of lapse rate, water vapour, cloud coverage.
Anyway, it’s good to see that as much goes out as comes in, otherwise we would be freezing or frying.
@Willis:
I’m getting the picture from your comments that you can’t use CERES data for an energy balance, but your comment:
“In the CERES data, both the incoming flux and the outgoing flux are averaged 24/7 over their particular gridcell. They are not general measurements of the total global flux. As a result, there is no such error as the one you imagine.”
also doesn’t make much sense in this context. Isn’t the reason that there is an energy imbalance because the observations don’t cover all wavelengths? If not, then there has been a major error in communication of your results, because I doubt most people just from reading this article could could pass a quiz on where the energy is going, or even if CERES data indicates and energy imbalance. Further clarification may be required vis-a-vis why an energy imbalance in CERES data isn’t an imbalance in total solar energy flux for the earth’s surface.
Rob Ricket says:
January 8, 2014 at 9:57 am
Thanks, Rob. I don’t know that I explicitly said any of those, but in order:
• Cloud formation does indeed change the frequency of the emitted energy.
• More clouds do reflect more SW
• However, clouds are the opposite of transparent to emitted LW. In fact, they are generally considered as blackbodies for IR purposes, as they absorb ≈ 100% of incident longwave radiation.
w.
Willis Eschenbach says:
January 8, 2014 at 10:35 am
• However, clouds are the opposite of transparent to emitted LW. In fact, they are generally considered as blackbodies for IR purposes, as they absorb ≈ 100% of incident longwave radiation.
Each droplet in the cloud will absorb ~100% of the incident light and also scatter an equal amount of the incident light.
However, clouds are the opposite of transparent to emitted LW. In fact, they are generally considered as blackbodies for IR purposes, as they absorb ≈ 100% of incident longwave radiation.
And they strongly emit LWIR as well, and do so high in the atmosphere where there is much less of a GHG “blanket” between them and the TOA/space. As such they are active transport heat sinks: LWIR incident on the ocean surface is absorbed in the top millimeter, transformed almost entirely into latent heat by causing surface evaporation. The evaporated water vapor with its latent heat is vertically transported and cools via conduction with the lapse rate of the surrounding air and via radiation. When it condenses into clouds it gives off the latent heat, now much higher up in the atmosphere. In the case of upper troposphere clouds, the latent heat is relatively quickly lost. Down lower it may still have a substantial amount of atmosphere and lapse rate to work through.
This is why simple one slab or two slab atmospheric models don’t do very well. From some papers recently reported on WUWT, GCMs substantially underestimate the cooling potential of e.g. thunderstorms via the mostly neglected mechanism of direct, rapid transport of head-laden warm moist air aloft to where it is rapidly lost via radiation on the top of most of the GHG layer. Plus, of course, the modulation of albedo, plus the additional latent heat removal at the warmed Earth’s surface when rain falls and re-evaporates from the ground beneath. It’s basically a heat engine and runs by transporting heat from down low to up high.
rgb
Greg says:
January 8, 2014 at 6:01 am
And what is the sky temperature on a clear, dry day? (Well away from direction of sun)
That is away from the sun. The sun is low on the horizon and I measured directly above.
Don’t take offence Willis, I’m trying to make a suggestion to improve what you are showing , not to give offence.
“Regarding your other question, the colors show points on the scale, not intervals. The legend (with colors for say 1, 0.6, 0.2, etc) shows the color that is associated with that specific number.”
I realise what the scale shows , my question is what the graph shows. Clearly it is not just the points that get exactly -1.00000000, that R wants to print as “-1” that get coloured blue.
It seems that the legend label “0.6” is a truncated 2/3 , so what I was wondering was what _interval_ of values get the coloured on the graph.
My guess is -0.67<x<-1 but it could be perhaps half way between -0.67 and -1
I doubt any of the cells actually correlate at -1.0 , so it would be more informative and perhaps less misleading (depending upon exactly what the values turn out to be) to have more graduations.
If I could fix it easily I would have done it and posted the result for you to check out but R is a bitch to work with and I don't have a day free to waste on it's enigmatic and incomplete documentation, to fix something you can probably do in two minutes on code you wrote.
Neither do I have time couch everything in flowery language and conditionals , so please take comments in the spirit they are intended and not get shirty. As you know, I am supportive of what you are suggesting, I'm not trying criticise it other than to improve it and make it more convincing to others who will want to break it.
best regards.
Willis 9:33am: “..I’m totally unclear what you mean. Bear in mind what I said above: This is a great simplification, but sufficient for this discussion.
Global surface temperature 1.5F increased since 1880:
http://climate.nasa.gov/
Thermometer measured surface Tmean isn’t observed unchanged; interested in comments on why there isn’t compensation by albedo observed per your view top post Fig. 1: ”In response, the albedo increases proportionately, increases the SR. This counteracts the decrease in upwelling LW, and leaves the surface temperature unchanged.”
Kevin, “That is away from the sun. The sun is low on the horizon and I measured directly above.”
Well since you said you’d measured cloud, it would not seem to be the “clear dry day” I mentioned. OK, I’ll spell it out. We know emissions are proportional to T^4 where T is absolute temperature.
Space is about 3 kelvin. The difference between -30 C (~243)^4 and and 273^4 is not so great compared to 3^4. Now the atmosphere will still be emitting more than 3K but you can start to get my point. On _dry_ day (not just a gap between clouds on a day with high humidity) the sky can be much colder that what you related. A lot of what you measured as “-30” was thermal emission from water vapour a potent greenhouse gas.
Also there is substantial thermal inertia in the ground , so even when the sky clears don’t expect its temp to plummet in 10 minutes and start to draw conclusions about downward radiation.
Trick,
I sort of doubt Willis is proposing that it’s impossible for global surface temperatures to change at all, merely that there are mechanisms which regulate temps and keep them within certain boundaries.
Greg says:
January 8, 2014 at 11:25 am
Actually what you did was accuse me of using “crude rounding” and say my work was “not too accurate”. Hardly “suggestions”, and not that charming.
Take a range from -1 to 1. Divide it into 5 equal intervals. Two of them fall at plus and minus 0.600000000000 …
As I said before, they do not fall at 0.67. Now you’re just guessing, and I’ve already told you the answer. The colors in the legend are the colors of that point EXACTLY. I use a 100-point color lookup table that goes evenly from one end to the other through all six colors. I sample it at the stated point, and that is what shows up in the legend. On the graph, I use exactly the same procedure. If the correlation is +.36, it gets that color from the lookup table.
You say that … and other people have told me that I should have less than six colors. In any case, the interval from say -1 to -.6 goes evenly between the two colors shown in the legend. And yes, there are lots of results in the high 90s.
Now, on the Figure 2 graph I could have set the color range from -0.97 to +0.25, because that’s the actual range of the data. However, it is misleading because then the reds start in the negative correlations at about -0.5. So for correlations, I always keep the same color range, from -1 to +1.
I started programming computers in 1963. I speak half a dozen computer languages fluently, and another half dozen haltingly. I learned R maybe eight years ago. The idea that R is an “enigmatic” computer language is risible. It is the easiest languages to write and debug that I know of.
For example, in languages like C or Fortran or Basic or many others, if I want to add “1” to each cell in a map called “themap”, I do this:
For thelatitude = 1 to 180
For thelongitude = 1 to 360
themap[thelatitude, thelongitude] = themap[thelatitude, thelongitude] + 1
Next thelongitude
Next thelatitude
I have to go and manually add one to each cell. In R, on the other hand, you simply say
themap = themap + 1
Which one is “enigmatic” on your planet? Which is easier to write and debug?
Greg, I don’t care about “flowery language”. But when you don’t know what variables do, accusing me of using “crude rounding” doesn’t cut it. If you don’t know, ask.
Finally, you say that I know that you are “supportive of what [I am] suggesting” … sadly, I know no such thing. Are you the same “Greg” that was “Greg” last time? There are so many players and so many aliases, I don’t try to keep people identified. I react comment by comment. And normally, I just look at an accusation that I’m making mistakes, from someone who admittedly hasn’t parsed the code, and go “BZZZZT! Next contestant, please”.
But actually, in your case, I guessed that you were that Greg and not any of the many other Gregs on my many posts, and so I answered your boorish accusations that I’d made some crude error. Otherwise, I’d have just skipped over it. I’ve got little time for people who accuse me of errors without reading the code. I repackaged it and parsed it and cleaned it up so it could be usable, and I’m willing to answer questions about it.
But claims I’ve made a “crude” error when you haven’t read the code? Sorry, not on.
w.
PS—Plus, I don’t often make crude errors. In the spirit of full disclosure I must confess that I have made sophisticated, far-reaching, subtle, and too often devastatingly bad errors … but they are rarely crude.
Phil says: “Each droplet in the cloud will absorb ~100% of the incident light and also scatter an equal amount of the incident light.”
Cool that makes 200% then. Let’s call this Light Amplification by Simulated [sic] Emission of Radiation.
Wow! LASER clouds, I’d always wondered what all those lines in the sky were when I’d eaten mushrooms 😉
Willis, I feel so sorry that you constantly fall into the traps of AGW and this post is a good
example that you are unwilling to learn!
Two points, 1.) you employ the 340 W/m2 value as a fixed value (which is 1361 W/m2 divided by 4), but this TSI-value is an artifical construct for the solar OUTPUT, and the real Earth solar INPUT varies between 1318 and 1408, changing daily).
The IPCC agreed in 2006 to drop the SPIRAL advance of the elliptic Earth´s orbit around the Sun, fixing the OUTPUT of the Sun as the averaged INPUT (Insolation on Earth), which is not a, but THE major lie of the IPCC.
Therefore, in YOUR argument, you keep the effect of the Earth orbit as irrelevant or as Zero.
2.) as CERES shows, [and soon as the launch of the new RAVAN satellite in 2015 will show], there is a greater heat loss (outwelling from Earth into space) than solar inwelling. The increasing solar inwelling since the LIA (17.century) , due to a favourable Earth orbit closer to the Sun (a centuries long warming run of Earth around the Sun), stipulated the IPCC imagination that there has to be an equilibrium between inwelling and outwelling….. another false assumption, which both the measurents of CERES and of the Stockholm insolation of 50 years do not confirm.
Willis, free yourself from Warmist manure and keep going with critical eyes…Cheers JS.
Mark 11:46am: Then the center panel of Fig. 1 would apply. I’m interested in the view developed in top post resulting in the right most Fig. 1 panel. The mechanism of albedo change compensation in developing that view is interesting for discussion.
Alas, I do not have time to read the entire discussion to this point, but it seems that something has been missed or misunderstood at the outset. Basically, any “greenhouse” gas functions as a beamsplitter, reradiating any absorbed radiation both upwards and downwards. When there is scarcely any GH gas, there is no impediment. When the GH gas is “saturated” (no further addition will significantly alter the effective width and amplitude of the absorption spectrum, which is total for the defined width), the split will be 50-50. Intermediate values give intermediate results. Willis’s diagrams do not show this.
I used to work problems in radiative heat transfer when analyzing effects of high energy laser weapons, and the physics are the same. (By the way, a similar process occurs in the shortwave spectrum for blue, indigo, violet, and ultraviolet light, which is sent both up and down by Rayleigh scattering. If you don’t believe in down-scattered shortwave radiation, walk outside and check the color of the sky.)
“Anyhow, that’s today’s news from CERES … the longwave and the reflected shortwave is strongly negatively correlated, and averages -0.65 globally. This strongly supports my theory that the earth has a strong active thermoregulation system…”
Phil. is right on this one. The negative correlation is just a matter of the arithmetic used. Here is just one of many accounts on what CERES measures. It says:
“Each CERES instrument measures filtered radiances in the shortwave (SW; wavelengths between 0.3 and 5 µm), total (TOT; wavelengths between 0.3 and 200 µm), and window (WN; wavelengths between 8 and 12 µm) regions…”
“Since there is no LW channel on CERES, LW daytime radiances are determined from the difference between the TOT and SW channel radiances.”
IOW, what you are describing as upwelling LW is just (SW+LW)-SW. And since upwelling (SW+LW) pretty much balances incoming SW (solar constant), negative correlation comes from that arithmetic.
In atmosphere temperatures gases dosen’t practically emit or absorb any heat radiation (emission/absorbing factor 0,002 aprox), only in higher temperatures over 600C you can measure something like 0,05, in 1500C something like 0,2. Gases emits radiation only when they burn, basic thermodynamics, look Hottel tables. Tiny water droplets (humidity) is water and they absorb and emits much much better. There is norhing like greenhousegases in atmosphere as someone thinks. Heat transfer between ground and air is well over 99% only by conduction. Learn how heat transfers between different materials.
Willis, I did not say you’d made “crude errors” I said crude rounding. I don’t think there is an error just a lack of clarity. Maybe I should have said not precise rather than not accurate but something that is not precise when a precise value is available is not accurate.
The point was that from 0.6 to 1.0 is a big jump in correlation coeff.
I may be mistaken but all I see are the six individual colours on the graph. Any impression of nuance is adjacent pixels giving a blended effect.
regards. Greg.
