Guest Post by Willis Eschenbach
In the comments to a previous post of mine, Bob Wentworth made an interesting point. He said that it’s not enough to propound my new theory of how the climate works. I also have to show that my theory that emergent climate phenomena control the climate is not included in the current climate models and theory. I’d not thought of that before, and it’s a very valid point.
So I decided to see how the models treat the question of how the oceans, and in particular the tropical oceans, respond to downwelling radiation at the surface. To do this, I looked at the correlation between downwelling radiation and sea surface temperature (SST). If the correlation is positive, it means that when the radiation goes up the temperature goes up. And if the correlation is negative, when the temperature goes up, the radiation actually goes down.
So below are the results from five different climate models, showing the response of the oceans to net downwelling radiation at the surface. The net solar radiation is the downwelling solar (shortwave, or “SW”) radiation less what is reflected upwards from the surface, plus the downwelling infrared radiation (longwave, or “LW”) from the clouds and the atmosphere. This is the so-called “greenhouse radiation”
What’s improperly but inalterably called “greenhouse radiation” starts out as energy absorbed by the atmosphere—absorbed solar energy, sensible and latent heat moved from the surface to the atmosphere, and radiation from the surface of the earth that is absorbed by the gases, including greenhouse gases (GHGs) in the atmosphere—water vapor, CO2, methane, and other minor gases. Once the radiation and the other energy is absorbed, it warms the atmosphere. And since anything that can absorb radiation also can emit radiation, those greenhouse gases radiate the absorbed solar, sensible, latent, and radiated heat in all directions.
This downwelling radiation resulting from the atmosphere is what is known as “greenhouse radiation”.
This “greenhouse radiation”, the downwelling radiation from the atmosphere, leaves the surface warmer than it would be if there were no greenhouse gases—if there were no GHGs, the upwelling surface radiation would go straight to space and be lost. But instead, the upwelling surface radiation is absorbed by the greenhouse gases in the atmosphere about half of it is returned to the surface.
(Important note: the above is all well-established science. The downwelling radiation from both the atmosphere and the clouds has been measured, not modeled or estimated, by thousands of scientists around the planet for decades. There’s an entire network of observing sites around the US called SURFRAD, which as the name implies do nothing but measure the radiation flows, both shortwave radiation (sunshine) and longwave radiation (thermal radiation) to and from the surface. Here’s a typical 24-hour measurement of the downwelling infrared (longwave) “greenhouse radiation” from one of the SURFRAD stations.
Figure 1. Downwelling longwave (thermal) radiation from the atmosphere, AKA “greenhouse radiation”, as measured at the Table Mountain SURFRAD station. SOURCE
Now, as I said, there’s no question that such downwelling radiation from the atmosphere is real and leaves the earth warmer than it would be without GHGs. As a result, I politely invite people who do not think that such downwelling radiation is real or that it leaves the earth warmer to take up that argument anywhere but on this thread. This thread is NOT a place to debate the existence of downwelling radiation from the atmosphere. It is a place to discuss the size and nature of the effect of that radiation. So let me be perfectly clear—I will delete any comments that claim that downwelling radiation from the atmosphere doesn’t exist or that it doesn’t leave the earth warmer than in its absence. I’m more than happy for you to debate the existence of downwelling radiation … but please, do it anywhere but on this thread, thanks. And please, don’t whine like a baby about how I’m the krool science police. It’s not gonna work, I’ll just delete that as well. With the caveats clearly stated, let me return to the discussion.)
So here are the results from 5 different climate models, showing the correlation between downwelling “greenhouse” radiation at the surface, and sea surface temperature.
Figures 2 a-e. Results from five climate models involved in CMIP5, the “Climate Model Intercomparison Project”. All of them have used the same data—”ts”, the surface temperature; “rlds”, longwave downwelling surface radiation; “rsds”, shortwave downwelling surface radiation, and “rsus”, shortwave upwelling surface radiation. The model results are all available from the World Climate Research Program. And there’s a list of the variables here.
There are several things of interest in these model results. First, they vary greatly in the amount of ocean that is negatively correlated with downwelling radiation. The MIROC model at the bottom (e) has almost no ocean with a negative correlation to radiation, while the NorESM model (d) has a much larger area.
Second, the strongest correlation is near the poles, with correlations between 0.8 to nearly 1.0.
Third, the average correlation in the tropics is quite varied—0.22, 0.25, 0.36, 0.45, and 0.45 for the various models. And the same is true about global average correlation.
So with that as prologue, here is the actual reality as determined from different observations.
Figures 3 a-c. Results from comparing CERES satellite-based radiation datasets with the Reynolds Optimally Interpolated (Reynolds OI) sea surface temperature (SST), Berkeley Earth SST, and CERES SST.
Some notes about these. First, despite using different datasets, unlike the models they are very close in all values
Second, the correlation near the poles is much smaller than that shown in all of the models.
Third, all of them show larger amounts of negative correlation in the tropics, as well as globally, than do any of the five models.
There’s another way to look at this same data. This is to look at a scatterplot of the longer-term (a couple of decades) averages of the gridcell surface temperatures versus the corresponding average amount of net surface radiation each gridcell receives. Here, for example, is the CERES radiation data versus the Reynolds SST data.
Figure 4. Scatterplot of temperature of the 43,350 1° latitude by 1° longitude oceanic gridcells versus the net downwelling surface gridcell radiation. The black/red line shows a LOWESS smooth of the data. The slope of the LOWESS smooth shows the change in surface temperature for each additional W/m2 of downwelling radiation. Values are longer-term (two-decade) averages of the gridcell variables.
This represents the long-term relationship between downwelling radiation and ocean temperature. The ocean has had hundreds of years to adjust itself to the average amount of downwelling radiation. Note that in the warmest parts of the ocean, the correlation between the radiation and temperature goes negative—as one goes up the other goes down. This is what we saw in the tropics in Figures 3 a-c.
Now, to compare this to other datasets, it’s not too meaningful to include the 43,350 individual data points. So first, let me compare the LOWESS smooth of the data in Figure 3 with the LOWESS smooths of the corresponding data for the other two observational sea surface temperature (SST) datasets, the Berkeley Earth SST data, and the CERES SST data.
Figure 4. LOWESS smooths of scatterplots of net downwelling radiation and sea surface temperatures, observational data.
Other than a small difference near the poles, close to the edge of the sea ice where the water is just above freezing, all three observational datasets are in good agreement. And again, at the warm end of the scale at the right, we see the correlation go negative in all the datasets.
Next, let me compare the LOWESS smooths of the models in the same fashion.
Figure 5. LOWESS smooths of scatterplots of net downwelling radiation and sea surface temperatures, computer model results. Note that only one of them, NorESM, goes negative at the warmest sea surface temperatures.
Again they are similar … but in this case the difference is in the warmest areas. As we saw in Figures 2 above, they differ greatly in the area of the warm ocean where the correlation between radiation and temperature goes negative.
And to close out this part of the discussion, Figure 6 below shows the data in Figure 5, with the observational data from Figure 4 overlaid on the top.
Figure 6. LOWESS smooths of scatterplots of net downwelling radiation and sea surface temperatures, computer model results plus CERES observational data.
Now, my theory about emergent climate phenomena says that at the warmest ocean temperatures, the action of thunderstorms will strongly cool the sea surface … as we see in the observational plots above.
Here’s further evidence that the thunderstorms strongly cool the surface at the highest temperatures. Figure 7 below shows the “net cloud radiative effect” (CRE). Clouds cool the surface by blocking the sun. They also warm the surface by absorbing upwelling longwave from the surface, about half of which is radiated back to the surface. The “net cloud radiative effect” is the sum of the warming and the cooling effects. Here’s the map of the surface net cloud radiative effect.
Figure 7. CERES surface net cloud radiative effect versus Reynolds sea surface temperature.
Note the great strength of cooling at warm sea surface temperatures, up to as much as ~ 70 W/m2 of cooling in certain locations. This is about half of the global ~ 160 W/m2 of average solar energy at the surface. This is what causes the negative correlation between radiation and temperature in the warmest parts of the ocean.
My theory also says that the increase in sea surface temperatures will be slower than it would be otherwise, due to the action of a variety of emergent phenomena acting to cool the surface. And we see that as well in Figure 5 above.
So … does this establish that my theory about emergent climate phenomena is true?
Nope. It’s more support, but its far from establishing it.
However, it does strongly suggest that emergent climate phenomena are not realistically included in the climate models.
Finally, Figures 2 a-e of this analysis reveals the huge differences between just these five climate models … so next time someone says the models are “physics-based”, you’ll know that they’re talking Hollywood.
What do I mean by “talking Hollywood”?
Well, it’s like when Hollywood says a movie is “based on a true story” …
My best wishes to all, stay well in these most curious times …
w.
Post Scriptum: I must confess that I am quite baffled by how mainstream climate scientists handle the whole subject of climate models. Clearly, as shown in Figures 2 a-e above, certain models are fairly close to at least some aspects of reality, while others are very far from reality. For example, the MIROC model shown in Figure 2 (e) is clearly missing some very important aspects of oceanic behavior, while the Norwegian model NorESM Figure 3 (d) gives much more realistic results.
But all of that gets ignored by the mainstream scientists. All of the results of the different climate models are given equal weight, the group is called an “ensemble”, and a simple average of all of their output is taken to be a valid result … say what?
If I ran the zoo, I would get the modelers together and devise some simple tests, something akin to the graphs and regional measurements in Figures 2 a-e above, but covering many other aspects of the real climate system. I would have a competition wherein we could evaluate and rank all of the models based on how well they passed those tests. Not only that, but I would use the tests to examine and elucidate the reasons why some models do so much better than others.
I would also use things like Figure 6 above to work to understand why all of the models that I tested are in one tight bunch, and all the observational datasets are in another tight bunch … what are the models missing?
I have no explanation for why the modelers deal with the models in this curious hands-off “everyone is equal” manner. However, as many folks are more than happy to remind me, I’m merely a fool without any credentials, just three lifetimes or so of personal experience at solving real-world problems … so I’m clearly unqualified to opine on really complex sciency things like climate models.
It does, however, remind me of modern education, where people want to get rid of the SAT and other tests and even get rid of grades so all the students can feel good about themselves.
Similarly, it appears that the scientists just want to give every model a “Participation Prize” so they don’t damage any of the modelers’ precious self-esteem … and sadly, this is what passes for “science” in the climate world.
My Usual Request: QUOTE THE EXACT WORDS THAT YOU ARE DISCUSSING! I can’t tell you how many times folks have twisted, misrepresented, or spun my words and then attacked me regarding their fantasy of what I said. Misunderstandings are the bane of the intarwebs.
First class work, Willis.
And your Post Scrip is spot on. Why would adding, with equal weight, a bad model to an ensemble improve confidence in the ensemble? We have enough history and measurements to conclude some of the models are closer to data than others. Why do we continue as if they are all equally good?
And IF THE SCIENCE IS SETTLED, why have so many models of equal weight giving differet results?
