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)
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.