Trick,
How do you figure that? I must be misunderstanding you. You appear to be saying that either temperatures are absolutely fixed in place or that they must be completely unregulated. I don’t understand what basis you have for making that assertion. Well, that or I simply don’t understand what you’re saying.
Could you suggest how I can get more than the six graduations on the temp scale ?
Michael 12:13pm: Willis has written above his diagrams are simplified, not showing some things.
BTW, all else equal, if earth had a pure argon atm., and you then walked outside from your proper environmental hut in a clear helmet spacesuit and checked the color of the sky, what color would you observe?
******
Mark 12:18pm: The albedo doesn’t compensate (392 changes up from 390) in center panel. In the right panel the albedo does compensate (390 unchanged). What is the interesting mechanism for this albedo compensation making 390 unchanged?
Trick,
Perhaps the cloud albedo compensation mechanism is imperfect one that does not completely compensate for changes, yet retards them to a large extent nonetheless. Who the heck knows?
Mark 12:35pm: “Who the heck knows?”
Yeah, think that would be the center panel view. Maybe Willis can add comments on his right side panel if he ever understands, interest has me asking.
Willis Eschenbach says:
January 8, 2014 at 9:12 am
Sorry – I misspoke. At 14,981.2nm, 63% of the IR energy is absorbed in 0.259 meters. However, that is the CO2 peak, not the average. The average is more inline with the numbers you provided.
For water vapor at 60%RH, in the 42 to 200 um band 63% absorption is typically in less than 2 meters, but with many spikes going to an inch or less. However, this again is not the overall average for the full spectrum – 4 to 500 um.
For these numbers I use a program that computes the spectrum using the HITRAN data. I apologize for not checking the graphs before making the post.
Willis:
My bible in these matters, “The Climate Near The Ground” by Geiger, says that going the other way, downwelling radiation, the situation looks like this:
Layer thickness Percent share of downwelling radiation
1st 87 metres above the ground — 72%
Next 89 metres above the ground — 6.4%
Next 91 metres above the ground — 4%
So the majority (72%) of the downwelling radiation comes from the first 300 feet of atmosphere above us, and 82% comes from the first thousand feet. Given that, the idea that the upwelling radiation is absorbed in a single foot of atmosphere seems highly unlikely.
w.
I’ve got an old Meteorolgy Text which has the citation for some work done in the 60’s using a tall tower in Texas that shows this conclusion to have merit. I’ll try to find the citation for you! (When I’m home. I’m working now to…doing FEA work, runs that take 15 minutes to 45 minutes. You probably have an idea of how complicated they are! BUT they are also backed by a variety of “reality checks”…)
Greg says:
January 8, 2014 at 12:04 pm
Phil says: “Each droplet in the cloud will absorb ~100% of the incident light and also scatter an equal amount of the incident light.”
Cool that makes 200% then. Let’s call this Light Amplification by Simulated [sic] Emission of Radiation.
No it’s standard light scattering, that’s exactly what happens nothing to do with emission or lasers (which are phenomenally inefficient by the way).
Read page 130 of this text for example:
http://www.che.utah.edu/~ring/ChE-6960/Chapter_5_Ring.pdf
The classic text on the subject is by van der Hulst which is extensively referred to in this reference. As far as I know it’s out of print now.
Wow! LASER clouds, I’d always wondered what all those lines in the sky were when I’d eaten mushrooms 😉
Stay away from those mushrooms!
Nick Stokes: “IOW, what you are describing as upwelling LW is just (SW+LW)-SW. And since upwelling (SW+LW) pretty much balances incoming SW (solar constant), negative correlation comes from that arithmetic.”
Sounds like reasonable argument, if that is the case, so in that case how can you explain the vast areas with low correlation? Everything should necessarily have strong neg. correlation.
Phil says: “Each droplet in the cloud will absorb ~100% of the incident light and also scatter an equal amount of the incident light.”
I don’t know what you though you were saying but that is patent nonsense, you can not both absorb and scatter 100% of anything.
Neither have you understood the pdf that you refer me to.
One thing I have done in the past is worked on numerical modelling of scattering of E-M radiation by atmospheric aerosols, rain, hail, sleet and slightly melted hail with a liquid surface….. heavy rain light rain, mixed rain with various models of raindrop size distribution, etc, etc. Our results were within 10% of empirically measured results.
But you don’t need professional experience to realise you can’t have your cake and scatter it.
Whether or not the emission is immediate is not relevant. Over land, it is fairly common for the atmosphere to be warmer than the surface. As a result, when there is a temperature inversion, CO2 emits more IR radiation than it absorbs.
As you say, the cornerstone of the AGW hypothesis is that increasing GHG reducs outgoing longwave radiation ot space (OLR). ONe of the most repoutabel sites for climate data is NOAA. They publish a month by month record of the measured OLR since 1980. I have downloaded and analysed this data as have others. It shows that between 1980 and 2010 OLR increased by 2.5 watts/sqM. To put the magnitude of this into perspective, a half doubling of CO2 (which is what we have since about 1900) would have reduced OLR by about 1.5 watts/sqM so the 2.5 increase is far from trivial. That, all by itself is enough to cast serious doubt on the entire theory of AGW. Jennifer Marohasy has been kind enough to post an article by me which covers this in somehwat more detail. Article title “AGW Falsified: NOAA Long Wave Radiation Data Incompatible with the Theory of Anthropogenic Global Warming”
Phil. says:
January 8, 2014 at 10:42 am
Huh? Typo on your part? You can’t both scatter and absorb 100%. Scatter is reflection. If you reflect 100% there’s nothing to absorb.
Next, clouds both absorb and reflect a variable amount of light, depending on the type and the thickness of the cloud. In no case is it anything like 100% for either one.
In any case, we were discussing longwave (IR) radiation, not light radiation.
Best regards,
w.
Greg Goodman says: January 8, 2014 at 1:03 pm
“Sounds like reasonable argument, if that is the case, so in that case how can you explain the vast areas with low correlation?”
I said “pretty much balances”. It’s globally constrained by conservation of energy. But there can be temporary storage of energy by cooling or warming the atmosphere (and the ocean, on a slower timescale). And spatial deviations due to circulation patterns moving heat around (so energy from incoming SW is still emitted, but not all where it entered).
J.Seifert says:
January 8, 2014 at 12:05 pm
Do your homework first, J. The code is posted. Nowhere in the entire analysis do I “employ the 340 W/m2 value as a fixed value”. In fact, this analysis doesn’t use the CERES solar dataset at all, so your entire claim is a total fabrication, BS stem to stern.
In other words, you don’t have a clue what you are talking about, but you insist on your right to tell me I’m wrong. You are a pathetic SIF, a “single interest fanatic” who tries to relate everything to one issue. In your case, the one issue relates to the fact that you don’t seem to understand the concept of averaging … but you’re willing to tell everyone they are wrong about averaging the solar radiation, EVEN PEOPLE LIKE MYSELF WHO ARE NOT TALKING ABOUT DOWNWELLING SOLAR RADIATION AT ALL.
So let me request that you go find some thread that actually relates to your fanaticism, and leave me alone.
w.
Michael J. Dunn says:
January 8, 2014 at 12:13 pm
Thanks, Michael. It would help if you told us what you think you missed or misunderstood …
Which “this” are you referring to that should show up in my graphs? And why would you expect whatever “this” is to show up in my analysis?
My analysis above relates to the changes in IR compared to the changes in reflected SW … where do you see anything about beamsplitters, or saturation, or what the amount of the split either is or should be? I could analyze that, it’s worth doing, actually I’ve done it and not published it … but that’s not this analysis.
w.
Stephen Rasey says:
January 8, 2014 at 8:42 am
Thanks, Stephen.
There seems to be some confusion, my responsibility. By the “seasonal signal” I meant the month-by-month average variations in the signal, also called the “seasonality” or the “climatology”.
To remove the seasonal signal, I average the data by month, express the averages as an anomaly around zero, and subtract the corresponding monthly average from each month’s worth of data.
In response to your question, if you don’t remove the month-by-month averages (the “seasonal signal) from the data, you get the following map:
Curious, huh? I suspected that this mostly reflected the seasonal changes rather than what happens in a month where it is warmer or cooler than average. So I removed the seasonality from the signal.
Thanks,
w.
Willis Eschenbach says: January 8, 2014 at 10:35 am
“Huh? Typo on your part? You can’t both scatter and absorb 100%.”
Not perfectly expressed, but the idea is right. Here is the vander Hulst relation. For long wavelength, Q is 2. That is the sum of absorption (1) and scattering, as a fraction of absorption. The amount of incident light scattered is equal to that absorbed. That includes light that was not going to hit the particle directly.
Nick Stokes says:
January 8, 2014 at 12:15 pm
Gosh, you mean that LW is equal to SW + LW – SW? Gotta say that’s a real shock, right up there with 4 = 7 + 4 – 7 … what’s your point?
You say that incoming solar is about equal to upwelling SW + LW. While this is generally true for the planet when averaged on a yearly basis, it is not true in any sense for the individual gridcells. On a gridcell y gridcell basis, the range for (solar – longwave – reflected) ranges from -200 W m-2 to + 200 W m-2. Not only that, the interquartile range is from -110 W/m2 to +60 W/m2 … and you call that “pretty much balances”???
Run the numbers first before bothering us with your theories, there’s a good fellow. Right now, I’m doing your homework for you and finding your errors, which doesn’t do your reputation any good.
w.
Willis, I am trying to better understand your position based on the diagram you have offered. It *appears* that:
Your expectation is that any change in the strength of the planet’s greenhouse effect is reacted to directly by the planet’s albedo, in an equal and opposite direction, the end result being that the surface temperature will be the same as it was before. But having left the passage of time out of this analysis leaves the question whether you expect this to occur instantaneously or…? On some unspecified timescale? At any rate: based upon this it appears your contention is that: the same absolute surface temperature could sustain a higher or lower albedo, and the albedo is, in effect, determined by the strength of the greenhouse effect, not the surface temperature. Is this correct?
Interesting to see how the various commenters are beginning to diverge.
Willis is right in his observations and he realises the practical implications but IMHO still needs to do a bit more thinking to see the mechanisms involved. He is currently ‘stuck’ on GHGs as being necessary for a convective cycle whereas they are not needed at all. They just help to ‘lubricate’ the convective cycle.
The usual ‘warmist’ proponents are making more and more picky points about irrelevant aspects and are avoiding the main issues.
Some, like rgb, are getting very close to envisioning the reality. He sees the effectiveness of the hydrological cycle as a system lubricant but has yet to realise that the convective cycle can do the job for a relatively non-radiative atmosphere even if the albedo changes can only be effected by wind kicking up dust from a dry surface.
The simplest description is that the sum of convection and radiation must leave the correct amount of thermal energy (KE) at the effective radiating height to match energy in with energy out. Otherwise no atmosphere.
If it does not, then convection moves energy around (KE to PE and back again) as necessary and the less radiative gases there are in an atmosphere the harder the convective cycle has to work to maintain equilibrium.
The convective cycle will alter albedo by whatever means are available even if that involves merely violent winds whipping up dust from the surface as seen on Mars.
Interesting times 🙂
Bulsit says:
January 8, 2014 at 12:15 pm
Dear heavens, the fog is thick out there today.
Yes, Bulsit, there is an emissivity for gases … but no, it’s not 0.002. For any particular gas, he emissivity depends on the frequency of the radiation, and varies from 0 to about 1. See the flux emissivity tables and discussion here.
And don’t try to impress us with your wisdom until you have some. Your claim is patent nonsense that any serious researcher would just laugh at.
w.
Willis Eschenbach says: January 8, 2014 at 2:06 pm
” what’s your point?”
The point is that what you have described as LW is not an independent measure of upwelling LW, according to CERES. It is obtained by subtracting measured SW from measured total upwelling. And since total upwelling is constrained to balance TSI (cons en), with temporary variations due to environmental heating/cooling and spatial fluctuations due to heat circulation, the variation of “LW” is mainly determined by SW, and so must correlate (negatively).
That’s nice. With the seasonal effects removed, I was surprised by the large size of the correlation.
Greg Goodman says:
January 8, 2014 at 12:17 pm
Greg, you came in the door and rather than saying something like “I didn’t bother reading your code, so I have a question about rounding”, which would be passable, you said my numbers were “not too accurate” and that I had engaged in “crude rounding” … both of which were nonsense and a complete fabrication on your part. I did neither one.
I’m just saying that if you don’t know something, ASK. You didn’t have a clue what the “roundto” variable did, but despite that you accused me of using “crude rounding” … and all the while, my legend numbers were accurate to 100 decimal places.
You should ask if you don’t understand, because falsely accusing me of putting out inaccurate numbers and using “crude rounding”, when NEITHER ACCUSATION CONTAINED A SHRED OF TRUTH, will not win you any bonus points.
Best regards,
w.