It is definitely NOT “settled.” In the Koonin I mention in my reply to an observation made by Willis, Koonin makes it very clear that the more the modelers have tinkered with the models, the uncertainty and variability of those models has INCREASED, not decreased. Koonin says at one point in the chapter on climate models that “The fact that the spread in their results is increasing is as good evidence as any that the science is far from settled.”
I also that in the pages of this website Judith Curry and Nic Lewis have put the sword to the models in respect to their predictions regarding equilibrium climate sensitivity (ECS). The fact that the models vary so widely in their conclusions about ECS is another reason to question whether these guys actually know as much about they are doing as they should. It is propaganda masquerading as science.
They’re looking for the god prime, observing patterns in the clouds, and simulating the primordial ooze that flows out from their expanded frame of reference. So, predictably, monotonically, the solution diverges from normal. This is not science. It may be philosophy. Time will tell.
simulating theprimordial ooze…LOL.
more like simulating the rectal ooze. they are.
Glad to hear you received “Unsettled.” I placed my order on April 18th. No date for delivery was given for estimate delivery. The release date was May 3rd if I recall correctly. I just checked and they expect to deliver it June 10th.I had started to get concerned that Amazon had borrowed Facebook’s “Fact Checkers” to determine whether they should sell the book or not. Hopefully, the long delay is due to it’s sales and a grotesque underestimate of demand.
The modelers are a ‘club’. Lots of money in modeling. Equal weights insure nobody gets expelled from the club, so the money continues to flow.
For climate modelers, data are either confirmatory or an annoyance.
They have no idea how to critically compare observation and theory to improve the physical theory.
one of several versions of Upton Sinclair’s Lament:
“It is rather pointless to argue with a man whose paycheck depends upon not knowing the right answer.“
The Climate Dowsers are certainly dependent on not knowing the right answer to keep the checks coming.
I wonder, could they model the behaviour of three fishes in a fish tank
Yes indeed. Why do we not just use the good ones?
None of them are “good”, some are just less bad than the others.
The Russian one is pretty good (INM-CM4 Russian Institute for Numerical Mathematics). Accurate temp predictions, good ocean models.
Logically, there can only be one ‘best model.’ Why do we not just use the good one?
There can be no best model because they’re subjective. No “logic” is involved. Best for whom? … best at what? What is the best portrait ever painted?
There is a simple way to prove that all climate models cannot incorporate emergent phenomena like thunderstorms, illustrated in my post some years ago here, ‘The Trouble with Climate Models’. The grid size to actually model such a convection cell, is on the order of 2-4km, which is what the better weather models actually do use. This is possible because they are regional rather than global, and run out a few days rather than many decades.
The numerical solutions constraint to partial differential equayions is called CFL. NCAR says that as a rule of thumb, doubling resolution by halving grid size raises the computational requirement 10x—one order of magnitude. The better CMIP6 models use equatorial grids about 160×160 km. That is still six orders magnitude less than would be needed to do 5km grids.
The climate model solution is parameterization. Parameters cannot emerge; they are set ‘constants’. And, they automatically drag in the attribution problem, which is why models run hot. They attribute warming to anthropogenic rather than natural causes—because that is how the IPCC explicitly defines the game.
A typical comment I get on social media when I explain how the physics of convective weather is not and cannot be directly computed in the models, and therefore the resulting projections are driven by (tunable) parameterizations: “But surely all those scientists have accounted for that.” Oy.
Yuh, no need to challenge the climate priesthood- we must have faith in the Holy Mother Climate Church.
Rud,
consider this;
no matter how good or not, we think,
(you, me or any one else, including WE);
that the CO2 atmospheric concentration variation can be considered as a climate indicator, definitely the thunderstorm phenomena can not enjoy that status.
If you somehow agree with the above, please do consider the point of your comment, in accordance with the models in question… the ‘climate models’.
cheers
Read my previous several posts here in climate models, and/or the several model essays in ebook Blowing Smoke. Then get back.
Rud,
either you know it or not,
I do appreciate a lot you and your work,
but still please try to at least consider what your are told.
“There is no meaning or beauty in the realm of the experiment and models outside the clause of parameterizing.”
Man, you are flirting with the idea of ugliness and “sin” in proposition of science.
Doubling down on Occam’s razor is unacceptable, and ugly, considering that you intellectually enough matured at your age, to at least consider what you are told.
There is no chance or even a meaning in the proposition of any ‘reverse engineering’ outside the clause and the firm dependence on the parameterizing.
Still T.P, (Thunderstorm Phenomena),
do not make it under any circumstances,
as to be considered as a climate indicator or a potential climate variable parameter… period.
Parameters and the parametreizing happens to be the main point or the “blood” of the experiment and/or the concept of modelling.
Wish you the best anyway.
Still you very much appreciated.
🙂
cheers
whiten,
“ happens to be the main point or the “blood” of the experiment and/or the concept of modelling.”
Speaking with 25 years experience in modeling complex chaotic systems I agree with your statement. But speaking with 25 years of experience this is exactly why you must be cautious and VERY critical of the results.
I have lost millions in revenue due to models and modeling – this does not mean that models do not have great usage and are not helpful, indeed I use them frequently. BUT if you do not question the inadequacies of the model or the parameters you are asking for trouble.
I have yet to see a climate model ( I have only seen a few but they all seemed pretty close to one another in parameters and modeling ) that would pass my smell test when it comes to a robust model that I would place faith in.
That does not mean one does not exist HOWEVER can you imagine what would happen to the funding on a modeler that did not agree with the consensus?
Now this does not mean the models are WRONG only that based on what I have seen to date, for a complex system that is our world and the changes we have made to it, the systems seem overly simplistic when you nail them down.
Rud,
you are smart enough, I guess,
to understand,
that what you suggesting there, to me is conceptually impossible.
You, yourself can not accomplish or achieve what you telling me to do.
Once you can really do a full read of your own “genius” there,
I will consider to do it too, honestly.
Your word on it will be good enough.
No other proof or evidence required… only your world.
But you got to do it first.
cheers
Excellent claptrap
And claptrap isn’t as easy as it looks.
See the Chomskybot for great claptrap. Random phrase generators produce what looks profound, but is complete nonsense.
You’re making up utter gibberish or you’ve run what you did write through a faulty translator.
Willis, a very very good post… summarizing many of the concerns that all of us have had all along with the climate modelers. Some models produce graphs, some produce giraffes, some just …garbage.
“I also have to show that my theory that emergent climate phenomena control the climate is not included in the current climate models and theory.”
A nice trick, asking you to prove a negative. My friend moved from London to Prague and wanted to insure his new Czech car. The insurance company asked him to prove that his new car was NOT insured in the UK.
Don’t you just love those folks that ask you to prove a negative? My response to them is “I think you are a serial child molester. Prove that I’m wrong.”
that’s Kafkaesque
I suspect that there is a language barrier there and when they said “prove”, they meant something like “confirm”.
I have downloaded all of the CMIP6 models of all the SSP scenarios and different physics for the various parameters from that site and looked at the comparisons with observations. Why did you choose the CMIP5 and not the latest CMIP6? Which model scenarios and physics did you choose and why? Questions a reviewer would want a complete answer to.
As you say some of the models are quite good while others are very poor. If I was doing modeling I would be looking at why some are performing so much better than others. But they all get lumped into one. Also, being from Canada, it is rather dismaying that when looking at the temperatures the Canadian models (there are two, one of which is the CanESM5) are among the bottom 5 worst performing for all of the SSP types.
Thanks, Max. I’ve used CMIP5 because I haven’t found a convenient site to download the relevant variables. A link to the site that you used would be welcome.
However, since the improvements in the models are generally incremental rather than fundamental, I’m not expecting big differences.
w.
Here is the site I use.
https://esgf-node.llnl.gov/search/cmip6/
I did not notice it was not the same as the one you had. Actually, there are some big differences between the two, most of which are worse with the CMIP6.
On another note, I have done reviewing, and if I was reviewing this an important point I would want addressed is this. As I understand it (and you or others can correct me if I am wrong), CERES, as a satellite, does not measure down welling radiation. It is calculated using the radiation equations. So, in effect CERES is also a model. The climate models also use the radiation physics. So you are actually comparing one model to another. Why would, or is, the radiation physics of the climate models different from the CERES radiation physics? I would want an in depth discussion of that. I certainly do not know the answer.
To Max. I have applied the CERES radiation measurements a lot. The downwelling SW radiation is simply the TSI radiation minus upwelling SW radiation. So, it is observation-based radiation and not any model-based radiation.
The climate establishment has been silent about the huge SW anomaly since 2001. It has caused an RF anomaly of 1.68 W/m2 forcing being as great as CO2 forcing 1.68 W/m2 from 1750 to 2011. It is the reason together with El Nino for high temperature in the period 2015-2020, and now this anomaly is probably over since the temperature has come back the pause level 1998-2014.
I used the CMIP5 “historical” scenarios and the “r1i1p1f1” variant. Unfortunately, the CMIP6 model data says:
Not only that, but for my analysis I need the datasets rlds, rsds, rsus, and ts. And NONE of the models have historical data for “historical”, “r1i1p1f1” and those datasets/
I swear, they are making this as difficult as possible. And the
w.
Yes, it is very difficult. But reviewers do not give a rat’s ass about that. They will look for ways to reject a paper. I used mostly the r1i1p1 variant as it is available for most CMIP6 models. But I really do not know the physics it entails. If I was to publish I would have to explain exactly what that physics package was doing, why it was different from others, why I chose it, etc. In effect you have to know exactly what the models are doing and explain it. Man, that’s a whole research area in itself. Not something I would want to get into. It requires a lot of literature review and studying the models.
I was the Senior Instrumentation and Controls Engineer at TMI-II for the start up of the plant. I calculated every ICS (Instrumentation and Control System) for the NSSS, Nuclear Steam Supply System – The reactor and all inherent functions. That means I took the “Predicted” heat Balance of the plant at zero, 20, 40, 60, 80 and 100 percent power as the baseline for the probable value of these NSSS parameters. This was needed to get the control system (actually an Analog Computer) in the “Ball Park.” We used a 24-channel digital recorder recording the most important parameters of the NSSS. Primarily, those used and needed for the RETRAN computer simulation used for the Safety Analysis Evaluation and eventual NRC Certification. This information was valuable for the investigation and analysis of the TMI-II accident. The recorded data from this Data Recorder recorded every required Performance Verification Test, e.g., Loss of Off Site Power, Loss of Load, Turbine Trip, Reactor Trip (Scram) and many more. Although we got a fairly good Idea of the cause and significance of the accident from the RETRAN analysis of the accident with this information, that is a conclusion that was better than two Sigma.
I describe all of the above because with all of that available information and a computer model that was within two sigma, it took two years – well over 10,000 computer hours, to get RETRAN output/predictions that were within three Sigma of “Accidents” previously recorded on the Data Recorder.
Yet all of these climate change modelers, “ex-spurts,” have no idea of the needed parameters, their properties, the number of variables, etc., etc., etc. Worse, these modelers are taking short cuts similar to “Averaging all sic of the Feed-water heaters int one “Average feedwater Heater.” Averaging the temperature across hundreds of square miles from data that is taken from one point in that 1000 square mile area Taking the average of the wind speed across hundreds of square miles from data that is taken from one point in that 1000 square mile area. Same for Ocean Temperature, etc. etc., etc. If these people really could write a computer model that predicted the global temperature 100 years from now they could write one that predicted the value of ONE STOCK a week from now. WHERE is this computer model that can predict the value of just one stock just one week from now. And that is an orders of magnitude simpler problem than predicting the temperature of the globe 100 years from now.
I seriously doubt that there are even two Global Temperature Models that are within 0.5 sigma let alone 1 sigma.
Yeah but Rich did you first take into account what you “felt” your models should produce?
(as the climate models are tuned to do)
Feelings over facts are actually part of the post-modern science consensus building process.
Joel
You’ve just hurt my feelings with your micro-aggressive factoid!
Interesting post, Willis. Thank you. I wonder about precipitation, observed vs modeled, analyzed like this.
From what I’ve read, the emulation of real-world precipitation is one of the worst aspects of the climate models. Not sure how I’d test that, however.
w.
I have dome work on weather modeling. That is a fact. There is no unique physics of precipitation. There are a number of precipitation schemes. Some work better than others for different weather patterns. But the trick is, you never know in advance which one will be the best.
Sounds like the way I view poker: 50% luck, 50% skill, and 50% of the skill is knowing when you’ll get lucky.
But only half the time.
I also question how, if, they include and account for the rivers of water, larger than the Amazon River, transferring water from one point to another thousands of miles away. Carrying all of the energy contained in the latent heat of evaporation, then released as the latent heat of condensation. Then there is the latent heat of solidification and the inverse when the snowflakes melt. We are talking thousands of joules for evaporation/condensation per gram and hundreds joules per gram for ice. All of that energy moving at the speed of the jet stream carrying it.
OK, you just made my head hurt.
The KNMI data for CMIP5 models offers precipitation minus evaporation. This is one of the worst outputs because they do not accumulate the difference over a year. So there can be as much precipitation as desired to give a scary result without ever worrying about getting the water into the atmosphere. This is a plot of the CMIP5 mean:
http://climexp.knmi.nl/data/icmip5_pme_Amon_modmean_rcp85_0-360E_-90-90N_n_+++_2000:2020.png
Look at where the zero line is.
You and Willis should collaborate and combine this with the three part essay you just wrote and give us a nicely wrapped package.
Willis
My reading has led to the same conclusion. Supposedly, regional forecasts of precipitation sometimes even have opposite signs. The time-series functions describing temperature changes are continuous. Whereas, precipitation is discontinuous and even short-term forecasts have high false-positive rates because the rainfall is often highly localized — except in places like California where Winter rains may cover all of Northern California.
Dave, you can get CMIP5 precipitation estimates at KNMI. Dunno about CMIP6 yet.
And you can get the ARGO ‘ocean fresh water storage’ precipitation data derived from the salinity instrument at the Scripps/USC Argo data repository. Models underestimate ARGO observed ocean precipitation by about half, implying they have about double the observational WVF because theynare missing rain washout.
There was a paper about CMIP3 ocean precipitation that concluded basically the same thing. Wentz et al, How much more rain will global warming bring? SCIENCE 317:233-235 (2007)
Yes, precipitation is available in CMIP6, I have used it.
I’m replying to my own comment here. Thanks to Willis and to Rud for their replies. I finally remembered something I had seen over a year ago. This paper “Structure and Performance of GFDL’s CM4.0 Climate Model” (Held et al 2019) reports RMSE (root mean square error) for precipitation in comparison to the CMIP5 models and to the previous/other GFDL versions. See figures 18, 19, 20 and the surrounding narrative. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019MS001829
In Figure 18, the median RMSE for CMIP5 models on an annual basis is shown at 1.3 mm/day. The NOAA GPCP v2.3 data set is used for observed values (2.5 deg x 2.5 deg grid, monthly values.) See https://psl.noaa.gov/data/gridded/data.gpcp.html
So how much is 1.3 mm/day in terms of energy? I get 37 W/m^2 for the latent heat released by condensation into rain. Seems like a lot, when the models are claimed to usefully simulate the global effect of single-digit W/m^2 from GHG’s.
I would suggest most “talking Hollywood” climate models are closer to a Marvel comic movie full of super heroes able to defy physics using computer generated magic than to any “true story.” The climate model outputs are just computer generated magic.
As for the use of all the various national models in the intercomparison project ensemble, that is the clearest external indicator (without even digging into the internals of what and how they implement) that everything they output is utter bullcrap garbage science, even if there is some hard physics buried in there somewhere. The internals of the models are like taking the ingredients of serious radiation physics call it the flour and sugar and then baking it together with several cup fulls of bullcrap to make a cake. The result is not a scientific cake, but rather crap-cake. A crap-cake that I would strongly warn against taking a taste of. All of that together is why I label all the GSM makers, Climate Dowsers, trying use methods of divinations to locate water.
How about the Wizard of Oz, Joel? That would be a good, Hollywood way of describing it, too. Lol!
My uncle dowsed for wells for friends. We were skeptical. So my aunt took me and my brothers and sisters dowsing. I was a young teenager at the time. Willow stick, walk around. The stick moves down at some locations, not of my volition. My brother held my aunt’s stick along with her so she could not influence it. It still went down. Was there water there? We were in the flood plain of a creek so almost certainly. Why did the stick move by itself? Not a clue. I now have a degree in chemical engineering – still no idea what could cause that. Certainly the strangest thing I have ever seen.
I had a friend who believed in dowsing. I blindfolded him and led him over a garden hose twice, and he didn’t react. Most dowsers don’t understand the concept of a ‘water table.’
Joel
I liken the situation of “physics-based models” to adding a ‘fudge factor’ to Einstein’s famous energy/mass equivalence equation. That is, by writing E = mc^2 + F, one can claim it is “physics-based,” and yet get almost any results one wants by careful selection of the ‘fudge factor,’ F. As long as any part of the equation is subject to the insertion of a subjective ‘tuning variable,’ it ceases to be “physics-based.”
A new one: UN IPCC CliSciFi CMIP6 crap-cake. Thanks, Joel. Rolls off the tongue better than “Bunk.”
Great post; bookmarked under “thermostat effect.”
But just to dumb it down for me so I’m understanding what I’m seeing:
The dots in the scatterplots are hourly readings?
An explanation of the negative correlation is that the higher tropical sea-surface temperatures make thunderstorms appear earlier and thus make high local albedo last longer?
Hey, Joe, always good to hear from you. The dots in the scatterplots are longer-term (a couple of decades) averages of monthly data.
And you are correct about the negative correlation making more thunderstorms appear earlier, although the effects of that extend far beyond simple albedo.
Regards,
w.
Thanks a lot; that time interval makes more sense.
“But instead, the upwelling surface radiation is absorbed by the greenhouse gases in the atmosphere about half of it is returned to the surface.”
returned to the surface ? don’t you mean radiated towards the surface …
and since the surface is at a higher temperature it cannot absorb this radiation …
So explain what this radiation does to the surface ?
Sure. See here.
w.
I have in my house a ventilation system with the heat exchange moving heat from the outgoing air to the incoming air. The temperature of the incoming airflow is something like 17…18 Celcius degrees and my energy bill is about 25 % lower. Is it imagination? Energy transferred from a low temperature to a higher temperature? Yes, so it is.
Without doing any extra work or energy input?
Transferring dollars between people is also covered by the Second Law of Thermodynamics.
Yes,the surface does absorb the downwelling radiation. The surface is also radiating upwards, and the NET radiation at the surface must be from the hotter body to the cooler body.
“Yes,the surface does absorb the downwelling radiation. “
Evidence would be really nice.
DL, Look at it like the atmosphere is acting as an insulator. It slows down the heat loss from the surface.
“DL, Look at it like the atmosphere is acting as an insulator. It slows down the heat loss from the surface.”
Again, where is your evidence?
An object radiates at its temperature at any given moment.
I’ve said it before but I’ll mention it again. Be cautious about conclusions you’re drawing from the CERES model. If you wish to get published you must discuss and acknowledge exactly what this data is. All the MODIS satellite can do in the longwave spectrum is measure “brightness temperature”. So it’s just measuring temperature from above. All the downwelling and upwelling whatnot is simply a function of the temperature measured by MODIS from space, with CERES taking those temperature measurements and running it through a radiative transfer model with various other inputs and parameterizations from the earth observation system EOS. It is simply meant to distribute spatially the radiative transfer equations using temperature from MODIS. Additionally, a quick accuracy assessment check indicates much uncertainty in the tails of the distribution, but likely an adequate mean. The speaks to the limits of the radiative transfer model employed. It is not adequate when publishing to simply provide a link to the CERES description. You must indicate to the audience you understand what the “data” really is, and you must acknowledge its limitations. Using the CERES model data does not justify and validate, prove or disprove anything to do with GCMs. This is only meant as constructive criticism to assist in peer review. https://www.researchgate.net/publication/302591042_Evaluation_of_MODISCERES_downwelling_shortwave_and_longwave_radiation_data_over_global_tropical_oceans
Also noteworthy, it’s the accuracy assessment of CERES itself which may offer clues to the deficiencies of the radiative transfer equations used. This may be a more interesting line of investigation.
I posted my reponse before I read your comments. You are exactly correct. A reviewer would want an in depth analysis of why the radiation physics of CERES is different from the physics of the climate models. Both are models.
Thanks for a most interesting comment, JCM. I’ve compared a number of CERES results with observational data, and they are quite close.
Your link is most interesting, I hadn’t seen it before. Here is a view of their ground-testing of the CERES results in a location in the Pacific, versus the observations from the TAO buoy array. Qi is incident solar, Qa is incident longwave.
That is plenty accurate for the type of analysis I’m doing. Mean longwave is low by 0.2%, shortwave is low by 1.1% … not a problem. And for correlation analysis, you can see that the CERES data follows the actual observations very closely. The correlation between CERES and shortwave for the entire Pacific is 0.8, and between CERES and longwave is 0.9.
Finally, your study says:
“Compares well” works for me …
w.
Agreed. Mean values compare well. But, you seem to be drawing most conclusions from the tails. Any knowledgeable reviewer will veto the paper without an in depth discussion of the data on which your entire premise is based. Additionally, reliance on CERES and the associated accuracy assessments indicates that for a measured temperature the mean fluxes can be reliably estimated. In other words, measured OLR is simply a function of mean system temperature for each cell. Or, by the same virtue, measured downwelling longwave is simply a function of mean cell temperature. They are coupled, no cause and effect, one and the same. Measuring broadband longwave radiation in the sky from above or below reflects whatever temperature the atmospheric column is at. Additionally, any remotely sensed data contains significant spatial autocorrelation where the power density measured at the sensor spreads way outside the ground resolution cell. Neighbouring cells are not independent in broadband sensors – this is important when calculating (or more commonly mis-calculating) statistical significance of remote sensing results. Add this to all known CERES residuals to get at least a ball-park realistic significance of results. This autocorrelation might explain some of the structure of data depicted in Figure 6. Figure 6 is also a modelled parameter in CRE, thus CRE accuracy should also be discussed. . Thus, an in-depth discussion and acknowledgement of how the data is collected and processed is necessary for publication. They will use any of these issues mentioned and many more to deny publication.