Nick Stokes: The point is that what you have described as LW is not an independent measure of upwelling LW, according to CERES. It is obtained by subtracting measured SW from measured total upwelling. And since total upwelling is constrained to balance TSI (cons en), with temporary variations due to environmental heating/cooling and spatial fluctuations due to heat circulation, the variation of “LW” is mainly determined by SW, and so must correlate (negatively).
Clearly that is an important issue that must be resolved. Willis, is Nick correct about how LW is measured?
Willis:
You’re on the right track in recognizing that increased LWIR absorption by the atmosphere need NOT necessarily lead to increased surface temperatures. The “homeostatic” regulating mechanism, however, is not likely an increase in planetary albedo, as you speculate in apparent contradiction of your own findings from CERES data. Far more fundamental is the reduction in the insolation available for thermalization near the surface. A dusty atmosphere reduces the power density by tens of W/m^2 and a cloudy one by hundreds, thereby cutting the core supply of solar energy to the surface. As I’ve been trying to get across in my comments on your series of recent posts, what happens high aloft in the planetary “energy budget” is not the critical factor. It’s the near-surface processes that matter most!
Nick Stokes says:
January 8, 2014 at 2:18 pm
Thanks, Nick. I thought I went over this. Yes, the LW is equal to SW + LW – SW.
And yes, 4 is equal to 7 + 4 – 7 … again, what is your point? Does that make 4 the wrong answer?
No, no, no, there is no constraint that either the gridcells or the total radiation balance at any instant that we might care to measure them. The calculation LW = Overall (LW+SW) – SW is done on the instantaneous measurements, not on global annual averages. Thus, there is no constraint.
The CERES data doesn’t measure total radiation. It only measures gridcell by gridcell radiation. And that data is not constrained in the slightest, as I pointed out.
If your claim were true, then the LW-SW correlation would be the same everywhere, because it would be constrained … but it isn’t that way at all. Instead, the gridcell correlation ranges from -0.97 to + 0.25, and the gridcell “balance” ranges from -200 to + 200 W/m2 … so please, give up the claim that the gridcells are “constrained to balance”.
Finally, month-by-month the net TOA data are also characterized by imbalance, not balance. In June the net is minus ~10 W/m2, and in January it’s about -10 W/m2.
So at no point in time are either the individual gridcells or the overall total constrained to balance.
w.
here is the graph rescaled to clarify the range -0.5 to -1 . This is not supposed to be better or replace fig 2 but give a more detailed look at part of it. A finer colour scale over the range +0.25 to -1 would be better.
http://i39.tinypic.com/2crqzhu.png
Now we need to know what sort of correlation coeffs can considered significant.
Each cell has 13 years of monthly data. but this has been ‘deseasonalised’ which is crude kind of 12m low-pass filter and effectively reduces the number of degrees of freedom by a factor of twelve, so we are back to 13 independent readings.
with N=13:
-1.0/N+2.0/sqrt(N) = 0.48
So anything out of the red can be considered with 95% confidence to show correlation that is non random. So that means that the four regions close to land that were comment on by myself and others, are showing no significant correlation. Willis’ dark blue contour is quite close to showing the limit of significant correlation.
Since Willis understands the arcane workings of R far better than I , perhaps he can clarify how the colour banding works. I’m guessing that anything blue here is between -0.9 and -1.0 , though it could be 0.75 to 0.85.
Hm, I don’t see want to be all negative, but do you have any explanation, or at least an idea/ hypothesis to what the cause of this increased reflection can be?
To me it seems like you have just shown the obvious fact that increased SW warms the surface which gives increased LW, and vice versa. Or am I missing something?
/Jan
Nick Stokes says:
January 8, 2014 at 1:56 pm
Nick, Phil claimed that clouds absorbed and scattered 100% of the light.
Phil. says:
January 8, 2014 at 10:42 am
Now, there is likely an idea somewhere kinda sorta near to what Phil said that is right.
But no, Nick, Phil’s idea is not “right” as you claim. It is called “wrong” when someone claims that clouds both absorb and scatter 100% of the light.
As to what idea similar to Phil’s might be right … what does that have to do with the topic of the thread, or with my comment on IR that Phil was ostensibly answering to … and why should I care?
w.
Matthew R Marler says:
January 8, 2014 at 2:27 pm
He is right about how Lw is measured, but that is meaningless. Whether it is measured directly or indirectly, so what?
He is wrong, however, about constraints. There is no constraint that there be a net TOA balance at any given instant at either the local or global level … and we are dealing with a string of instantaneous measurements.
w.
It seems that the red areas are being decorrelated by the influence of cooler waters being dragged in by the major ocean gyres , as I suggested earlier.
It may be worth checking this against a graph of mean SST but it seems there is a temperature limit below which this regulatory effect does not work. Since it’s all based on evaporation, clouds and storms that is probably consistent with Willis’ hypothesis.
If too much of the SST in a region is below that ‘trigger’ value, the feedback won’t happen.
Willis Eschenbach says: January 8, 2014 at 2:51 pm
“Yes, the LW is equal to SW + LW – SW. And yes, 4 is equal to 7 + 4 – 7 … again, what is your point? Does that make 4 the wrong answer?”
It makes it something you can’t usefully correlate with 7. “LW”=Tot-SW. Tot and SW are independently measured, with independent errors. You’re correlating “LW” with something (SW) that was used in the arithmetic from which it is derived.
If you correlate daily T_SFO with T_LAX, it will probably be positive. If it’s warm in SFO, it’s more likely than not to be warm in LAX. But if you correlate with T_LAX – T_SFO, that will likely be negative. T_LAX is partly correlated, but -T_SFO totally.
I’ve emphasised that TOT is subjected to a global energy constraint. But even if it weren’t, it’s the arithmetic link between “LW” and SW which makes correlation with SW unwise.
To me it seems like you have just shown the obvious fact that increased SW warms the surface which gives increased LW, and vice versa. Or am I missing something?
/Jan
In a word, yes. The correlation is _negative_ ie. increased SW produces LESS LW out , if you want to see the causation the way around. That means more the surface heats more it retains that heat. sounds like run-away warming tipping points to me.
However, if conditions which produce more LW out also produce a reduction in incoming SW, that causality would be a stabilising negative feedback.
So do we see run away warming in tropics when sun is overhead or do we see a fairly hard limit on max SST in tropics. Which interpretation fits the facts?
1sky1 says:
January 8, 2014 at 2:30 pm
Thanks, sky. It is true that something on the order of 80 W/m2 is absorbed by the atmosphere. It is also true that energy absorbed in the atmosphere cools the system compared to the same energy hitting the surface.
However, as my series of articles on volcanoes shows, the global temperature is remarkably insensitive to dust in the air. I hold that this is because as soon as the planet starts to cool, the tropical albedo drops, and thus more energy enters the system to restore the equilibrium.
We know that this is true from the correlation of albedo with temperature in the tropics, which is strongly positive—the warmer it gets, the higher the albedo gets from increased clouds, and vice-versa. So when the earth cools from e.g. airborne dust, we get less tropical clouds, and thus more sunlight to compensate for the loss.
So I fear to say, the “critical factor” as you call it is not the amount of sunlight intercepted by dust. The critical factor is that there is a thermoregulatory system in place which keeps the temperature from varying much, despite large variations in radiation due to things like the amount of atmospheric dust.
w.
Willis Eschenbach says: January 8, 2014 at 3:01 pm
“Nick, Phil claimed that clouds absorbed and scattered 100% of the light.”
No, he said:
“Each droplet in the cloud will absorb ~100% of the incident light and also scatter an equal amount of the incident light.”
and that’s true in the van de Hulst formula, large radius limit (not large wavelength, as I wrongly said).
As to why you should care, I don’t know. Greg cares. I’m just noting what the formula says.
Nick , in what way is SW + LW – SW correlated to SW ?
” I’m just noting what the formula says.”
the formula says 50%=50% not 100%+100% . What Phil said was confused and wrong. If he had said 50% absorbed and as much scattered, no one would have commented. It would have been correct but irrelevant.
I tried to point out his error in a light-hearted way but he didn’t get it. Too subtle I suppose. Can we drop that now?
Nick , in what way is SW + LW – SW necessarily correlated to SW ?
Jan Kjetil Andersen says:
January 8, 2014 at 2:56 pm
Jan, the SW in question is upwelling SW reflected from the clouds.
HTH,
w.
Alec Rawls: “But there is also a simpler explanation for this anti-correlation. Where clouds block incoming solar the planet below warms less, leading to less outgoing LW. ”
Same error as Jan it seems. Positive correlation.
I wish someone would address Tim Groves’ comment of 1/7/14 11:41pm. I too see it as just logic that CO2 would block incoming LW just exactly as it blocks “upwelling” LW. Please advise?
Willis:
You say: “So I fear to say, the “critical factor” as you call it is not the amount of sunlight intercepted by dust.”
I cited insolation-reducing dust only as an example of a factor aloft. Although it does reduce daytime surface temperatures when encountered, nowhere did I refer to it as a CRITICAL factor on any climatic time-scale.
We have three measured quantities, energy incident on the earth from the sun (downwelling solar= constant= 340 w/m2) , visible wavelength energy reflected (upwelling solar ), and upwelling LWIR. Since for equilibrium, downwelling solar= upwelling solar + upwelling LWIR, and since downwelling solar is constant, the upwelling components must be negatively correlated; that is when one goes up the other must go down. Not surprising that the data show this.
However, this says nothing about the average surface temperature of the earth or global warming. The greenhouse effect is real—- have you not noticed the temperature of your car when you leave the windows up on a sunny day. I believe, however, the greenhouse effect of increasing CO2 in the atmosphere is insignificant — generally agreed to be only about 1 deg K with a doubling of CO2.
Greg Goodman says: January 8, 2014 at 3:31 pm
“Nick , in what way is SW + LW – SW correlated to SW ?”
By arithmetic. If LW=measured Tot – measured SW, and you correlate LW with SW, you’re measuring how changes in SW match changes in LW. But if SW rises by 1 unit, for whatever reason, , that guarantees a drop component of 1 unit in LW, to which is added a statistical change in Tot. That guaranteed component (via -SW) weighs heavily and artificially in the correlation.
I’ve emphasised that TOT is subjected to a global energy constraint. But even if it weren’t, it’s the arithmetic link between “LW” and SW which makes correlation with SW unwise.
No interest in playing referee here, but I don’t quite understand this. Suppose we measure an aggregate quantity. Total income of humans in various geographic cells. We also measure the total income of women in those same geographic cells in a separate measurement (we can imagine both are measured to reasonable precision by independent sampling). We can then infer the total income of men by subtracting the total income of women from the total income. This measurement/inference is, no doubt, less precise than either the measurement of total income or the measurement of the income of women, but I see no justification for an assertion that the correlation between women’s income and men’s income will be negative as an artifact of the measuring process. Especially when it is not, in fact, uniformly negative on the sample space.
So you’ll have to explain this. Lower precision, sure. But since the total energy per cell is not constrained to any particular value, I’m not sure that I agree with your assertion that there is a necessary, or even probable, anticorrelation.
Non-climate example, please?
rgb
Another excellent article. Thanks Willis! 🙂
Willis’ hypothesis and that also of Bill Illis and others of negative thermal feedback by cloud SW albedo is strongly supported by the negative correlation nicely shown by CERES exactly where it would be expected, i.e. the equatorial oceans.
There are a couple of factors that make me feel that there may be additional LW negative feedback:
1. One classic aspect of AGW theory is that CO2 cools the stratosphere decreasing the LW emission height. But a decreased emission height must also mean an emission height with a higher density of air molecules meaning, in turn, increased LW emission.
2. Turbulence and surface area – this is an argument from geometry. It has been stated upthread that both radiative and convective heat transfer in the atmosphere depend on temperature gradient. They must equally depend on the surface area over which this temperature gradient exists. What is this surface area? Is it just assumed to be 4 pi r sqrd at the emission height? This would be wrong if the surface with gradient (boundary between warm and cold) is complex – folded and crinkly – rather than smooth.
Two things will increase the surface area of the emission surface: (1) increased heat input to the atmosphere from CO2 IR will increase turbulence, increasing the emission surface area; (2) decreasing the emission height to a lower altitude that will also be more turbulent, will also increase the emission surface area.
Thus there may be LW as well as SW negative feedback in response to CO2 atmospheric warming.
Wikipedia:
“…The total amount of energy received at ground level from the sun at the zenith is 1004 watts per square meter, which is composed of 527 watts of infrared radiation, 445 watts of visible light, and 32 watts of ultraviolet radiation. At the top of the atmosphere sunlight is about 30% more intense, with more than three times the fraction of ultraviolet (UV), with most of the extra UV consisting of biologically-damaging shortwave ultraviolet.[3][4][5]…”
You state:
“…the incoming radiation, 340 watts per metre squared (W/m2)…”
Can you explain to an ignorant where the difference comes from?
Greg Goodman says:
January 8, 2014 at 1:17 pm
Phil says: “Each droplet in the cloud will absorb ~100% of the incident light and also scatter an equal amount of the incident light.”
I don’t know what you though you were saying but that is patent nonsense, you can not both absorb and scatter 100% of anything.