JCM May 26, 2021 12:45 pm
Thanks again for a detailed and interesting comment, JCM.
Per your linked paper, the CERES data is more accurate at the upper tails (where I’m drawing my conclusions) than in the midranges.
Your linked paper provides just such a discussion. Not sure what more is needed.
Mmmm. That’s not what the CERES folks are doing.
What I am doing is investigating the nature of the relationship between SST and mean fluxes. It is NOT, as is generally assumed, linear. And it cannot be estimated by the Stefan-Boltzmann equation.
As to the question of cause and effect, in climate this is often quite sticky. The nearest method I know of to measure that is “Granger-causation”. A time-series variable “x” is said to “grangercause” a variable “y” if knowledge of x(1) to x(t-1) helps us to predict the value of y(t), where “t” is time.
There are three possible results of a Granger test:
And as you might imagine, the relationship between surface temperature and total downwelling surface radiation is result (3), each grangercauses the other.
Go figure.
True. The S-B equation is one measure of that. Not sure what that means.
The resolution of the CERES imagers is ~ 4 km x 5 km per pixel. Since these are then combined into 1° lat by 1° long gridcells (~ 80 km x 80 km at the equator), I fail to see how this is a problem.
There’s a good discussion of these issues here at the NASA CERES Site. My point is simple. As far as I know, the CERES data is far and away the best estimate we have of the actual energy fluxes. Given the stated accuracies, I see no reason to disqualify it for this type of analysis.
For example, the ocean temperature in Figure 3 (e) is a straight S-B temperature calculation from the CERES upwelling surface LW data. Note how similar the result is to the results using the Reynolds and the Berkeley Earth results in Figures 3 (a) and (b). And the similarity is even greater in Figure 5 because it uses two-decade averages rather than monthly results.
In addition, per your link, the errors are approximately symmetrically distributed. So they would wash out in the ~ 20-year averages shown in Figures 4-6. And some Monte Carlo experimentation shows that it makes little difference in the results shown in Figures 3 either.
As a result, I would argue strongly that the CERES results are absolutely adequate for the purpose. I would also agree with you that a detailed examination of the question along the lines of us discussing this here would be appropriate for a publication version of this blog post.
w.
Beware of using averages when examining continuous functions. Sin and cos waves can give similar averages over a period of time, but they are dramatically different depending on phase angles. Temps and other climate data are also continuous functions and averages can certainly mislead.
Similarly, statistical analysis of differing continuous function time series without examining their actual time relation can terribly mislead. Most climate scientists and their adherents seem to have no knowledge of this.
Thanks, Jim. To avoid this problem, I do a cross-correlation analysis of the data to see if there’s any lag. There is no lag between temperature and surface downwelling LW, so no problem.
w.
Now, where else but WUWT would you get these kinds of details? Fantasitc! 🙂
You said “Compares well” works for me …”
Unfortunately, having a decent amount of experience in scientific publication, what works for you is irrelevant. It is what works for the reviewers that matters if you wnat to get published. You have to show the reviewers, and you audience, that you are indeded an expert in the field you are presenting. I have had some replies to reviewer that where longer than my original paper, in order to satisfy their criticisms.
Thanks, Max. I’m posting up an analysis of data on the web. It is not, nor is it intended to be, a publication-ready document. As usual, I’m doing analyses that I have NEVER seen done. It is experimental in nature, and as all such first cut results are, it is subject to future discoveries and refinement.
So in fact, what works for me is relevant, and what a paper reviewer might think is what is irrelevant.
w.
“Second, the correlation near the poles is much smaller than that shown in all of the models.”
I think a likely reason for that is that near the poles, Reynolds OI says that the SST in the presence of sea ice is -1.8C (ice freezing point in sea water). I think Berkeley would be similar. So that will have zero correlation with anything. I’m not sure what models (TOS?) do, but it wouldn’t be hard to do better.
Sea ice near the South Pole?
…and increasing slightly over the last 40 years.
If they are showing SST at the South Pole, something is wrong.
Say what? See Figs 2 and 3. NONE of them are showing SST at the South Pole, so I have no idea what you’re referring to.
w.
I couldn’t see it either. I was responding to Curious George.
“But all of that gets ignored by the mainstream scientists. All of the results of the different climate models are given equal weight, the group is called an “ensemble”, and a simple average of all of their output is taken to be a valid result … say what?”
Who actually does that? Quotes? Exact words? If I look at KNMI, for example, there are plenty of results of ensembles. But they are for the same model. Mostly multi-model results are presented as spaghetti plots.
Nick Stokes May 26, 2021 11:35 am
Umm … lots of folks do that.
Source: The use of the multi-model ensemble in probabilistic climate projections
w.
As usual, Nick’s methodology is “fire, aim, ready”.
They talk of a multi-model ensemble. But what you said was
“a simple average of all of their output is taken to be a valid result”.
Well, here is what Tebaldi and Knutti say in that link
“There are obviously different ways to combine models. In many cases,Bayesian methods (e.g. Robertson et al. 2004) or weighted averages, where weights are determined by using the historical relationship between forecasts and observations (e.g. Krishnamurti et al. 2000), perform better than simple averages where each model is weighted equally. Intuitively, it makes perfect sense to trust, and thus weigh, the better models more. The difficulty, however, is in quantifying model skill and deriving model weights accordingly. Controversial results exist regarding the best way to combine model results, even in the case where skill or performance can be calculated by comparing model predictions to observations. The problem of constructing a weighted average for climate projection, where no verification is available, is discussed in §3.”
That isn’t saying that “a simple average of all of their output is taken to be a valid result”.
But the point is that averaging the results of different models is fundamentally improper. The results of physical model averaged with the results of a different physical model of the same system does not make the average more likely to represent reality. But all the climate ensemble models are exactly that. I don’t know of any other discipline where this is tolerated.
Taking the average of a wrong answer with the right answer guarantees the average will be wrong.
Nick writes “Mostly multi-model results are presented as spaghetti plots.”
And in those cases there is mostly an average given and that is what is used in discussion.
You can get better correlations with atmospheric dew point at the surface rather than SST. Dew point is calculated using atmospheric temperature and relative humidity.The surface water evaporates when the temperature exceeds the dew point. Evaporation is an endothermic process so the surface tends to cool to the dew point. The lighter water vapor rises and condenses in clouds at the dew point. There is not much difference in these dew points so there is very little heat transfer by radiation between the sea surface and the bottom of clouds. Heat is added to the air in clouds by the exothermic process of condensation. The water cycle is controlling the surface temperature and the temperature in clouds. It is also controlling the atmospheric concentration of CO2. For a detailed analysis see Climate Changes.
The link to Climate Changes is http:://www.retiredresearcher.wordpress.com
Fred, you can use the “Link” icon below the comment entry box to make it a live link like this: Climate Changes
w.
climate changes
Fred Haynie May 26, 2021 11:37 am
“Better correlations” with what?
Thanks,
w.
Substitute dewpoint for SST in what ever relationship you are studying.
I’d love to … but there are no global dewpoint datasets.
w.
Willis, how come it gets left to you non-tenured scientists to investigate easily observed natural phenomena, and their influence on regional and global climate behaviors?
Maybe we could ask Kevin Tremberth to investigate why “we can’t find the missing
heatcoolness, and it’s a travesty that we can’t”Great work as always, Willis! I’d like to emphasize your point at the end.
In order to maintain panic, aggregators like the IPCC and the USGCRP use the mean and spread of model families (i.e. CMIP5 or CMIP6), which clearly have systematic warm biases, with CMIP5 in the tropics and CMIP6 everywhere. So much for scientific progress.
But if the gummint was employing best scientific practices, as does the National Weather Service every day they would rely on models that worked the best given the current synoptic situation. This would mean we should be relying upon INM-CM4.8 and CM5 and pretty much discounting the rest, as well as eschewing RCP8.5 or its bastard spawn in the upcoming AR6.
That is the way it is done every day, and it gives us a pretty good weather forecast. But it’s not the way it is done every year for the climate forecast, which gives a pretty crummy forecast, one that hindcasts too warm and is unstable in the future, but always biased high.
All these modeller folks, including the self-canonized Ben Santer, who cut himself off from Lawrence Livermore AFTER his retirement date (!) know what they are doing, they know they are disregarding best scientific practice, and they don’t care. Heck, Ben will take his Senior Exec Service pension. If he were so serious about cutting his ties to LLNL he would refuse that, but he’s not exactly a model of Aristotelian virtue. And it is him and his ilk that are behind this business of including all the models–most of that stuff come out of LLNL.in the National Assessments.
Keep firing, Willis, you’re hitting home!
The Bastard Spawn of RCP8.5 has a sinister purpose. Like it’s father, it’s to be the honey pot in order to find significant (p<0.05) impacts to lure in a diverse array of other research disciplines on ecosystems and species. Getting more to ride the corrupt climate bus increases the climate congregants, like any church would want.
…If he were so serious about cutting his ties to LLNL he would refuse that, but he’s not exactly a model of Aristotelian virtue.
As a dear departed friend and long time government employee observed : ” in government, ultimately, inexorably and inevitably one’s morals get tied to one’s mortgage.”
Thanks Willis for another interesting informative piece, and thanks to the commentors too
Cheers
Mike
“I must confess that I am quite baffled by how mainstream climate scientists handle the whole subject of climate models.”
Willis, I am in the process of reading Chapter 4, Part I of Stephen Koonin’s book “Unsettled” on the very subject of climate models. It is apparent from what I have read so far that these mainstream climate scientists do NOT handle the subject very well. Koonin pretty much establishes in my mind (my own conclusion, not necessarily his) that it is impossible for any of these models to be able to establish a certainty of local phenomenon the closer to the surface they get with their grid boxes. And there is neither enough computer power or computer time to take into account all of the things that one would have to take into account (either with more or smaller grid boxes) to produce a worthwhile model of the atmosphere. The result is a dramatically incomplete picture of what is actually going on. Mainstream climate scientists are flying by the seat of their pants, and are not actually practicing what I regard to be “science.” It is much more like propaganda than science. Which is why I have always said this is not so much about climate as it is about power and control. The emperor wears no clothes.
Great job, Willis. You have presented your information in your usual understandable and very informative way.
Willis, I always find your presentations clear. This one is no exception.
Here’s the “but” part: I hope that we can state your problem a little more positively
As another commenter aptly noted, this feels like asking for a negative proof. I don’t think that was Bob Wentworth’s intent. Perhaps I misundertand you, or Bob?
Cheers.
Dk, see my above comment. There is a way to affirmatively show models do NOT incorporate emergent things like thunderstorms. Has to do with computational intractability and the CFL constraint.
Rud, Sorry if it seems as if I am asking for you to repeat yourself. I found this previous comment link. You are proposing then that your process/method/model criteria in the link would satisfy Willis’ problem statement?
Yes.
Okay. I’ve had a chance to reread the other comment and the Trouble post. (Also threw Amazon some cash for your e-book. Scanning, but I’ve about 4 hours a day when I can go more than a couple paragraphs).
My thought is that in order to make the model resolution criteria work as a proof, it needs to be shown that complex emergent behavior effects, such as cooling from thunderstorms, must be individually same as or smaller than the 5km resolution grid you mention, yet large and frequent (common?) enough in effect to significantly impact the entire system.
I’m going to have to shut off and come back later. Thanks.
Rud,
Quoting you in Trouble,
What I think that you are saying in this thread is that Willis’ problem statement is not really a problem. From your earlier comment post:
Bending my enfeebled brain to attempt to rephrse or restate:
Rather than addressing emergent phenomena as a class, Willis’ specific observation and theory about the cooling effects of thunderstorms cannot be included in GCMs because of 1) inadequacy of model resolution to capture cooling effect of thunderstorms and 2) the corresponding use of parameterization.
Is that representation accurate?
Rud,
Addendum: quoting you in Blowing Smoke, essay Humidity is still Wet, on MIT Lindzen, 2001
Offered more as amplification. Same question: have I restated your position accurately in my previous comment?
BTW here is “The Trouble With Climate Models” link
Willis,
Just caught your other post to comments here. I suppose that should really answer what I was asking. Missed it.
In retrospect, I should have probably asked something more along the lines of “How can your hypothesis be falsified?” As enthusiastic as some replies are here, I haven’t caught anyone reasonably trying to do that.
Good question, dk_. I’ll have to give that some thought.
w.
Willis,
I attempt, in non-scientific language:
Can it be shown that thunderstorms are NOT a net cooling phenomena?
alternately
Can it be shown that thunderstorms are a net warming phenomena?
alternately
Can it be shown that thunderstorms have no effective atmospheric thermal gain or loss?
.
A parallel question is: has the increase in Downwelling Longwave radiation (DLR) over past decades, been sufficient to account for the observed increase in SST? I have not seen any evidence that it has.
But if DLR has not been increasing to a significant degree, then CO2 cannot be responsible for global warming. (This is the missing Tropical Tropospheric Hotspot enigma or the missing TTH.). There are of course alternatives to CO2-DLR invoked warming (the missing TTH), and these might include:
Oceanic cycles (AMO and PDO)
Polar ice-sheet albedo, modulated by Chinese industrial soot.
Cosmic ray-induced atmospheric albedo.
Direct data manipulation.
Ralph
Willis,
Figure 5 shows that measured total downwelling radiation has to be below 300 W/m^2 for the SST to get to 0 C but the climate models tightly cluster around 350 W/m^2 – a *huge* difference. This huge difference persists to warmer SSTs. The fact that the difference is huge and tightly clustered strongly suggests that the models all have a common flaw. I’ve heard, but not confirmed, that most models are based on the same ocean circulation/mixing model. Could this be why the models are so wrong at low to medium SSTs?
Liberal application of renewable brown matter will fill in the missing links.
That also sounds like the way it’s done with solar cycle prediction by committee.
Quotation: “What’s improperly but inalterably called “greenhouse radiation” starts out as energy absorbed by the atmosphere—absorbed solar energy, sensible and latent heat moved from the surface to the atmosphere, and radiation from the surface of the earth that is absorbed by the gases, including greenhouse gases (GHGs) in the atmosphere—water vapor, CO2, methane, and other minor gases. Once the radiation and the other energy is absorbed, it warms the atmosphere. And since anything that can absorb radiation also can emit radiation, those greenhouse gases radiate the absorbed solar, sensible, latent, and radiated heat in all directions. This downwelling radiation resulting from the atmosphere is what is known as “greenhouse radiation”.”
This all is true. There is one expression in the last sentence “called greenhouse radiation” or reradiation from the atmosphere, which needs clarification. Firstly, it includes absorbed solar radiation of about 75 W/m2 which together with the solar radiation to the surface 165 W/m2 is the total net solar energy of 240 W/m2 to the Earth, and therefore reradiation is not totally due to the GH effect. Therefore, it is also not a correct measure of the GH effect. The GH effect is the sum of LW absorption by GH gases and clouds 155 W/m2, latent heat 91 W/m2, and sensible heat 24 W/m2, totaling 270 W/m2. Secondly, the IPCC science and climate establishment define that only the absorption by GH gases and clouds 155 W/m2 is the measure of the GH effect.
My conclusion is that Willis has the same definition of the GH effect, which I have specified in my scientific publication https://doi.org/10.9734/psij/2019/v23i230149.
I am pleased to notice that WUWT has published this blog story of Willis because Dr. Spencer raised a strawman argument against my blog story claiming that I have said that the Earth’s energy balance violates physical laws. I never did so but I did claim that the GH effect definition of the IPCC violates the physical laws: How can 155 W/m2 absorbed by the atmosphere reradiate 345 W/m2 to the surface?
Since only a few people have ever read the GH effect definition of the IPCC, I write it here:” “The longwave radiation (LWR, also referred to as infrared radiation) emitted from the Earth’s surface is largely absorbed by certain atmospheric constituents – (greenhouse gases and clouds) – which themselves emit LWR into all directions. The downward directed component of this LWR adds heat to the lower layers of the atmosphere and to the Earth’s surface (greenhouse effect).” Does it matter? Yes, it does. By this trick, the contribution of CO2 in the GH effect has been calculated to be about 19 %, when it is actually only 7.4% or 2.5 C.
Otherwise, the evidence of radiation and surface temperature is convincing and there is also this surprise of tropical oceans.
“All of the results of the different climate models are given equal weight, the group is called an “ensemble”, and a simple average of all of their output is taken to be a valid result … say what?”
I have never understood this either. I can’t think of any other area of life where we take failing models and average their output with successful ones, and then proclaim the result to be better than just using the good ones.
I’ve never even seen anyone make any effort to justify what seems to be totally irrational behaviour.
Where money, power or prestige are involved, there is no irrational behavior.
You post: “And if the correlation is negative, when the temperature goes up, the radiation actually goes down.”
…
You have cause and effect reversed. Should be when the radiation goes down, (then) the temperature goes up.
As used in the graphs:
Downwelling shortwave—measured with a pyranometer, essentially a thermopile underneath a transparent dome, mounted horizontally giving a nearly 180-degree field-of-view. Wavelength response ranges are ~0.3um to ~3-4um, depending on the dome material, which differ among manufacturers and models. Total uncertainty of measured irradiance is at best +/-2 to 3% with good quality instruments and calibration, and lesser quality instruments +/-5 to 6% (or worse). Output signal voltages from the thermopiles is small, less than 100mV, so voltage measurement instrumentation is also critical.
Downwelling longwave—measured with a pyrgeometer; similar to a pyranometer except the dome material is silicon (Si). The bandgap of Si is ~1.2um, so the dome is transparent to wavelengths longer than the bandgap. With a multilayer dielectric coating, the dome’s short-wavelength transmittance cut-on is changed from 1.2um to ~4um. A temperature sensor for the instrument is needed to calculate the net IR irradiance. The transmittance curve is not flat over 4-50um, see https://en.wikipedia.org/wiki/Pyrgeometer
Non-obvious points:
1) The spectral response of a pyranometer includes strong H2O absorption bands at 0.84, 1.13, 1.4, 1.87, 2.75, and 3.2um. Most of these are quite broad. It will respond to the weak CO2 bands at 1.44, 1.58, 1.6, 2.0, and 2.7um
2) A pyrgeometer responds to the H2O band at 6um, and the strong CO2 band at 15um; there another weak band at 4.28um.
3) Dividing solar radiation in “SW” and “LW” is simplistic at best and likely misleading given all the overlaps.
4) Between 4 and 50um, the extraterrestrial (AM0) irradiance at the top of the atmosphere ranges from ~8 W/m2 down to 0.0004 W/m2. Very little of this can reach the surface.
5) The NOAA SURFRAD network has just 7 stations with a careful rotating calibration program, all in the continental US.
6) TMK there is no such program with the correct instrumentation at oceanic locations worldwide.
How is it possible that Reynolds and CERES ocean data exist? These aren’t something you can get with satellites; they must be models of some sort.
One other point, the total uncertainty of a pyrgeometer is probably on the order of +/-10%; they can’t be calibrated in sunlight as pyranometers are, I’m not sure what a calibration source for 4-50um would be. The WMO documents may have better information.
For some reason, I have considered a pyrgeometer the result of a middle school science project.
The silicon dome seems ingenious but I’d have to wonder about the long term durability of the dielectric coating.
Great in a vacuum. How do they keep dust and water off it? Dust on the surface would radiate black body-ish radiation based on surrounding air temperature. It’s better than a wet finger, I suppose.
Probably not the right post to discuss the merits of this equipment.
Monte, the accuracy was greatly improved in 1995. I find:
SOURCE
I can’t find any info on previous accuracy. However, average downwelling longwave is ~340 W/m2, so ± 2 W/m2 is ± 0.6% …
w.
Willis: after I posted this (very late) it occurred to me the calibration source had to be a resistive heater of some kind. What they describe here seems like a national laboratory-level effort, typical commercial instruments have only only T sensor TMK. Do you have a link for this abstract?
I need to see what the WMO has on pyrgeometers, their pyranometer info is very thorough.
Click where it says “SOURCE” in my link above.
w.
Thnx.
PMOD/WRC (Davos) has quite a good article about pyrgeometers:
https://www.pmodwrc.ch/en/world-radiation-center-2/irs/wisg/
The WMO document is #120:
https://library.wmo.int/opac/index.php?lvl=notice_display&id=18511
Similar to the terrestrial cavity radiometers group that represent the World Radiometric Reference, calibrations are done by comparison against the PMOD reference instruments (the WISG). Just like the cavities, the metrologists are arguing about an offset between the Davos instruments and SI radiometry.
(The ±2 W/m2 value is probably the unexpanded uncertainty, x2 = 4 W/m2, which is 1.2% at 340 W/m2.)
Knowing how rough pyranometer uncertainties are, it is surprising to me they have managed to get uncertainties this low. I’ll have to read the calibration procedure to see how they account for non-flat spectral response.
A pyrgeometer measures the net radiaton, not the downwelling which is calulated. The manual for CGR4 Kipp & Zonen says that net radiation is 0 to -5 W/m2 at cloudy overcast sky and -90 to -130 W/m2 at clear sky.
Regarding calibration see: Pyrgeometer Calibrations for the Atmospheric Radiation Measurement Program: Updated Approach ; T. Stoffel and I. Reda. (sorry, did not work to paste the link)
Yes, the radiation from the air exist but the re-absorption of that radiation by the ground does not , If the radiated energy was reabsorbed and added up to itself and increase its own temperature that way as it shows in that energy balance model you would have a run away out of control ever increasing energy amplifier with each cycle reabsorbing more and re-emitting more and more energy ,resulting in the planet would explode like a supernova in a very short order.
People constructing these models should go back to making children’s coloring books and stop bastardizing the laws of fizzix.
DELETED!!!!
Back radiation should be stuffed into the junk science folder and set on fire. That’s the only way it would add any heat.
Disagree on physics, despite agreeing colder back radiation cannot warm the surface, as you correctly surmise. Heat flows from warm to cold, unless we deny the laws of thermodynamics.