Actually you do, it is the Fraunhofer limit of particle size large wrt the wavelength scattering is equal to absorption and the extinction coefficient is equal to 2.0. You should have read the material I referred you to.
Neither have you understood the pdf that you refer me to.
I certainly did I’ve written something similar about 20 times in publications on the subject!
It’s not difficult when it opens with:
“For particles much larger than the wavelength of the incident light, the scattering efficiency approaches 2. That is, a large particle removes from the beam twice the amount of light intercepted by its geometric cross-sectional area. What is the explanation for this paradox?”
One thing I have done in the past is worked on numerical modelling of scattering of E-M radiation by atmospheric aerosols, rain, hail, sleet and slightly melted hail with a liquid surface….. heavy rain light rain, mixed rain with various models of raindrop size distribution, etc, etc. Our results were within 10% of empirically measured results.
But you don’t need professional experience to realise you can’t have your cake and scatter it.
Apparently you do and I guess mine trumps yours.
Robert Clemenzi says:
January 8, 2014 at 1:22 pm
Phil. says:
January 8, 2014 at 7:54 am
“Not correct because the emission by the CO2 is not immediate and is orders of magnitude slower than loss of energy by collisions to surrounding molecules when in the lower troposphere. In that region of the atmosphere CO2 always absorbs more than it emits.”
Whether or not the emission is immediate is not relevant. Over land, it is fairly common for the atmosphere to be warmer than the surface. As a result, when there is a temperature inversion, CO2 emits more IR radiation than it absorbs.
It’s very relevant because the energy absorbed by the CO2 molecule remains in an excited state for long enough for it to be deactivated collisionally and that is the primary mode of energy transfer from the excited molecule in the lower atmosphere. CO2 does not emit more IR radiation than it absorbs.
michael hammer says:
January 8, 2014 at 1:26 pm
—————————————
Michael,
in your 2013 analysis of OLR at Jennifer Marohasy’s site you concluded –
“The last 30 years of NOAA data is not compatible with the theory
of AGW. It would appear that either 30 years of NOAA data is wrong or the theory of AGW
is very severely flawed.”
I would point out that while inconsistent with AGW pseudo science, your analysis is entirely consistent with my claim that adding radiative gases to the atmosphere will not reduce the atmospheres radiative cooling ability and that the net effect of radiative gases in our atmosphere is radiative cooling at all concentrations above 0.0ppm.
1. The net effect of the atmosphere on the oceans is cooling.
2. The only effective cooling mechanism for the atmosphere is LWIR to space from radiative gases.
It really is that simple. AGW is a physical impossibility.
Willis Eschenbach says:
January 8, 2014 at 3:01 pm
Nick Stokes says:
January 8, 2014 at 1:56 pm
Willis Eschenbach says: January 8, 2014 at 10:35 am
“Huh? Typo on your part? You can’t both scatter and absorb 100%.”
Not perfectly expressed, but the idea is right.
Nick, Phil claimed that clouds absorbed and scattered 100% of the light.
No Willis, I said that the droplets in the cloud scattered an equal amount of light to that absorbed, this is a fact. Intuition by the lay man doesn’t always get the right answer, particularly when quantum effects are involved. In fact while Q=2 is true for particles large wrt the wavelength for particles approximately equal to the wavelength it can be as high as 4. The light that is passing close to the drop has no waves downstream to interact with (because of absorption) and is scattered as a result.
Nick seems to be assuming that Total radiation is constant, in which case the correlation of SW with LW would be exactly -1 everywhere and always.
It’s not, because it’s not.
Phil. says:
January 8, 2014 at 5:39 pm
“CO2 does not emit more IR radiation than it absorbs.”
———————————-
Perhaps you might reconsider that claim.
The atmosphere is heated by –
-directly intercepted solar radiation
-intercepted outgoing LWIR from the surface
-surface conduction
-release of latent heat
However there is only one effective cooling mechanism for the atmosphere –
-LWIR to space from radiative gases
From the mid to upper troposphere radiative gases are emitting TWICE the energy to space than both the net flux of IR into the atmosphere and intercepted solar radiation combined.
CO2 is not just emitting to space energy it acquires by intercepting radiation, but also energy it acquires conductively.
Konrad:
You’re taking a simple argument regarding radiative gases a bridge too far. ALL matter above zero Kelvin emits some radiation in the EM spectrum. This includes the nominally “inert” components of air: nitrogen, argon and oxygen. These bulk components are heated from below by conduction and convective eddy diffusion, as well as by molecular collisions with LWIR absorbent components. Adding radiative trace gases or–far more importantly–water vapor to the atmosphere does retard the radiative cooling of the surface by the corresponding back-radiated amount. It is the interplay of all these factors, along with cloud formation and dissipation, that makes the problem far more complex than you allow.
timetochooseagain says: January 8, 2014 at 5:59 pm
“Nick seems to be assuming that Total radiation is constant, in which case the correlation of SW with LW would be exactly -1 everywhere and always.”
That’s the extreme. But short of that, the fact that LW has an arithmetical component of SW is a strong push toward negative correlation. See next.
rgbatduke says: January 8, 2014 at 4:55 pm
“I’m not sure that I agree with your assertion that there is a necessary, or even probable, anticorrelation.
Non-climate example, please?”
Two coins, A and B. Score 1 for heads, 0 for tails. After many simultaneous tosses, you find near zero correlation.
Now correlate A with C=B-A. Correlation coef about -1/sqrt(2). But nothing is physically correlated. It’s just the arithmetic.
@Nick Stokes-
If:
T = S + L
then making a linear model for S based on L if T is constant results, of course, in;
L = -1*S + C where C is a constant
Therefore deviations of the coefficient from -1 are indications that T is not constant.
But it appears to me that Willis’s hypothesis is equivalent to the idea that T should be approximately constant. If T was *so* inconstant as to make the correlation between S and L near zero, this would probably be evidence against Willis’s hypothesis. To the extent that the correlation deviates little from -1 it would tentatively constitute support for Willis’s hypothesis.
If the correlation had been -1 everywhere and always that would have been definitive proof of his hypothesis.
1sky1 says:
January 8, 2014 at 6:46 pm
—————————————————-
I would agree with much of what you have written.
“ALL matter above zero Kelvin emits some radiation in the EM spectrum. This includes the nominally “inert” components of air: nitrogen, argon and oxygen.”
Correct, and more important than most realise. If you remove strongly radiative gases from the atmosphere, air masses at altitude could no longer lose energy, buoyancy and subside. Full convective circulation in the Hadley Ferrel and Polar cell would then stall. The poorly radiative gases stagnated at altitude would then be subject to radiative superheating, just as in the thermosphere.
“These bulk components are heated from below by conduction and convective eddy diffusion, as well as by molecular collisions with LWIR absorbent components.”
You should also add that radiative gases are also absorbing energy by conductive contact with other gases that they then radiate to space .
“Adding radiative trace gases or–far more importantly–water vapour to the atmosphere does retard the radiative cooling of the surface by the corresponding back-radiated amount.”
Only 29% correct. Downwelling LWIR has no real effect over the oceans. Incident LWIR can neither heat nor slow the cooling rate of water that is free to evaporatively cool.
“It is the interplay of all these factors, along with cloud formation and dissipation, that makes the problem far more complex than you allow.”
The problem is far simpler than you would ever believe 😉
Climate pseudo scientists calculated the black body surface Tav for an earth without an atmosphere as -18C then claimed a radiative greenhouse effect would raise this to the observed 15C surface Tav. But the ocean is a fluid body in a gravity field, and SB equations alone cannot derive its temperature profile.
Without an atmosphere our oceans would boil into the vacuum of space. However imagine a force field retaining them in the absence of an atmosphere. Now the ocean can be heated at depth by SW and only cool by outgoing LWIR from the surface. A desert may have a Tav of -18C without an atmosphere, but would this hold true for the oceans? Would they freeze over as climate scientists claim? If you have some “dark money” or a spare “big oil cheque” you can build an experiment to check this claim.
http://i42.tinypic.com/315nbdl.jpg
This experiment prevents evaporative cooling and almost prevents conductive cooling of a water sample heated below the surface by an intermittent high power SW source. LWIR back radiating onto the surface is virtually eliminated.
1sky1,
With a starting temperature of 15C, will the water sample freeze or will it reach around 80C?
If the sample heats to near 80C then AGW is a physical impossibility. The net effect of the atmosphere would then be surface cooling and the only effective cooling mechanism for the atmosphere is radiative gases.
What do you think the water sample will do?
Willis Eschenbach says:
January 8, 2014 at 2:51 pm
The CERES data doesn’t measure total radiation. It only measures gridcell by gridcell radiation. And that data is not constrained in the slightest, as I pointed out.
According to CERES that’s exactly what they do!
“Each CERES instrument measures filtered radiances in the shortwave (SW; wavelengths between 0.3 and 5 μm), total (TOT; wavelengths between 0.3 and 200 μm), and window (WN; wavelengths between 8 and 12 μm) regions. To correct for the imperfect spectral response of the instrument, the filtered radiances are converted to unfiltered reflected solar, unfiltered emitted terrestrial longwave (LW) and window (WN) radiances (Loeb et al. 2001). Since there is no LW channel on CERES, LW daytime radiances are determined from the difference between the TOT and SW channel radiances.”
The calculation is as Nick pointed out as you can see above.
http://ceres.larc.nasa.gov/documents/cmip5-data/Tech-Note_CERES-EBAF-Surface_L3B_Ed2-7.pdf
Konrad 7:48pm: “Climate pseudo scientists calculated the black body surface Tav for an earth without an atmosphere as -18C.”
Not without an atm.; simply theoretically reduced existing atm. global emissivity from ~0.79 to near 0, water and solid surface emissivity & net solar held steady.
Trick says:
January 8, 2014 at 8:33 pm
————————————–
Trick,
please have a look at the experiment linked give me your clear and direct answer –
http://i42.tinypic.com/315nbdl.jpg
With a starting temperature of 15C –
A. will the water sample freeze?
B. will it reach around 80C?
Can you even answer A or B?
Will it be the usual round of nit picking hand-waving and bafflegab?
Do I need an ISO certified kitchen with brushed stainless German tap-ware to run this one?
You can’t answer because I haven’t properly defined the unicorn/rainbow ratio?
What will be you glorious excuse for being unable/unwilling to answer this time…
“Scientists may be wrong, and often are. But when you think you’ve uncovered a “major error”, something really obvious, well, you should check your facts very carefully before uncapping your electronic pen ”
The irony burns.
Nick Stokes says:
January 8, 2014 at 7:06 pm
I see the problem. You’ve assumed that the measurement creates the reality. In your example, you are assuming that the underlying physical relationship is that the independent variables are variable A, AND THE TOTAL B, with the other variable C=B-A dependent on the other two.
But in the real world, it works the other way around. In the real world if A is one independent variable and C is the other independent variable (as in your example), then the causation runs the other direction. C is not defined as B-A, it has independent physical identity as does the variable A. As a result, rather than C = B-A being the governing equation, the physical reality is that the total B = A + C. In other words, the physical reality is that the total is the sum of the parts.
As a result, the relationship between A and B is not changed by the way it is measured. If the two underlying physical phenomena were 100% correlated before the measurement, they will be 100% correlated after the measurement.
And if they were totally uncorrelated before we started they will be uncorrelated thereafter.
As an example, suppose two people step on a scale together. They weigh 280 pounds. Then we weigh one person and they weigh 160 pounds. From this, we conclude that the other one weighs 120 pounds.
If we do this a thousand times, will we find that the weights of the two people are correlated with a value of -1/sqrt(2)?
Absolutely not. If the peoples weights were correlated before weighing them, they will be correlated after we do the C=B-A calculation to figure both weights.
And if they were not correlated before weighing they won’t be correlated after the measurement.
The key issue is that the total is the mathematical sum of two physical measurements, which may or may not be correlated. The fact that if we know one variable and we know the total we can calculate the value of the other variable does NOT mean that that the two variables are therefore correlated.
w.
Greg Goodman says:
January 8, 2014 at 3:36 pm
” I’m just noting what the formula says.”
the formula says 50%=50% not 100%+100% . What Phil said was confused and wrong. If he had said 50% absorbed and as much scattered, no one would have commented. It would have been correct but irrelevant.
I tried to point out his error in a light-hearted way but he didn’t get it. Too subtle I suppose. Can we drop that now?
No because you’re wrong, in the case referred to above to which I replied, for an absorbent drop all the incident light on the drop is absorbed, additionally an equal amount of light is scattered resulting in twice the incident light being removed from the beam. This is correctly stated in the reference I cited:
“For particles much larger than the wavelength of the incident light, the scattering efficiency approaches 2. That is, a large particle removes from the beam twice the amount of light intercepted by its geometric cross-sectional area. What is the explanation for this paradox?”
The error is yours, do yourself a favor and actually read the material I cited.
As I pointed out in my reply to Willis under conditions of anomalous diffraction the number can be as high as 4 times the incident light.
Konrad 8:44pm: “What will be you glorious excuse for being unable/unwilling to answer this time…”
Not glorious. Just the ordinary CERES observations of LWIR data posted and discussed by Willis show your small experiments don’t resolve for the earth system at large. In the past, I’ve responded with links to papers and texts showing you the physical reasons.
1sky1 says:
January 8, 2014 at 4:17 pm
Sky, sorry if I misunderstood you. You said:
Since you gave airborne dust as an example of just such a “critical factor”, I was merely saying that no, airborne dust was not in any way critical. As the volcanoes have demonstrated, airborne dust does little to the global temperature.
w.
Konrad says:
January 8, 2014 at 6:02 pm
Phil. says:
January 8, 2014 at 5:39 pm
“CO2 does not emit more IR radiation than it absorbs.”
———————————-
Perhaps you might reconsider that claim.
Certainly not, though you perhaps should consider reading the context in which it was made.
Trick says:
January 8, 2014 at 8:56 pm
“Not glorious. Just the ordinary CERES observations of LWIR data posted and discussed by Willis show your small experiments don’t resolve for the earth system at large. In the past, I’ve responded with links to papers and texts showing you the physical reasons.”
———————————————————————————
You were right about that, not glorious at all. Rather pathetic really.
You were asked a specific question about a specific experiment and you come up with some waffle about “the earth system at large”.
Again I ask if you can give a clear and direct answer to the question. A or B. Will the water in the experiment either –
A. freeze
or
B. rise toward 80C?
Perhaps another reader can help Trick out?
janus says:
January 8, 2014 at 5:31 pm
While there are ignorant people, the only ignorant questions are the ones you don’t ask, they are the questions that keep people ignorant.
First, as to the difference, my value is the top-of-atmosphere (TOA) measurement averaged over the surface of the earth. The earth absorbs radiation based on its cross-section. However, the surface area is four times the cross-sectional area, so the total amount needs to be divided by four to give a global 24/7 average.
At the TOA, the “solar constant” is about 1360 W/m2. But since the surface area is four times the area intercepting the 1360 W/m2, the global average is a quarter of that, 340 W/m2.
As to the Wiki quote, they are not looking at a global 24/7 average value as I was. The are looking at a tropical noon-time instantaneous value. As they point out, that’s about a kilowatt per square metre.
However, things are nowhere near as accurate as Wiki claims. The proportions of UV/Near IR/Visible Light are about right, but the amount of energy received at ground level varies greatly with the transmissivity of the atmosphere. Something on the order of 80 W/m2 are absorbed in the atmosphere on a global 24/7 average, but in the tropics, because the downwelling amount is greater and it is an instantaneous measurement, the absorption is greater. As a result, it’s unusual to see noontime values over a kilowatt, although they definitely do occur. My point is, it’s not “1005 W/m2” as the wiki says.
w.
Phil. says:
January 8, 2014 at 5:39 pm
The GHGs definitely emit more IR radiation than they absorb. This is because the atmosphere is warmed by four different sources—absorbed light (~80 W/m2), sensible heat from the surface (~80W/m2), latent heat from the surface (~100 W/m2), and radiation from the surface (~350 W/m2).
This is a total of 610 W/m2 being absorbed by the atmosphere (global 24/7 averages), of which 350 W/m2 comes from radiation absorbed by the GHG (mostly water vapor and CO2).
Of course, since the gaining 610 W/m2 constantly, the atmosphere has to also lose 610 W/m2 constantly
But all of that energy is lost from the atmosphere by radiation. And all of the radiation is coming from GHGs.
As a result, we can say that atmospheric GHGs including CO2 most assuredly are radiating more energy than they are absorbing, in the ratio of 610 / 350.
w.
Phil. says:
January 8, 2014 at 9:04 pm
————————————–
I see that Willis has added a little more “context” 😉
Phil. says:
January 8, 2014 at 5:33 pm
Ah, I finally see the problem. The meaning of “incident” was unclear. To everyone out here, the “incident light” is all of the light that is affected by the object in question, and “non-incident light” is the light that is unaffected by the object.
To you, “incident light” is the NOT the amount of light intercepted by the actual phenomenon. Instead, it is just a number, it’s the light intensity times the cross-sectional area of the particle. As such, to you the incident light does NOT include all of the light affected by the phenomenon. In your terminology, some “non-incident light” is also affected.
It’s a problem with specialists, they forget that the words that have special meaning within a discipline do not have the same meaning to the general public.
Because to us, if light is getting either scattered or absorbed by a particle, then perforce it is “incident light”, and the light that is not scattered is not incident light.
But to you, the light being scattered by a particle is NOT incident light.
As a result, when you say that a particle can absorb 100% of the incident light and also reflect 100% of the incident light, folks like myself say “huh”?
Since you are the specialist, this misunderstanding is on you. When you use a term in some non-standard way, you owe it to your readers to point that out … because there’s no way that your readership can be expected to understand your non-normal use of the term.
Thanks for persevering, I finally got the answer to my “huh”?
w.
Willis Eschenbach says: January 8, 2014 at 8:47 pm
“I see the problem. You’ve assumed that the measurement creates the reality. In your example, you are assuming that the underlying physical relationship is that the independent variables are variable A, AND THE TOTAL B, with the other variable C=B-A dependent on the other two.”
Correlation works on the numbers as measured. That’s A and B, or SW and Tot. The point of the coin example is that you get a negative correlation with B-A which does not tell you about the reality of anything. The coins have no correlation.
Just the same arithmetic is done with SW and Tot. If the coins with no correlation gave a neg correlation for the difference, you can’t infer any useful relation between SW and “LW” from exhiibiting the same behaviour. You don’t know a priori about any underlying reality – you’re trying to infer it from the correlation. Measurement is all you have.
People keep making the claim that if on average the anomalies of LW and SW sum to zero, that A and B must perforce be negatively correlated. Nick even put forth a flawed attempt at a proof. However, it’s not true.
Consider the result of the following series of paired observations, which are randomly generated pseudo-anomalies of LW and SW.
LW, SW
-2.9, -2.2
-14.2, -13.0
5.3, 7.2
0.5, 0.4
2.9, 1.8
2.6, 1.5
-2.4, -3.0
2.7, 2.7
2.4, 2.2
3.1, 2.3
Here’s the oddity. They sum to zero … but their correlation is 0.98. Why? Because basically they move together, but their overall mean is zero.
In other words, even if the sum of two anomalies is physically constrained to be zero over a sufficiently long period of time, there is no special requirement that the two anomalies be negatively correlated.
The data was generated by the following R code:
# generate ten random numbers
LW = rnorm(10, sd=4)
# generate ten more random #s, with the mean of each random number generation
# equal to the corresponding value of LW
SW = rnorm(10, mean=a)
In other words, all I did was require that SW anomalies be correlated to LW anomalies, and as long as the mean of the LW anomalies is zero, the mean of the sum will be zero.
But wait, as they say on TV, there’s more. Here’s another example:
# generate 100,000 random normal pseudo-longwave
# radiation observations, mean 240, standard deviation = 42
# mean and sd values from CERES LW data
LW = rnorm(100000, mean=240, sd=42)
# 100,000 random pseudo-shortwave radiation observations, mean 100, std. dev. = 72
# mean and sd values from CERES SW data
SW = rnorm(100000, mean=100, sd=72)
mean(LW+SW)
# 339.998
cor(LW,SW)
# -0.0014
You see what I’m getting at? The fact that in the long run the longwave (avg. 240 W/m2) and shortwave (avg, 100 W/m2) are constrained to sum to the solar value (avg. 340 W/m2) does NOT mean that they have to be negatively correlated. They can be positively, negatively, or un-correlated and still sum to the solar value.
w.
@Willis Eschenbach at 8:47 pm reply to Nick Stokes
You’ve assumed that the measurement creates the reality.
It is possible you and Nick are both correct.
CERES data from the TERRA, AQUA, AURA satellites may record the individual components of the flux and the correlations are real and not mathematical artifacts.
But again, let’s remember the provenance of the CERES dataSET. It is mostly GOES-MODIS data that is calibrated (SOMEHOW!!) into a CERES look-alike data format. It is also “Adjusted”
To me it is an open question whether the GOES data recalibration into CERES-like data might create a non-zero, and likely negative correlation coefficient. If the correlation is not generated from the GOES conversion, it might still result from the adjustments they made to close the 5 W/m2 gap in the total.
So, Willis your B = A + C example may be correct if the CERES dataset was pure CERES collected data. But it isn’t. CERES instruments are in solar synchronous orbits, in just two orbital planes. CERES instruments cover no more than 4 out of the 24 hours of the day. The rest of the dataset comes from GOES+mathematical magic.
Nick Stokes may have a point given how much of the CERES dataset comes from some fuzzy GOES recalibration process and fuzzier adjustments to partially close a gap.
Nick Stokes says:
January 8, 2014 at 10:20 pm
Thanks, Nick. You are confusing the reality with the measurements. Let me try it again with your coin example.
I’m flipping two coins. I dub one of them LW and the other SW. I flip both of them at once, and in my notebook I write down a pair of values plus their total. I get something like this:
LW, SW, TOT 1, 0, 1 0, 1, 1 0, 0, 0 1, 1, 2 0, 1, 1 1, 0, 1 1, 1, 2 0, 1, 1 1, 1, 2 0, 0, 0Now, I send the notebook page to you … but unfortunately, it gets caught in a letter-sorting machine and torn in half, and all that you receive is the following:
SW TOT 0, 1 1, 1 0, 0 1, 2 1, 1 0, 1 1, 2 1, 1 1, 2 0, 0You, being Nick Stokes, are not so easily deterred. You know that you can reconstruct the value of the LW observation from the total and the SW observation. So in each case you calculate the value of the LW as the Total minus the value of the SW coin.
Now … does the fact that you are calculating the value of LW as (Total minus SW) imply that the values are negatively correlated?
I say no. I say that the reality is not affected by how you calculate it. If LW and SW are correlated in reality, then the calculation of LW will reflect that. The reality is not driven by the calculation method.
Having read your posts for some years now, however, I strongly suspect that even this clear exposition plus the computer code above plus the post from Dr. Robert Brown from Duke (rgbatduke) will fail to convince you. After all, they don’t call you “Racehorse Stokes” for nothing—as far as I know no one has ever actually witnessed you admitting that you were in error … but that doesn’t matter, I’m writing for the lurkers.
w.
Willis,
“there is no special requirement that the two anomalies be negatively correlated.”
Indeed. The formula for correlation of A with B-A is
ρ=(σ_B ρ_AB-σ_A)/sqrt(σ_A^2+σ_B^2)
ρ corr coef, σ sd
So yes, you can get positive correlation with large positive ρ_AB (and negative with negative). But you’re reasoning the other way around. The two quantities don’t have to be negatively correlated. But they can be without it meaning what you want it to mean.
Mosher writes “The irony burns.” in response to Willis’
“Scientists may be wrong, and often are. But when you think you’ve uncovered a “major error”, something really obvious, well, you should check your facts very carefully before uncapping your electronic pen ”
Well I think its a major error to be relying so heavily on GCMs for “science”
Things that make you go hummmm include the following extract from CMIP3 model constant section.
http://map.nasa.gov/ModelE_html/html_code/src/CONST.f.html#CONSTANT
!@param lhe latent heat of evap at 0 C (2.5008d6 J/kg)
real*8,parameter :: lhe = 2.5d6
!@param lhm latent heat of melt at 0 C (334590 J/kg)
real*8,parameter :: lhm = 3.34d5
The Cloud module is FULL of unreferenced constants. Soon, I’ll be able to definitively say its a fit and document it but for now I’ll simply marvel at the sloppiness of the implementation.
Will that count as an “uncovering” ?
Stephen Rasey says:
January 8, 2014 at 10:45 pm
Not sure where you got that idea. Actually, the CERES instruments are flying on four different satellites, Aqua, Terra, TRMM, and Suomi NPP. Three of these have polar sun-synchronous orbits, with different equator-crossing times. They are at 750 km altitude and scan limb-to-limb. The fourth one, TRMM, flies at 350 km altitude at a 35° inclination to the poles.
Next, since they image limb-to-limb, that means that the three polar satellites are each sampling a swath ≈ 6,000 km across. And as you pointed out, they are sun-synchronous, one orbit per day. This means that each one of the three satellites images about half of the planet every day.
In other words, most of the input to CERES is from the four CERES satellites, and there is terabytes of it..
As to your question about how the MODIS and GOES satellite data is integrated in the data processing, there’s a good overview here.
w.
Jan made the same point I did:
Willis answers:
Greg Goodman offers a similar reply:
I think Willis and Greg need to look at this again. The more SW is reflected back into space by clouds the less reaches and warms the planet’s surface, reducing the amount of upwelling LW. Thus clouds should be expected to CAUSE the negative correlation between upwelling and SW and upwelling LW that Willis has found. (In other words, Jan and I have this right: we are talking about upwelling SW and we are talking about its negative correlation with upwelling LW, as documented by willis.)