My disagreement reason is a fundamental GHE misunderstanding. The radiative GHE is NOT a warming—warming comes only from the Sun SLR. It is an absence of offsetting OLR cooling. Backscatter OLR is just one of the ways this radiative cooling absence is observed, because it did not go to space(which cools), it went down to ground (which does not).
” It is an absence of offsetting OLR cooling. Backscatter OLR is just one of the ways this radiative cooling absence is observed, because it did not go to space(which cools), it went down to ground (which does not).”
Question. What governs the rate of emissivity of the Earths surface?
Is it it’s temperature?
I didn’t refer to any physics. I might have implied sophistry, though.
I don’t yet fully understand the concept. I’m probably thick. If back radiation from the atmosphere is absorbed, it must heat the surface (or slow down the cooling) – whatever. Leaving it warmer than it otherwise would be. Ok, but surely that would mean that the radiation from the surface must must keep up with what it is receiving. ( I’m sure I read Einstein said energy in = energy out) Which means that the increased radiation from the surface would add again to that being received by GHGs which in turn must keep up with what they are receiving and on and on and on. Where does the warming (OR SLOWING OF COOLING) part come in?
Focus on the atmosphere (including clouds), not the Earth’s surface: Energy in = Sun (SW) + from surface (LW + Latent + Sensible); Energy out = reflected Sun (SW) + emitted to space at TOA (LW) + down to surface (LW). Within the accuracy of existing instruments, it has all been measured.
Why are you using historical model run and not data from the Ceres period?
“I will delete any comments that claim that downwelling radiation from the atmosphere doesn’t exist or that it doesn’t leave the earth warmer than in its absence”
LOL!
Guess then you will want to delete this short little article..
(SNIPPED the link) SUNMOD
Willis wants to delete certain posts because he can’t provide a shred of evidence that downwelling radiation from the atmosphere is a real forcing. If he could he would gleefully devote a whole article to the subject. Which he hasn’t.
Well, the Moon Has an absence of downwelling radiation from an atmosphere, and it gets up to 260 degrees F on the sunny side. But I guess Willis is talking about average temperatures and not actual.
Yes it does, interestingly. That is despite it should only get to ~382K in theory, as (1376*(1-0.12) / 5.67e-8) ^0.25 = 382. I mean if we assume an albedo of 0.12. So does the moon have a GHE too?
If only there was a ressource sorting out all these things.. 😉
(Snipped the link) SUNMOD
This is exactly why this policy was made a while back, to stop derailing threads with the no downwelling radiation claims, it become so disruptive that this policy was made.
POLICY:
Maybe you should read before you judge. The evidence on my site so much more sophisticated than anything you ever presented here, or “heard” of in some way. At no point I suggest “back radiation” would not exist, of course it does. And I have to ask to not be connected in any regard to non sense like “Slaying the Sky Dragon” or similar incompetence.
Mr. Schaffer, Is there some part of
that is unclear to you?
We have had literally dozens of posts here on WUWT about downwelling radiation. And there are dozens of other sites with such posts.
Please take your claims about the “evidence on your site” to one of those posts.
w.
I do support Willis in this matter. In the post of Dr. Spencer in which he claimed that my GH effect definition is bad skeptical science, there were about 600 comments but only less than 10 comments about the GH effect definition of mine and the IPCC, which was the subject. It was just a battlefield if reradiation exists or not. If you allow, this goes on and on. I have experienced this many times. The final comment may be like this: the reradiation cannot be measured, it is just a hoax of climate establishment and the CERES radiation results should not be used since they are products of NASA.
DELETED—Take it elsewhere! This is not the place.
w.
DELETED—There’s a new post where you can argue this to your heart’s content. Take it there.
w.
DELETED—I made a new post specifically for you. Take it there.
w.
The great physicists of the 20th century were also “misguided” I suppose.
http://web.ihep.su/dbserv/compas/src/einstein17/eng.pdf
How so?
Hoyt, 260°F ≈ 400K.
E. Schaffer, in theory, the max should be
(solmax * (1-.012)/(epsilon * 5.67E-8))^.25
Because of the eccentricity of the earth’s orbit, the maximum solar input “solmax” = 1,406 W/m2. Epsilon, the average emissivity of the lunar surface, is 0.9. This makes the theoretical maximum temperature = 407K, above the number you give.
Finally, the Diviner lunar mission measured the moon’s surface temperature. It gave a maximum temperature of 396 K, slightly further below the 407K theoretical max.
So, sorry to disappoint you both, but there’s no contradiction at all.
w.
Sorry for having to correct again, as I usually have to, but you seem unable even to apply your own formula, which is wrong anyhow. It should be..
(solmax * (1-.012)/(epsilon / 5.67e-8))^.25
or more reasonably..
(solmax * (absorptivity / emissivity) / 5-67e-8) ^0.25
So you DIVIDE by the SB constant, NOT multiply!
And if we do so, and use your parameters, we get..
(1406 * ((1 – 0.12) / 0.9) / 5-67e-8) ^0.25 = 394.6K
407K nowhere in sight.
I mean seriously, what is that non sense you are constantly posting all about? Do you want to show off how incompetent you are? Is it a joke? You cannot be serious..
And this idiocy which is all over the place is exactly why I had to start my own site. So that finally some competence enters the discussion.
I’m sorry, E., but it seems that you fail to realize that
a/b/c = a / (b*c).
Check out the parentheses in my formula, and compare it to your formula. And while you’re at it, dial back on the ugly snark.
However, you are right that my formula contains an error … just not the error you falsely claimed and wrongly abused me about. The error was, I used 0.012 as the albedo, not 0.12. Typos rule …
In any case, there is STILL no contradiction, because of the inexactness of the figures. If the emissivity of the moon is 0.89 instead of 0.9, a change of about 1%, the max temp becomes 396, the same as the Diviner value.
So the value given by the S-B equation is correct, not wrong as you claimed.
Here’s some free advice, E., take it for what it’s worth. If you want to be taken seriously you need to stop raving about “idiocy” and spewing insults of “incompetence”. You couldn’t even diagnose the error in my work, and you made a totally false claim about the math. All you’re doing is destroying your own reputation.
Yes, I made an error, a typo in my formula of 0.012 in place of 0.12. Not my first error due to a typo, won’t be my last. And guess what?
You didn’t find the error. I did.
You, on the other hand, displayed an ignorance of the basic rules of math, wrongly identified the error, and on that basis you foolishly claimed that using the Stefan-Boltzmann equation was wrong, and roundly abused me and called me an idiot … not a good look on you.
w.
DELETED. Is there some part of “discuss it elsewhere” that is too complex for you to understand?
You are welcome to discuss my and your calculations for the S-B temperature of the moon, and in fact, we agree on the value. But leave the rest out.
w.
Actually, without order of preference established, one is free to use whatever rules one wishes to evaluate the expression:
a/b/c
The traditional way is to use the PEMDAS rule, but that is not a hard and fast rule.
PEMDAS is:
Parenthesis
Exponents
Multiply (left to right)
Divide (left to right)
Add (left to right)
Subtract (left to right)
Using this, the expression would be evaluated as
( (a) ÷ (b) ) ÷ (c) –> a ÷ (b*c)
It is also just as correct to evaluate it as:
(a) ÷ ( (b ÷ c) ) or (a * c) ÷ (b)
I never let students leave out mathematical punctuation as it is then open to interpretation. It’s like leaving comma’s and periods out of prose.
Jim, that’s not true in the slightest. EVERY computer language I know of, and I speak about ten of them, uses the rules you outline above. So it is NOT
It’s not correct at all to say that.
And no, it’s only in your head that it is “open to interpretation”. Type the expression into anything from Excel to Fortran and you’ll get the same answer. Here’s the calculation in R:
The same is true in Excel, C, COBOL, Mathematica, S, Logo, Lisp, Forth, C++, Pascal, Python, Basic, and any other computer language you might name.
w.
PS. the only one who knows what Willis is talking about is not even himself 😉
This deleting threat reminds me “The Emperor’s New Clothes” case , as if you can only discuss the colors if the Emperor’s Clothes but you are not allowed to simply point out he is naked
Eben, stop your childish whining about the krool science police. You knew what the rules were when you chimed in. Don’t like it? Sorry, not the place to discuss your claims. I’m not stopping you from making claims about the Emperor’s purported nudity. I’m just insisting that you do so elsewhere, as it distracts from this discussion.
w.
DELETED—Stuff it where solar panels don’t work.
w.
DELETED—I put up a new post, you can argue this there.
w.
LOL
You trolls are unhappy you are not invited to disrupt the conversation among adults. But you got your sub-thread so go chew your bubblegum with the other children up the street.
Typo Willis (you hate typos!) 🙂
“And to close out this part of the discussion, Figure 5 below shows the data in Figure 5, with the observational data from Figure 4 overlaid on the top.”
It should say “Figure 6 below shows the data in Figure 5, with the observational data from Figure 4 overlaid on the top.“
also this one:
“I would also use things like Figure 5 above to work to understand why all of the models that I tested are in one tight bunch,”
You mean Figure 6
Both fixed, thanks,
w.
“Clearly, as shown in Figures 2 a-e above, certain models are fairly close to at least some aspects of reality, while others are very far from reality.”
There is at least one thing that all the models get wrong-the hot spot.
R McKitrick, J Christy – Earth and Space Science, 2018
Willis,
On models,I have a personal friend who is a Professor of Chemical Engineering.
I use him as a sounding board for my ideas on climate science and he corrects me when I am off track.
Like you he has done modelling for more than 30 years.
He reminds me that the well known aphorism is true-
“All models are wrong,but some models are useful.”
Willis, your words:
“This “greenhouse radiation”, the downwelling radiation from the atmosphere, leaves the surface warmer than it would be if there were no greenhouse gases—if there were no GHGs, the upwelling surface radiation would go straight to space and be lost. But instead, the upwelling surface radiation is absorbed by the greenhouse gases in the atmosphere about half of it is returned to the surface.”
Take what you write as correct for the first “cycle”. For, after one pass through this mechanism where 1/2 goes to space, successively 1/4 then 1/8 then 1/16 …. goes to space in a series that sums to unity, 1. So the surface cools in rhythm with losses to space that sum to unity. Where is the warming, except in a delay? Are you reliant on a delay? Geoff S
You’re making the false assumption that the multiplier in each “cycle” is 1/2. It’s not. For a more general treatment of this issue, see my essay Atmospheric Energy Recycling.
Thanks, Bob. Geoff, for another look complete with the math, see my post entitled “The Steel Greenhouse“.
w.
Willis,
Memory lane trip back to 2009 and Tinkertoy. (Let me not add to the volume of comment that you caused then). There is one problem, of why a GHG like CO2 is much different to any other gas, apart from how quickly key processes happen. An earth with no GHG should still reach a final temperature over geologic time and not oscillate aimlessly, but as yet I have not decided which of the possible estimates seems best. Until then, I’ll drop off this discussion. Geoff S
I doubt we will ever come across a planet without any radiative gasses in it’s atmosphere, but that does have an atmosphere, and see what it is up to.