Cloudiness could also be an effect of increased GHGs (Willis’ thermostat hypothesis). The extra heat trapping (lower upwelling LW) causes increased evaporation and increased cloudiness that reflects more SW back into space. This direction of causality also produces anti-correlation between upwelling SW and LW. My initial suggestion was that the causality in the first direction (where clouds are a cause rather than an effect) probably dominates, obscuring what causality may be going on in the other direction. As I said before:
Steven Mosher says:
January 8, 2014 at 8:45 pm
Unlike most folks, I have actually uncovered major errors by other scientists. Take the claim of the cancellation of LW and SW in the tropics as one example.
And yes, I’m damn careful when I think I’ve found something like that.
However, unlike you, I actually do make mistakes.
Not only that, unlike you and most scientists, I work in total isolation, with no co-workers or associates or graduate students or anything. As a result, the errors that slip by me don’t get caught privately by discussing it with someone. They get caught publicly, and it’s damn embarrassing to me when they do.
But it’s rarely because I didn’t check my facts.
So yes, Steven, I’ve made some very public errors. That’s how science works. People put their work out in public, and other people try to falsify it. And sometimes they do. And when they do falsify my work, unlike many folks, I admit it freely, and science moves on.
Now, it seems that you want to be a total jerkwagon about that process, and accuse me in one of your ugly one-line drive-by shootings of not checking my facts … bullshit. I put hours and hours into checking my facts, and then I re-check them … and I still make mistakes. So what? Does that mean I shouldn’t advise others to check their facts?
Yes, I make mistakes, unlike you, I assume from your snide comment … you know, Steven, many times on the web I’ve gone out of my way to support you and defend you when you’ve been attacked by others.
But in this case? You’ve gone out of your way to be nasty, spewing pure childish spite, and that’s not doing your reputation a damn bit of good.
w.
Willis: He is right about how Lw is measured, but that is meaningless. Whether it is measured directly or indirectly, so what?
The problem is not that it is “indirect”, but that is it the difference between one measurement and another: a – b = c. The difference will be correlated with the terms of which it is made: a is positively correlated with c, and b is negatively correlated with c. The constraint of which Nick Stokes wrote is non-constant because a and b are random variables.
Willis Eschenbach says:
January 8, 2014 at 10:55 pm
“…After all, they don’t call you “Racehorse Stokes” for nothing..”
———————————————————————————–
Fast, but not fast enough.
Makarieva et al 2010 discussion paper….
“The Moving Finger writes; and, having writ,
Moves on: nor all thy Piety nor Wit,
Shall lure it back to cancel half a Line,
Nor all thy Tears wash out a Word of it”
There is no escape from the Following Dark.
Willis: Nick Stokes wrote: Willis,
“there is no special requirement that the two anomalies be negatively correlated.”
Indeed. The formula for correlation of A with B-A is
ρ=(σ_B ρ_AB-σ_A)/sqrt(σ_A^2+σ_B^2)
ρ corr coef, σ sd
So yes, you can get positive correlation with large positive ρ_AB (and negative with negative). But you’re reasoning the other way around. The two quantities don’t have to be negatively correlated. But they can be without it meaning what you want it to mean.
That is something that I think you need to study. Nick has identified what might be called “a rookie mistake”, though you are more than a “rookie”, and it is a mistake that I missed by being less familiar with the measurements. It is not necessarily the case that your conclusion is wrong, but it is unjustified unless you can get truly independent measures of what I have called a, b, and c. As long as one is measured as the difference of the other two, you will obtain correlations that have not any firm theoretical significance.
Willis Eschenbach says:
January 8, 2014 at 9:14 pm
janus says:
January 8, 2014 at 5:31 pm
However, things are nowhere near as accurate as Wiki claims. The proportions of UV/Near IR/Visible Light are about right, but the amount of energy received at ground level varies greatly with the transmissivity of the atmosphere.
========
In the proportions given by wiki it does not say that it is shortwave infrared making up the whole infrared amount…
The AGW meme actually claims it is mostly visible light and insignificant amounts of infrared (around 1%), so the wiki quote contradicts that too.
Here: http://earthguide.ucsd.edu/virtualmuseum/climatechange1/02_3.shtml
“The incoming energy from the Sun to Earth is mainly visible sunlight, called the �visible portion of the spectrum of electromagnetic radiation.� We perceive visible sunlight as colors from violet (short-wave radiation) to red (long-wave radiation). … A relatively minor amount of energy leaves the sun as radiation with shorter wavelength (�ultraviolet�) and as radiation with longer wavelength (�infrared� or �heat radiation�).”
The AGW claim is that we do not get heat radiation, longwave infrared, from the Sun.
The wiki quote says over half as measured at the surface is infrared.
So which is it?
http://hyperphysics.phy-astr.gsu.edu/hbase/thermo/grnhse.html
“The greenhouse effect refers to circumstances where the short wavelengths of visible light from the sun pass through a transparent medium and are absorbed, but the longer wavelengths of the infrared re-radiation from the heated objects are unable to pass through that medium.”
The second reason AGW gives of no longwave infrared heat from the Sun reaching us.
Willis, we cannot feel shortwaves from the Sun, that is simply a physical fact. Shortwaves are incapable of raising the temperature of matter, it takes the bigger heat energy of longwave infrared to move molecules of matter into vibration, which is kinetic energy, heat. Heat heats matter.
We cannot feel visible light as heat, because it cannot heat us up. Visible light, shortwaves, affect matter on the electronic transitional level, not the vibrational level of heat.
Your comparisons do not make sense because you are using AGW ‘physics’, now ubiquitous throughout the general education system because the traditional teaching has been systematically removed to promote AGW.
This is traditional teaching now removed from direct NASA pages: http://science.hq.nasa.gov/kids/imagers/ems/infrared.html
“Far infrared waves are thermal. In other words, we experience this type of infrared radiation every day in the form of heat! The heat that we feel from sunlight, a fire, a radiator or a warm sidewalk is infrared. The temperature-sensitive nerve endings in our skin can detect the difference between inside body temperature and outside skin temperature
“Shorter, near infrared waves are not hot at all – in fact you cannot even feel them. These shorter wavelengths are the ones used by your TV’s remote control. ”
Shrug, I’ll stick with traditional teaching which knows the difference between heat and light.
Which if you go back to my first quote you will notice that they say our perception of visible light is as colour…, we do not perceive visible light as heat as they well know.
Matthew R Marler says:
January 9, 2014 at 12:14 am
Oh, good, someone accusing me of rookie mistakes, that’s always fun.
Matthew, neither you nor Nick have dealt with my example. I will repeat it.
I have a scale and I’m weighing married couples. They both get on the scale, and I record the weight. Then the woman steps off the scale, and I weigh the man. I do this for 1000 couples.
Next, I calculate the woman’s weight in each case as the total minus the man’s weight.
Note that this is exactly the method used by CERES. They measure the total radiation, and they measure part of the radiation. They calculate the value for the rest of the radiation by subtracting one measurement from the other.
Does this method of calculation mean that the weight of the man and the woman are negatively correlated, as you and Nick claim?
No. The method of calculation of the woman’s weight, whether direct or indirect, has no effect on whether or not their weights are correlated.
For example, if we were to do the experiment, since larger men tend to marry larger women and 5’2″ guys rarely marry 6’2″ women, their weights will have a positive correlation. That’s the real correlation, and it has nothing to do with how we measure their weights.
Are you seriously arguing that because of the way that we’ve calculated the woman’s weight, as the total weight minus the husband’s weight (just as CERES does it), that the real-world positive correlation of the couples’ weights will suddenly become negative? Because that is what you and Nick are claiming …
There is a rookie mistake here … but it ain’t mine …
w.
The NickStokes “arithmetic correlation hypothesis” for Dummies:
(a definitive experiment?)
A) create a blank spreadsheet of , eg, 100 rows
B) fill column LW with randomly-generated numbers between ,eg, [200 .. 300]
C) fill column SW with randomly-generated numbers between ,eg, [50 .. 150]
D) define column TOT as (LW + SW)
E) define column LWx as (TOT – SW) [ie: (LW+SW) – SW ]
F) define column SWx as (TOT – LWx) [ie, (TOT- (TOT-SW))]
G) calculate correlation coefs for this pair of series: (LW, SW)
(( i predict near-zero correlations betwixt random series))
H) calculate correlation coefs for each of these pairs: (TOT, LW) and (TOT, SW)
(( i predict non-zero correlations for these DEPENDENT arithmetically-related pairs ))
I) calculate correlation coefs for this pair: (LWx, SWx)
(( I predict the SAME near-zero result as for (LW, SW) —
despite the arithmetic derivations, the quantities remain INDEPENDENT ))
X) deduction: if LW and SW were generated with some non-zero correlation ,
[to simulate the Willis Hypothesis] ,
the (LWx , SWx) series pair would retain that same correlation.
Willis: “I’m just saying that if you don’t know something, ASK. You didn’t have a clue what the “roundto” variable did, but despite that you accused me of using “crude rounding” … and all the while, my legend numbers were accurate to 100 decimal places.”
In the code you provided in the link you had a different range for the colour legend and when I increased the number of sig figs in the legend 0.2 become 0.25 . While it is turns out that the range you used in fig 2 here the legend falls on exact 0.1 intervals and is accurate, that is what lead me to question whether 0.6 was not a truncated 0.67.
I don’t know why you always any critical comments as a personal affront. I was not “accusing” you, I was trying to discuss what you were presenting. That is what this blog is about. It’s not like you have a peer reviewed paper published and I’m rebutting it. It’s a discussion.
The main point, which I was trying to point out was the impression that the map itself was banding the values into intervals. These are the interval that I have been asking about but you have not understood what I was referring to. However, I have done a screen cap of the R plot and zoom it to 800% in Gimp and the visual impression I had about bands is not the case. There are colour nuances. The fact that this is not very clear is probably a function of the colour mapping in R . The help on that says it is sub-optimal and may not be very good in RGB space. So I guess we’re stuck with it.
This all comes back to what I originally suggested would be visually better and more informative would be a finer colour scale. I have not found out how to get more colours into the colour scale and you have not replied to my request for help on that.
You have your reasons to always use the same colour scheme but it is not the clearest scheme for this data. that is why I reworked the colour scheme to highlight the areas with significant correlation.
http://i39.tinypic.com/2crqzhu.png
One omission in the article is a value of what CC may be considered significant and without that it is difficult to know how to interpret the graph. I find a value of 0.48 which is fairly high due to short data and the smoothing and puts the coastal regions that stood out into ‘no significant correlation’.
I don’t know whether you have a different idea of what the significance level should be, stats is not my speciality. Maybe someone else could comment on that.
Best regards.
Willis,
“Does this method of calculation mean that the weight of the man and the woman are negatively correlated, as you and Nick claim?”
No, but I don’t claim it does. Incidentally, I don’t object to this as a way of getting the weight estimate. Your 7=(4+7)-4 is OK as far as the actual estimate (expected value) is concerned. The issue is trying to make inferences from the covariance, where independence etc matters.
Again, you’re turning the argument around. Yes, in the weighing you may not have negative correlation; in fact maybe none at all. But you are trying to infer something from an observed negative correlation of A and B-A. And my point is that the negative correlation is consistent with various possibilities, including, in the coins example, nothing meaningful at all. So you can’t deduce anything from it.
Alac Rawls: “I think Willis and Greg need to look at this again.”
Yes, Alec, that last comment was posted well past my bedtime 😉 . Your comment made sence when I first read it as you see in my initial reply. I got a bit confused by Jan’s comment and forgot the SW was reflected, not incoming.
As I said originally, it’s a bit of chicken and egg situation. Direction of causation may need more digging.
Nick , sorry if you’ve replied and I missed it but I don’t think so. It seems the simplest way to ask the question is: why would the “arithmatic” produce a correlation between (LW+SW-SW) and SW ?
You suggested a neg. corr. was a necessary consequence of the arithmatic and thus had no significance. I don’t see that.
Alec Rawls: “I think Willis and Greg need to look at this again. The more SW is reflected back into space by clouds the less reaches and warms the planet’s surface, reducing the amount of upwelling LW. Thus clouds should be expected to CAUSE the negative correlation between upwelling and SW and upwelling LW that Willis has found. (In other words, Jan and I have this right: we are talking about upwelling SW and we are talking about its negative correlation with upwelling LW, as documented by willis.)”
As I implied above, I agree with Mr. Rawls. There may well be a good reason to ignore the causal direction to which Mr. Rawls refers, but I have seen no clear explanation on this thread of what it is.
Causal direction. If it’s cloud that causes LW change, it raises the question : what causes the cloud?
1. External eg. Svensmark, oceanic or atmospheric tides …
2. SST => Willis
3. mutually caused oscillation arising from chaotic variability: chicken and egg.
WIllis: I find this analysis very interesting, but have some concerns about working with monthly temperature anomalies rather than absolute temperatures. Outgoing LWR varies with the fourth power of absolute temperature, not temperature anomaly. Temperature anomalies obscure relatively large seasonal changes in temperature. The mean global surface temperature is 3-4 degK higher in July, than in January, a roughly a 20 W/m2 seasonal difference in average surface emission. The roughly +/-1 W/m2 variation in LWR and SWR anomalies in your Figure 3 represents the small differences after correcting for much larger seasonal changes with anomalies.