Not soon enough for you or me, though, eh Geoff?
I must admit I have scratched the old noodle a time or two over this question.
But I think we can think of a way to definitively say what the case is/would be, and show our work too.
Still, Luna is a body in the solar system with no radiative gases in admittedly a nearly non-existent atmosphere. You can argue that Earth’s moon isn’t a planet, but then I will bring up Mercury (atmosphere of atomic Oxygen, Sodium, Magnesium and Hydrogen plus others). You can argue that it doesn’t have a significant atmosphere, but then, sorry, you’ll have to add “significant” to your objection, and then we’ll be arguing about trivia.
You could argue that we’ve never been to Mercury or Luna, but then we’d have, for each, an entirely different semantic argument.
Can we show that the formula does not apply to the pitiful atmospheres of Mercury or Luna (or half a dozen or so other small bodies in the solar system)? I can’t do the math reliably. Can you?
dk_, I have no clue what you are claiming about the moon. The S-B equation says it should reach about 396°F. The Diviner moon probe measured the temperature and found it to be about 396°F …
… and?
w.
WIllis,
I should have been more specific. Aiming at Nicholas
Not because I thought it would do any good, but because I think references to real planetary bodies without GHG have been ignored in the past, even in this thread. Wasn’t aimed in your direction, and I shouldn’t have posted. I’ll be fine if you wish to delete it, since it isn’t at all constructive and I do quite regret it.
Thanks, dk_. I didn’t object to your comment, I just didn’t understand it.
w.
Willis,
Positivism is positively hard. Should have been a Yogi Berra-ism. I’m finding it so.
BW,
“Yet, the purpose of the diagram is public education, not rigorous modeling.” Geoff S
And, the point of your comment is?
Bob W,
I gave a simplified example of cycles reducing by 1/2 each pass. You replied that it was not 1/2, reference provided. Thank you for the reference. I lifted a line from it in my reply as I wished to avoid the bunfight that Willis wanted to avoid and ended it there. Geoff S
OK, I am going to go against every instinct to avoid pain that I have in my soul, and dive in here. Let me know if this helps anyone, please:
I think this is a semantic problem only, or else a problem in communicating that the little cartoons are only showing the net result.
What really happens is, the Sun rises in the morning (after a dark and stormy night…), and for a while there is more incoming than outgoing energy to and from the ground, and so the surface heats up.
The ground started the day with some heat left over from all the previous days, so it is not starting or ending with zero energy.
It keeps radiating more strongly as long as it (the ground) is getting warmer, and at some point in mid afternoon, the outgoing flux is first exactly equal to the incoming, and the ground stops warming, and then because the Sun is getting lower in the sky, and the ground is initially still about the same temp, for the rest of the day the ground is cooling as outgoing flux exceeds incoming.
At Sunset, incoming stops, and the ground continues to cool, until a temperature is reached where the ground is in equilibrium with the air temp and the sky temp. (and conduction of heat from below…which is slow)
Sidenotes:
We have neglected throughout so far, and it is neglected in many of the diagrams, that there is also energy transfer from the ground to the air via conduction the whole time.
-If the air is warmer than the ground, the air is warming the ground by conduction by some amount or rate.
-When the ground is warmer than the air, the ground is warming the air by some amount or rate.
Since air is far less dense and has far less thermal mass than solid ground, heat transfer from air to ground proceeds far more slowly when the air is warmer. This helps explain, for example, how and why frost can sit on the ground when the air temp is 38°: The ground is radiating more quickly than air can provide energy to melt the ice crystals. Note this only happens in clear skies and light to absent wind. Any significant wind lets the air deliver more energy to the ground, and any clouds or even haze, slows outgoing radiation below the amount needed to get frost at 38°. So this explanation satisfies observations of this common occurrence, as well as textbook descriptions of when frost can form. I myself, having been born and raised in the downtown of a big city, never saw this occurring until I was in college and bought some land way out in what city folks call “the country”. I had previously been told this is true in classes in such subjects as physical geography and meteorology, and can happily report that I live far enough away from cities that I see it all the time, starting from my plant nursery days. Imagine my surprise…ice on the ground and cars and grass in tiny crystals when it is way above freezing. But only if there is no wind and the dew point is low and there are no clouds. Hot damn, I have seen it with me own eyes, and so can you. But you have to go outside on cold nights with thermometers and look for it. Not to see the frost, but to know it is actually well above freezing even an inch above the frost. And you have to do it many times to confirm that even a mild breeze of 4mph or so, or any clouds, will disallow frost at these temps (32°-38°F)
OK, end of side note and back to discussion of my plain language description of what the hell exactly is going on with all of this incredibly controversial and utterly unproductive morass...
If there was no incoming back radiation at night, then the Earth would be almost like the dark side of the moon, with the night time temp FALLING Falling falling …down to extremely low temps limited only by how fast heat could conduct up through the ground or conduct back to the dense surface from the thin air…but the air would be cooling by contact with the cold cold cold of space ground.
As we can see from our side notes, we know that conduction up from the ground or to the surface from the thin air, is not even sufficient to melt tiny crystals of ice, or keep them from forming, even when the ground is over 70° just an inch or two down, and the air is well above freezing.
If there were no such thing as back radiation, why would not the ground keep cooling all night long?
We know air radiates, because everything does. We know moist air cools more slowly than dry air. Why does it? Because all that moisture is radiating, all the time, and at night it becomes a significant influence on how fast and how much the ground cools.
We know the ground cools faster than the air after sunset, because it can be observed that first dew and then frost, if it is cold enough, will form on ground surface long before the air is at the dew point (in the case of dew) or at the freezing point, (in the case of frost).
On Summer evenings, anyone can go to anyplace with grass and see the dew form, and do so before the Sun is even all the way set in some cases.
And we know the air near the ground cools by it’s own radiation and also from contact with the more rapidly cooling ground surfaces. How do we know this?
Because we can put thermometers outside the windows of tall buildings for one thing, or we can look at soundings from radiosonde balloons for another thing. And when we do that we see that the air is cooling off at all levels, but fastest at the ground, and we can infer how fast heat can conduct through air and know the entire air column could not be cooling by conduction from the ground. Air conducts poorly. Anyone can test this in any kitchen. Or look it up.
So what about this endless feedback loop that some people are saying is a logical result if back radiation is a thing, and we follow the reasoning to it’s logical conclusion?
Because they are neglecting that all along, the temp and the amount of radiation emitted from the ground has been a product of all of the sources of incoming energy it has been receiving all along. Even before they started thinking about it, and even from before they heard about any of this!
So there is no runaway feedback loop.
So, how do we know for sure for sure that energy back from the air (the sky)is for sure for sure a real thing?
What if the logical chain of reasoning I have laid out is unconvincing, and you think my observations and inferences about rates of conduction are irrelevant?
What about a cold object not being able to warm a warm object?
This one is easy: The mean free path length of a photon in the air anyplace close to the ground is very short. Photons are packets of energy. For a packet of energy to go from the ground up to space, or halfway there and then back again, it must be absorbed and re-emitted a whole skintillion number of times. For one thing very few of them are going straight up and then straight down…like zero of them do that. So there is a mean free path length.
Another thing to know about energy levels is, at any given point in time, many molecules are moving far slower and are at far lower energy than the average. And there are so many molecules that a photon can find one of these, if it has to.
Condensed matter is different though…it is not limited to a small number discrete energy levels from which it can radiate or emit.
What about the idea we have seen mentioned that photons are physically incapable of being emitted towards a cooler object by some known-only-to-a-few-select-internet-bloggers rule of physics?
Or that they can, but will then be reflected if a cooler object than the emitter is the target?
Is it really true that no photons can travel from an object or a gas molecule and impinge upon a warmer object?
This would certainly be very significant if true, but it is even vaguely plausible?
If it was true, would it not have to be strictly true in al and every single last instance imaginable?
After all, if it was not, it aint much of a physical law, eh?
Would it not mean anything colder than our eyeball would be invisible?
Would it not be prominently mentioned in discussions and equations describing reflectance and refraction?
And if photons emitted from the surface can never come back this way via emission from CO2, but only and inevitably go outwards, ever outwards, what physical mechanism in the molecules is making sure this is so? And could we not exploit this to make devices that were perpetual motion machines?
The laws of physics were arrived at by men, using experimentation and observations, not chiseled in stone and passed down from on high.
If there is any physics that has ever described any of these ideas, why does no one tell us which physicist did the experiments and observations and when they did it?
I was baffled by this for a long time. Years.
But a few years ago, I started studying this subject.
After all, students get PhD’s in physics in less time when they are just kids.
Whether photons are absorbed and re-emitted, or just scattered, is irrelevant to an observer.
When we look at gas clouds in space, we can see discrete emission lines. We can see absorption lines in light that passes through them.
If a physical law is found to be violated even once, it is not a physical law.
There are oodles of examples of radiation from cooler objects impinging on and being absorbed by warmer objects.
There are plenty of examples in which these ideas can be shown to not hold up.
Therefore they are false.
That is how laws of physics work, and how we know which ideas are physical laws.
Here is proof obtained via an entirely unrelated field of inquiry:
The evolution of the theoretical bolometric albedo in close binary systems – NASA/ADS (harvard.edu)
The Proximity Effects in Close Binary Systems. II. The Bolometric Reflection Effect for Stars with Deep Convective Envelopes – NASA/ADS (harvard.edu)
1985Ap&SS.113..349V (harvard.edu)
Welp, I think that covers everything.
I would love to know if this made any sense to anyone?
By the way, what those links show, for anyone who does not want to read them, and no one should have to read some long thing when the person presenting it can just say what the thing says, what those papers are, are studies of stars in close binary orbit, and how they shine on each other, and warm each other up.
One is hot, and the other is…um… hot… but less hot than the first one, and they warm each other up(!).
It has been known for a long time, and has recently been quantified.
I got plenty more if anyone does not believe it.
Thanks your welcome.
What was that thing about, if you cannot explain something to a seven year old, is is probably not true?
Mr. E,
I suppose this comment may be contrary to your stated guideline, so if you need to delete it, I understand.
Willis,
Re your figure 6, I am also concenrned about model/observation differences along your X-axis. The models differ from obs by 50 units, which is significant by any measure. Thus, the slope of the fitted curves is so different that at least one set has to be wrong. Why, I do not know, but I would like a modeller to explain. Geoff S.
Willis, your hypothesis is garbage. If thunderstorms regulate climate, how come they did not block the MWP? If thunderstorms regulate climate, how come they did not block the LIA? If thunderstorms regulate climate how come they did not stop the last glaciation and snowball Earth?
The simple answer is they don’t and you are full of feces.
How in God’s name are you going to give data on the prevalence of thunderstorms during the Roman Warming Period?
Jay, if you were a decent human being and not someone whose go-to theme is ugly personal attacks, I’d answer you.
But you’re not. So I’m gonna pass. There is a good answer to your question. I don’t care in the slightest if you know what the answer is.
Come back when you’ve learned the bare modicum of public discussion and you are willing to apologize for your foul mouth, and we can talk about it.