A number of people have tried to calculate feedbacks using the seasonal change in surface temperature and TOA radiation. The latest effort (and references to earlier work) can be found at the link below. The paper looks at outgoing LWR and SWR from all skies, clear skies and cloudy skies and conclude that cloud radiative feedback is small. Interestingly, reflected SWR from CLEAR skies (and all skies) decreases 4-5 W/m2 as mean global temperature rises 3+ degK every year, probably due to less reflection from snow and ice-covered surfaces during summer in the NH. In contrast, reflected SWR from cloudy skies increases about 1 W/m2 as the global warms 3+ degK. (They don’t tell us how much the cloud fraction changes with the season, but the all-skies result shows that the most important SEASONAL change in SWR comes from clear skies.) None of my comments are meant to imply that your analysis is wrong; just that other interesting methods have been applied to the same data set you are using.
http://www.pnas.org/content/110/19/7568.full
Greg says: January 9, 2014 at 1:41 am
“Nick , sorry if you’ve replied and I missed it but I don’t think so. It seems the simplest way to ask the question is: why would the “arithmatic” produce a correlation between (LW+SW-SW) and SW ?”
Well, I said above that the formula for correlation of A with B-A is
ρ=(σ_B ρ_AB – σ_A)/sqrt(σ_A^2+σ_B^2)
There’s an error in the denominator, which doesn’t affect the sign; it should be
ρ=(σ_B ρ_AB – σ_A)/sqrt(σ_A^2 + σ_B^2 – 2ρ_AB σ_A σ_B)
Setting the sd ratio r=σ_A/σ_B, that gives:
ρ=(ρ_AB – r)/sqrt(r^2 + 1 – 2ρ_AB r)
Now ρ_AB is between -1 and 1. If r>1, ρ must be negative. For any r, the centre case is ρ_AB=0, when ρ=-r/sqrt(r^2 + 1). The -r in the numerator is a consequence of the B-A “arithmetic”, and creates a tendency to negative ρ.
But again, I’m not claiming that ρ is always negative. I’m saying that it happens in so many cases that there’s nothing to be concluded just from a case where it proves to be so.
“the formula for correlation of A with B-A is”
but I don’t see A with B-A , I see A with B+A-A
Greg says: January 9, 2014 at 2:56 am
“but I don’t see A with B-A , I see A with B+A-A’
The original problem had measured Tot and SW. LW is calculated as Tot-SW, and was correlated with SW. That is, Tot-SW with SW. B-A with A.
I say we either use the Ceres data or we get rid of all the people and the funding used in operating the instruments.
Whenever someone (Willis in this case) finds something particularly insightful with climate data or climate monitoring devices/systems, the pro-AGW’ers pile in and say you can’t use that particular system. A long series of mostly incoherent posts continue until that person loses faith in their newfound insight.
Meanwhile clime science goes on wasting millions of dollars per year continuing to operate the systems (that the pro-AGW’ers say we can’t use). And then the pro-AGW’ers continue on writing papers using the same data from the same systems.
This data presented by Willis is particularly insightful. It answers a huge question with respect to the theory. What do clouds do (or total SW reflectance which is more comprehensive than clouds by themselves anyway) when there is warming.
The feedback is negative and the data says it is a large negative. Opposite to the theory.
ρ=(σ_B ρ_AB – σ_A)/sqrt(σ_A^2 + σ_B^2 – 2ρ_AB σ_A σ_B)
I’m not sure how you derived that but by symmetry it looks like a term has been lost in denom:
ρ=(σ_B. ρ_AB – σ_A)/sqrt(σ_A^2 + ρ_AB^2.σ_B^2 – 2ρ_AB σ_A σ_B)
??
“Tot-SW with SW. B-A with A.”
I can see there could be problem with measurement errors and variation not related to SW,LW relation correlating, since both are surely present in large doses. But isn’t that the point of signif estimations?
Can you suggest a formula for 95% confidence value of correlation coeff ?
Willis Eschenbach says:
January 8, 2014 at 9:45 pm
Phil. says:
January 8, 2014 at 5:33 pm
… “For particles much larger than the wavelength of the incident light, the scattering efficiency approaches 2. That is, a large particle removes from the beam twice the amount of light intercepted by its geometric cross-sectional area. What is the explanation for this paradox?”
Ah, I finally see the problem. The meaning of “incident” was unclear. To everyone out here, the “incident light” is all of the light that is affected by the object in question, and “non-incident light” is the light that is unaffected by the object.
To you, “incident light” is the NOT the amount of light intercepted by the actual phenomenon. Instead, it is just a number, it’s the light intensity times the cross-sectional area of the particle. As such, to you the incident light does NOT include all of the light affected by the phenomenon. In your terminology, some “non-incident light” is also affected.
It’s a problem with specialists, they forget that the words that have special meaning within a discipline do not have the same meaning to the general public.
Because to us, if light is getting either scattered or absorbed by a particle, then perforce it is “incident light”, and the light that is not scattered is not incident light.
But to you, the light being scattered by a particle is NOT incident light.
As a result, when you say that a particle can absorb 100% of the incident light and also reflect 100% of the incident light, folks like myself say “huh”?
Since you are the specialist, this misunderstanding is on you. When you use a term in some non-standard way, you owe it to your readers to point that out … because there’s no way that your readership can be expected to understand your non-normal use of the term.
Thanks for persevering, I finally got the answer to my “huh”?
Thank you for persevering too, to me the light incident on a droplet is as you say above the cross-sectional area multiplied by the light intensity. The explanation was included in the article I cited. The light scattered is additional to that so the drops remove more light from the beam than falls on that drop. The same phenomenon is observed in macroscopic objects, e.g. we know how much sunlight falls on the earth, it’s the cross sectional area multiplied by the solar irradiance, you’ve calculated it many times. However, if you were out at Jupiter’s orbit observing the sun and earth transited the sun the amount that the sunlight would reduce by is twice that value.
I disagree that my use of ‘incident’ is non-standard, the dictionary definition is:
“(esp. of light or other radiation) falling on or striking something.
“when an ion beam is incident on a surface””
As a scientist I use the language precisely, people reading what I write should take that into account (no criticism intended).
The original reason for my comment was that ‘clouds absorb all the IR incident on them’, the point of my comment was that this is impossible because half of the light incident on the cloud will be scattered and for drops smaller than the incident light wavelength half of that light will be backscattered out of the cloud. In that situation the maximum which could be absorbed would be 75%, I hope that’s clear?
That phenomenon is in fact how drop size in clouds can be measured by remote sensing of that backscattered light.
By ‘backscatter’ I mean light directed in the 180º back towards the observer.
Willis Eschenbach says:
January 8, 2014 at 3:46 pm
Ok, but the important question to ask is why should the albedo increase, and I cannot find any reason for it to do that.
An alterative explanation for the correlation you have found is as follows:
I think we can take for granted that there is a very strong correlation between incoming SW and reflected SW. If the albedo is constant the correlation = 1.
I think we also safely can take for granted that there is a strong correlation between incoming SW radiation and temperature in both the atmosphere and the surface. More incoming SW gives more heating which gives higher temperature.
Likewise, there is of course a strong correlation between the surface temperature and the LW radiation. There is also a strong correlation between atmosphere temperature and LW radiation from the atmosphere.
Because incoming SW is correlated to reflected SW, and incoming SW is correlated to temperature, which is correlated to LW, we then have that reflected SW is correlated to LW.
/ Jan
“The original reason for my comment was that ‘clouds absorb all the IR incident on them’, the point of my comment was that this is impossible because half of the light incident on the cloud will be scattered”
cf
“Each droplet in the cloud will absorb ~100% of the incident light and also scatter an equal amount of the incident light.”
What you originally wrote was mis-worded. Whatever the complexity of the mechanisms involved it is incorrect to say ” absorb ~100%” and “scatter an equal amount” ie “~100%” of the same thing (whatever it’s called and how it is defined).
If you had originally said “half of the light incident on the cloud will be scattered”, I’m sure it would have been understood perfectly and would have effectively corrected whoever it was that said a cloud absorbed all incident IR.
This is quite a significant point because the downward LWIR from clouds is usually described as being re-emitted which implies assumptions about spectral content.
I would imagine that MODTRAN / HITRAN model this correctly, however, that some false assumptions are being made by climate modellers or in calibration and interpretation of satellite data seems quite possible. Could such an issue contribute to the CERES TOA budget imbalance?
Thanks for highlighting this important distinction.
By arithmetic. If LW=measured Tot – measured SW, and you correlate LW with SW, you’re measuring how changes in SW match changes in LW. But if SW rises by 1 unit, for whatever reason, , that guarantees a drop component of 1 unit in LW, to which is added a statistical change in Tot. That guaranteed component (via -SW) weighs heavily and artificially in the correlation.
No, it doesn’t, that’s only true if the total is a constrained constant. Think of it the other way around. Suppose that one were directly measuring LW and SW and inferring the total, as it makes it easier to review the possibilities and is, of course, the exact same problem. We have four possibilities: LW and SW go up; LW goes up, SW goes down; LW goes down, SW goes up; LW and SW go down. In two cases LW and SW covary and are positively correlated, in two cases LW and SW countervary and are negatively correlated.
The total will, of course, go up and down more strongly with the positively correlated cases and will remain more nearly constant with the negatively correlated cases, but recall, it is not constrained to be constant and in fact it varies, strongly, all of the time everywhere.
I believe that this is Willis’ point. In fact the have a strong tendency to countervary and in fact are fairly decisively negatively correlated. This makes sense in a model that is essentially stable and I don’t find it surprising, but I don’t think it is in any sense “built in” to the numbers themseleves.
The big question is whether or not it is consistent with the positive feedback, high climate sensitivity models. There I am not convinced that the argument is sufficient, or even necessarily relevant. The problem I have comes from several issues — one is that Willis is using SW, if I understand it correctly, primarily as a proxy for the effect of high-albedo daytime clouds, snow, ice, and the lower amplitude modulation of albedo due to deciduous vegetation and cropland utilization. The Sun’s TOA insolation variability is, after all, nearly constant on a daily basis even though it varies substantially (91 W/m^2) over a year.
Suppose albedo varied completely randomly and due only to clouds. Then what would we expect that LW radiation to do? Well, one thing we would expect it to do is vary in any give cell completely in tandem with the seasons and average seasonal temperature. The way seasons work, we’d expect “ground” LW to vary the same way, but with a lag — it takes time to warm or cool any given parcel in response to a change in solar-inclination forcing, and of course a lot of the response comes not from a direct effect but from indirect effects like the delivery of a pre-cooled arctic air mass down to North Carolina that in no way reflects the actual solar-inclination local equilibrium. So there is a lot of energy transport and noise. Still, one major component of LW varies only with the ground temperature, and that co-varies with the seasonal SW. We’d expect a strong positive correlation between the two on the basis of this alone.
However, life is never that simple. First, the data is seasonally detrended. Basically, this means that this huge positive correlation is thrown away. Second — and remember, we’re still asserting completely random clouds here — LWIR doesn’t come just from the ground. Let’s assume that there are three components to the LWIR — one is direct ground radiation (clear sky). One is indirect radiation from greenhouse gases at a band of heights approaching the top of the troposphere and is temperature suppressed. The third is from the random clouds, which block the ground radiation and replace it with more weakly temperature suppressed broadband radiation from an intermediate height (but which also represent a substantial amount of latent heat carried aloft).
Let’s consider clear sky as the baseline. Albedo is low, SW emission is seasonally adjusted “normal”. LW is also seasonally adjusted “normal”. A random cloud wanders by. Albedo rises. SW increases. The cloud blocks LW from the ground, replaces it with LW from the cloud in the unblocked bands and alters a bunch of things nonlinearly in the air above the clouds but I would have to say that the net daytime effect is going to be a decrease in LW. Consequently, even if the clouds were 100% randomly generated, utterly decorrelated from any cause, I’d expect a general negative correlation between SW and LW (which could be overridden, one imagines, by nonlinear transport phenomena e.g. the movement of warm wet clouds into an area that would ordinarily be much colder, as will happen in a couple of days in NC when we get a warm air mass pulled up from the Gulf.
Hence my inclination is to say that what Willis is showing isn’t a demonstration of a causal connection, but something one would predict as a natural feature of “the way clouds work”. So I agree that there is some sort of problem here with the conclusion, but it isn’t because statistical differences of unconstrained quantities “have” to countervary — they don’t, and the result isn’t a statistical artifact — it is an expected feature of the radiation dynamics of clouds. Clouds almost always increase SW and decrease LW over their daytime area, so given that nearly all areas have some average cloud coverage, nearly all areas will exhibit a negative correlation once one has subtracted the probably dominant positive correlation between SW and LW due to seasonal variations out.
The test for this is simple enough. In the map Willis shows above, the areas with positive LW/SW correlation are — deserts. There there is no cloudiness, and LW and SW vary weakly together, even after seasonal adjustment. Where is it strongest over land masses? Places where there is lots of ice and/or are very elevated, and rain belts.