Until then, as they say, “talk to the hand, son, ’cause the face ain’t listening …”
w.
Obviously Mr Eschenbach, you don’t understand the difference between a thunderstorm which is a WEATHER phenomena and something that has CLIMATIC effects. Too bad you can’t handle a simple refutation of your garbage hypothesis. Once you realize how worthless your hypothesis is, you’ll understand why you can’t get a decent journal to publish it.
(Snipped)
(You are done here in the thread with your unwanted behavior, you are warned to not do it again )
SUNMOD
Good decision mods. You defeat your own argument when you become offensive. Civility costs nothing
The blue areas on the global plots are the blindspot for everyone who believes.
The global oceans have upper and lower temperature limits. Cannot be warmer than 305K and average peak is limited to 303K by the process of lateral convergence. Cannot be colder than 271K. Who can make a stab at what the global average temperature will be? Stand up and take a bow those who arrive at 287K.
The real question is – Did those standing need a “Greenhouse Effect” to arrive at that somewhat obvious result.
The lower limit of 271K is easy to understand – there is no ocean water surface cooler than 271K.
The upper limit a bit more challenging but just as precise as sea ice forming. Only it is atmospheric ice that forms above the level of free convection for the upper limit. Easy to demonstrate that the open ocean surface temperature CANNOT exceed 305K while the surface pressure sits around 1010mb. It is the simple atmospheric physics that climate models try to parameterise with the inevitable outcome being the huge blind spot. The 210W/sq.m powered heat engine that regularly catapults massive amounts of water above the LFC to as high as 14km.
RickWill May 26, 2021 7:53 pm
The Persian Gulf, the Red Sea, and the Sea of Cortez are all warmer than 305K. CERES puts the max at 215K, Reynolds OI SST says 308K, Berkeley Earth says 309K.
If it’s “easy to demonstrate that the open ocean surface temperature CANNOT exceed 305K, let me invite you to do so, and in the process explain how your theory allows those three bodies of water to exceed 305K.
Global ocean temperature is ~ 290K, not 287K, and global land temperature is ~ 282K … not sure how that fits with your theory.
Best regards,
w.
Read these first then come back to me:
Part 1 An analysis of the temperature of tropical ocean warm pools and the temperature limiting processes
Part 2 Discusses the mechanism of deep convection concluding with the persistency of clouds over ocean warm pools.
https://wattsupwiththat.com/2021/05/25/ocean-surface-temperature-limit-part-3/
I have it from NASA that the global average temperature is a “cozy” 14C:
At least that’s what the kids are being told>
https://climatekids.nasa.gov/greenhouse-effect/
Richard,
Please do not take my question the wrong way, I am very interested in this.
But we know the GMST has varied by quite a bit over time, and yet these limits seem pretty hard and fast, especially the one at the freezing point of sea water.
And I am not necessarily speaking only of the MWP, LIA, Roman Warm Period, etc.
But the glacials and interglacials, and all the variations seen in the paleo reconstructions of temp?
I am also wondering about a simple average of these two numbers…would not the amount of water at or near each of the extremes, matter?
What changes when the Earth warms and cools?
Nicholas
The hard limit changes with air pressure. I made a stab at the Cretaceous period having an air pressure of 1100mb. The Table 1 for that conditions is compared to 1010mb.
A big change over time is the distribution of water. Places like Drake’s Passage and Bering Strait are important points for ocean heat transport. Drake’s passage has not been open for all that long in geological history. The Bering Strait shoals during glaciation.
Earth orbit is a significant factor in the distribution of heat input; eccentricity and obligatory are not static.
Ice mountains will cause low surface temperatures in the vicinity wherever they occur.
Then there are cosmic influences that no one really understand because the entire focus is on the evil CO2.
The current 14C, or whatever it is, is the result of the current distribution of surface water. It is a nice co-incidence it sits in the middle of the upper and lower limits. It is a reasonable number based on physics rather than some improperly modelled rubbish based on CO2 being the control knob.
I still challenge the notion of a global average temperature – it is a meaningless number. The aim of the three part series was to slay the “Greenhouse Effect” as have any valid scientific basis.
The missing attachment.
Willis
I have a question about that first figure of
“ Here’s a typical 24-hour measurement of the downwelling infrared (longwave) “greenhouse radiation” from one of the SURFRAD stations.”
It looks like as if you were to run that out to 48 hours there would have to be a sudden saw tooth drop from the Day 1 peak to the start of Day 2 reading – which doesn’t seem to follow.
What am I missing?
You’re missing that there is no repeating cycle, that each day is different from the previous day, and so there is no reason to assume that day two will be identical to day one.
w.
I have seen this supposed typical “greenhouse radiation” chart number of times, it shows a 24 hour period starting at 5pm and ending at 5pm it should show the same level on both ends , not 275W on start and 295W on the end, it is the same 5pm, it makes no sense and yet nobody even questions it.
First, this particular chart is from May 6th, so your claim that you’ve seen it “a number of times” is nonsense.
Second, the amount of downwelling radiation is a function inter alia of the surface temperature … which is different every day at 5 pm.
In the head post I gave you the link to the site. GO TO THE SITE AND LOOK AT THE FOLLOWING DAY!!!. May 7 starts at 295 W/m2, but it looks nothing like May 6th … nor would we expect it to. And May 8th is different from both of them … again as we’d expect.
w.
Your SITE link is bad (Bad Site code) here is the correct link below.
SURFRAD Radiation Data Plots
Thanks, Tommy. I fixed the link.
w.
The problem is the word ‘typical’, which implies ‘average’.
The phrase ‘random day’, or ‘specific day’ measurement would be clearer.
I have a question about that chart.
The minimum DWLIR at 5am is 250Wm2, what Average Temperature does this represent and at what Height in the atmosphere?
AC, per S-B the temperature is -9°C. As to the height, if you go to the site and click on “soundings” for 0 GMT on May 6th, it looks like it’s about -9°C at a pressure altitude of about 500 mb.
With temp = -9°C, pressure = 500 mb, surface pressure = 836 mb, that’s about 2.5 miles up.
w.
The disturbing thing is Willis, that you still think that a ‘theory’ can be ‘proved true’.
Wash your mind out with Karl Popper!
I specifically said that this does NOT establish that my theory is true, in part because I wanted to disabuse people of the idea that a theory can be shown to be true. Sorry if that wasn’t clear to you.
w.
Would it be possible to parse out the humidity or water content response to downwelling radiation from coincident dataset?
It’s difficult because we don’t have much in the way of global humidity or water content datasets.
w.
Willis, please develop a reality based model, maybe with other rational thinkers! It would be great to do monthly or seasonal comparisons with reality and with the doomsday models.
At the risk of being deleted, I think it unwise to model the effect of gases in the atmosphere as ‘downwelling radiation’, instead of what it intrinsically is: insulation, properties of the atmosphere that effect the flow if energy coming from the true energy sources, the Sun and to a much lesser extent, the geothermal energy. I could be wrong but it seems like alarmist treat the co2 as a separate heat source, quoting some such W/m2 when it always depends on the energy coming in (and of course at night it depends on the heat capacity of the atmosphere, yes). I haven’t done a lot of heat transfer modeling, and they were simple ones or using readymade reactor modeling software like Cathena, but I always tried to set up the model to mimic as best as possible the real system.
Oops, forgot most importantly to commend your work! You have added truly to the field of science, in the way you’ve shown how temperature and radiation correlate (or don’t) and clearly shown how water is the true thermostat, keeping the oceans from going much above 30°C. Hopefully free thinking climate modelers will take to heart the glimpse inside the climate machine that you’ve provided.
Very good. As in any system that is very old I would assume that there are no tipping points within previous experienced “forcings” by that system. Since earth did not end-up in a hot-house or an ice ball and got stuck there millions of years ago, there are “emergent” phenomena to counteract that. Tipping points are typical phenomena of computer models. They are not typical phenomena of systems millions of years old. There can be no other conclusion than that emerging negative feedback mechanisms are counteracting the warming of increased CO2. Earth is a waterplanet with enormous capacities to transport heat to the atmosphere and release it there as negative feedback in combination with increased albedo through more clouds.
Willis, could you explain your Fig. 1? What happens between 23.59 hrs and 00.01hrs?
Tony, it’s one specific day, not an average. The next day is different. Go to the site (link in the head post) and call up some days in sequence.
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Willis, please make it standard practise to add atlantic centered maps. People in Europe cannot read your maps.
Hans, I’ve been doing that, but in this case it would mean an additional eight maps, which seemed extreme. Having said that, nobody lives in the mid-pacific where my maps are centered … and yet I can read them.
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UCAR did a limited version of “Mean Pattern Correlation” checking for the CMIP6 models that were available in January 2020.
See the colourful table at the top of the following link :
https://webext.cgd.ucar.edu/Multi-Case/CMAT/CMATv1_CMIP6/index.html
It includes “ENSO”, “LWNET(TOA)”,”SWNET(TOA)”,”LW(CF)”, “SW(CF)” and “RH(SFC)” lines, which I think are related to the “aspects of the real climate system” covered in your article (though they are by no means identical to them).
Note that the “OVERALL” correlation scores go from 72 to “only” 86 (percent), while the “ENSO” line is noticeably “blue-er” than most.
PS : The link also includes the following line :
“NetCDF files with data of plotted fields can be found in case directories in this compressed tarfile (10 GB).”
Thanks, Mark, most interesting link. Bookmarked.
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Willis says: “If I ran the zoo, I would get the modelers together and devise some simple tests, something akin to the graphs and regional measurements in Figures 2 a-e above, but covering many other aspects of the real climate system. I would have a competition wherein we could evaluate and rank all of the models based on how well they passed those tests.”
Tests are good, however I would posit an even better motivator to produce realistic models than mere tests would be to link their funding and employment to how accurately the models predict! (i.e. put some consequences to the failure of tests)
Akin to how if an engineer or a gaggle of them designs some aspect or system, and it crashes planes, or trains or collapses bridges – they never work again at engineering!
So instead of “I may not pass the test”, it is “oh schist, if I can’t pass the tests then I will be working at Starbucks slinging latte’s!”
Some may argue this would completely stifle science investigation – no, it would make it come back to reality. And only actually tested hypotheses get funded and accepted.
All aspects of real life has such consequences: if a plumber screws up royally as have the Climate Cult, he does not get customers and goes broke or finds another profession. If a mechanic screws up again and again and again – he does not continue employment or business…. etc, etc… It should be no different for all these wolf criers and sky is falling proponents….
Let me try another analogy – anyone with almost no skill can walk on a 4″ wide line painted on the pavement without stepping off the line. But put a 4″ wide beam 200 feet in the air and only the most skilled at the task will even attempt it – and only after a lot of practice with a net.
This is how we should treat all this “modeled” science masquerading as reality or prediction of reality. (there has to be consequences for the ongoing failures of the thermaggeddon promoters and modelers)
Water is a “mundane miracle” – we’re so closely related to it, and its miraculous properties, we lose sight of them: Like being “nose blind” to a powerful odor, we are “miracle blind” to the amazing molecule that modulates, regulates, and dominates our planet. It’s because of miracle blindness to water that