So I’m not at all convinced that the negative correlation is meaningful, but not for the reason you describe. It is because I don’t see how it could be otherwise, given the TOA spectrographs for cloud covered regions in e.g. Petty. It’s just the way clouds work.
I think what Willis WANTS to show is going to be more difficult to show than this. In fact, I think it can only be shown by searching for lagged dynamic fluctuation autocorrelation, not static correlation. It is the parcel that heats and then clouds appear to cool it that is what he is trying to show, but merely showing the clouds are correlated with increased SW and decreased LW does not accomplish it. We already know that.
rgb
Thanks, that clarifies a lot. Nice and clearly put.
I think Willis’ original post on this was looking at the hour of onset of cloud in a band across the equatorial Pacific. It is probably in high temporal resolution data that the phase response can be found to prove such an effect.
There’s generally too much detrending , deseasonalising and incorrectly sampled decimation and averaging going on in climatology. This probably fine if you start out prove everything is “stochastic” noise + CO2 , but often impedes a more serious system analysis.
…if the emitted radiation must equal the incoming radiation (so the earf does not experience an increase or decrease in temperature)… Then what energy forms all that corn, wood, grass, algae and other plant matter? Is that so trivial as to be negligible?
Stephen Rasey: “In the CERES dataSET 12 pm, 1 pm, 2pm, 3pm, etc. coverage comes from low resuolution geosynchronous MODIS data from GOES satellites, that are converted (SOMEHOW!!) into CERES data”
Willis Eschenbach: “[E]ach one of the three satellites images about half of the planet every day.”
Pardon me for kibitizing, but I had hoped that someone who’d slogged through the documentation could answer Mr. Rasey’s question question, and it’s not clear to me that Mr. Eschenbach did.
Mr. Rasey says there are only two sun-synchronous low-orbit satellites but that the data purport to give an output value for each hour at each location. Mr. Eschenbach says there are three such satellites. Given a 99-minute orbit and a horizon distance of about 2900 kilometers, it seems that each satellite would view every equatorial location for about a 13-minute stretch each day and about a 13-minute stretch each night, with higher-latitude locations getting more exposure because of path overlap: each satellite would see every location every twenty-four hours.
But even if there are three sun-synchronous satellites and they are optimally spaced, wouldn’t each equatorial site be visited only once every four hours?
Brian says:
January 9, 2014 at 8:09 am
Hi Brian
The thing is that energy cannot be destroyed; it can only be converted to another form of energy. That is one of the fundamental physical laws.
So all the energy that forms corn, grass and other biomass will be stored as chemical bound energy until that biomass is eaten, burned, rot or in other way disappears.
Then that chemically stored energy will be released as heat and radiated as longwave radiation back to space.
/ Jan
@Nick Stokes- Actually, them being negatively correlated (and the stronger, closer to negative one the better) means *exactly* what Willis “wants it to mean.”
What you are not grasping is that Willis’s hypothesis is essentially equivalent to dTot/dt = 0. Therefore he has devised exactly the right sort of test to see if that should be so, for the reasons he thinks.
The only real problem is, he should be testing to see if the correlation is significantly different from -1, not significantly different from 0. Because *if* dTot/dt = 0, always and everywhere, the correlation will be exactly -1, and if Willis *doesn’t* find that correlations are signficantly different from -1, he would *fail to reject his hypothesis* that dTot/dt = 0.
Greg says:
January 9, 2014 at 6:59 am
If you had originally said “half of the light incident on the cloud will be scattered”, I’m sure it would have been understood perfectly and would have effectively corrected whoever it was that said a cloud absorbed all incident IR.
And as I pointed out above half of that would be backscattered under certain circumstances and so be downward LWIR. This is independent of any blackbody radiation emitted from the droplets which is another component of LWIR.
This is quite a significant point because the downward LWIR from clouds is usually described as being re-emitted which implies assumptions about spectral content.
These are two components to the LWIR, the backscatter would depend inter alia on the drop size distribution of the cloud, the emission will depend on the drop temperature.
Willis:
Willis Eschenbach Jan 8 11:39 pm
Not sure where you got that idea [that CERES data is mostly GOES]. Actually, the CERES instruments are flying on four different satellites, Aqua, Terra, TRMM, and Suomi NPP. Three of these have polar sun-synchronous orbits, with different equator-crossing times. They are at 750 km altitude and scan limb-to-limb. The fourth one, TRMM, flies at 350 km altitude at a 35° inclination to the poles.
Next, since they image limb-to-limb, that means that the three polar satellites are each sampling a swath ≈ 6,000 km across. And as you pointed out, they are sun-synchronous, one orbit per day. This means that each one of the three satellites images about half of the planet every day.
In other words, most of the input to CERES is from the four CERES satellites, and there is terabytes of it..
Here is where I got my facts:
From Rasey 10/10 8:35 am
10/8 13:33 – Terra:
Period = t = 98.8 min
Distance to Horizon a Perigee = 2767. km
Distance between passes = Ve*t = 2737 km
Grid Cells between passes = 24.7 cells
Grid Cells between 45 deg oblique on each pass = 12.7
Descending pass at 10:30 am
So an equatorial grid cell will see Terra overhead at 10:30 am. Technically, it will see Terra on the horizon (of questionable usefulness), at 8:51 am and at 12:09 pm. Realistically a grid cell gets one overhead pass or two oblique passes per day from Terra.
As you point out, CERES flies on more than Terra. But Aqua, Auro, and Suomi NPP all have 13:30 equatorial passes. Aqua and Aura are in the same train, about 8 minutes apart. Suomi NPP is a few km higher with a period slightly longer, but with still maintains a 13:30 equator pass. So these three satellites are more redundancy than increased in temporal coverage.
TRMM flies below half the height of the others, so covers half the area per pass, so no oblique overlap. It is at an inclination of 35 deg so TRMM doesn’t see beyond 40 deg north and south.
So there you have it. If the CERES dataset has global hourly coverage, then most of it must come from the geostationary imagers. Each grid cell (in the tropics) sees the CERES instrumentation between 3 to 5 times out of 12 daylight hours per day. Likewise for the night hours. The other hours have to be filled from GOES.
All this is in support of the main question. “Is the CERES dataset what you think it is?” There has been a lot of processing, some infill to “minimize temporal sampling errors”, and that “smoking gun” adjustment to reduce a 5 W/m2 systemic error to Hansen’s 0.75 W/m2 hypothesized error. In all those passes through the black box, are some of the correlation mathematical artifacts? I BELIEVE the negative correlations are REAL; it makes sense. But I also believe the dataset is dirtier than it appears at first blush.
Willis: I have a scale and I’m weighing married couples.
A thousand people enter a weight loss program, and we measure before and after weights and their difference: d = a – b (difference = after – before.) We discover that d is negatively correlated with b and infer, voila, that the weight loss is negatively correlated with initial weight, and positively correlated with final weight. Did the initially heavier people lose less weight, on average? or did the finally heavier people lose more weight? Maybe, maybe not. You have an equivalent example showing the maybe, which in my comment I admitted might be true in your energy flow analysis. But maybe not, and your energy flow analysis does not rule out the equivalent maybe not..
Do you want me to provide an example, or would you like to work one out on your own, as a challenge to yourself? I’ll let you think about it a while. The key is to think of a case in which the measurement error in a and b is large relative to the change d.
Willis Eschenbach says:
January 8, 2014 at 2:17 pm
Bulsit says:
January 8, 2014 at 12:15 pm
In atmosphere temperatures gases dosen’t practically emit or absorb any heat radiation (emission/absorbing factor 0,002 aprox), only in higher temperatures over 600C you can measure something like 0,05, in 1500C something like 0,2.
Dear heavens, the fog is thick out there today.
Yes, Bulsit, there is an emissivity for gases … but no, it’s not 0.002. For any particular gas, he emissivity depends on the frequency of the radiation, and varies from 0 to about 1. See the flux emissivity tables and discussion here.
And don’t try to impress us with your wisdom until you have some. Your claim is patent nonsense that any serious researcher would just laugh at.
w.
Pretty strange that atmosphere behaves under different Physical laws than those coal fired power plant boilers. There is absolute nothing radiative heat transfer which we can use under 500 C fluegas temperatures. CO2 is approx 12%. And when we design those boilers we can do pretty good measurements how the heat transfers from fluegases to pipes and how we have managed to calculate heat transfer surfaces. i don’t know who laughs, boilers and how they work aren’t for sure nonsense.
@Willis Eschenbach at 1:55 pm
RE: PLOT: Seasonal Cycles removed Negative or weakly positive correlations worldwide.
PLOT: Seasonal Cycles Not Removed Strongly positive correlation above 35 deg latitude, strongly negative in tropics.
My apologies for missing that plot last night. Yes it is curious. I guess I can understand positive correlation poleward of the circles (Higher SW and Higher LW during polar daylight). I am surprised to see it that strong at 50 N and even a far south as offshore Baja California.
I’m not sure removal of the seasonal signal should be taken for granted. The story in the polar and high temperate regions might change.
But I gather these are still a full year’s data all lumped together. Is it easy to show this plot only for one or two months, such as Jun-July, Dec-Jan (polar extremes) or Mar-Apr (equinox)?
Greg says: January 9, 2014 at 4:36 am
“I’m not sure how you derived that but by symmetry it looks like a term has been lost in denom:”
I just took cov(A,B-A)=cov(A,B)-cov(A,A)
and juggled sd’s to convert to correlation coefs. The denominator is sd(B-A). I think it’s right (it’s like cos rule); your version is the sqrt of a perfect square.
rgbatduke says: January 9, 2014 at 7:02 am
‘That guaranteed component (via -SW) weighs heavily and artificially in the correlation.’
No, it doesn’t, that’s only true if the total is a constrained constant.
I think it does, and the formula I gave for corr(A,B-A) shows it:
ρ=(ρ_AB – r)/sqrt(r^2 + 1 – 2ρ_AB r), r=σ_A/σ_B
You’re saying it’s only true if σ_B=0 (r very large). Well, that certainly ensures ρ negative, but for that it’s enough that r>1, so certainly r>ρ_AB. The point is that having a -A in there by construction puts the -r in the numerator, which weighs heavily toward negative values.
Willis, Nick, Phil, Greg and others: Outgoing SWR + Outgoing LWR does NOT have to equal incoming SWR on a monthly time scale! We know that changes of 0.1 degC in any one month are commonly observed in surface and satellite temperature data. These monthly changes are the result of a large energy imbalances from month to month that tends to average out over a year. The average heat capacity of the air plus a 50 m mixed layer is 157,000 kJ/m2/degK, so an 0.1 degC change in one month requires 15,700 kJ/m2. 1 W/m2 is 2630 W/m2. Therefore an energy imbalance of about 6 W/m2 is driving the average monthly fluctuation in temperature anomaly. The monthly anomalies Willis shows in Figure 3 are about 1 W/m2. Outgoing SWR and LWR anomalies this small are mathematically free to VARY INDEPENDENTLY on a monthly time scale when the average monthly imbalance is this large.
When we work with temperature anomalies, we tend to forget that larger changes are happening to the planet. Due to the asymmetric distribution of land, the planet’s surface temperature as a whole warms 3-4 degC every year. This is partially balanced by the eccentricity of the earth’s orbit which changes incoming SWR and – along with albedo – outgoing SWR. The radiation anomalies we use are what is leftover when two much larger numbers are subtracted. See linked paper on seasonal changes in my earlier comment.
The negative correlation Willis has found does shows that changes in LWR and SWR do tend to compensate on a monthly time scale – the “thermostat” IS working in the right direction. The negative correlation doesn’t tell us how EFFECTIVELY it compensates. On the average, a 1 W/m2 increase in LWR could be associated with an 0.2, 0.5, 1, or even 2 W/m2 drop in SWR and we could observe the same amount of negative correlation in each case.
rgbatduke says:
January 9, 2014 at 7:02 am
Second — and remember, we’re still asserting completely random clouds here — LWIR doesn’t come just from the ground.
The CERES product that Willis is using is as far as I’m aware Surface Upwelling Longwave Radiation (rlus) so this correlation is only with that component. Any effect of the clouds on the upwelling SW as asserted by Willis I would expect to have the opposite effect on surface LW and hence a negative correlation. More clouds means more upwelling SW and therefore less downwelling SW at the surface which implies less upwelling LW. That upwelling LW must then encounter those same clouds as discussed above there will be scattering and absorption which will further reduce the upwelling LW (if the rlus is indeed at the earth’s surface this won’t be a factor, but it will be important for the TOA statistic). So I would expect a negative correlation between these quantities which has nothing to do with GHGs.
Let’s assume that there are three components to the LWIR — one is direct ground radiation (clear sky). One is indirect radiation from greenhouse gases at a band of heights approaching the top of the troposphere and is temperature suppressed. The third is from the random clouds, which block the ground radiation and replace it with more weakly temperature suppressed broadband radiation from an intermediate height (but which also represent a substantial amount of latent heat carried aloft).
Sorry the last para should have been indicated as being from rgbatduke.