Britain’s Climate Policy is Leaving Us Dangerously Exposed to Our Enemies
Burnham ‘determined’ to reach net zero by 2050 Prime Minister claims green economy is ‘best chance’ to reindustrialise Britain
A tanking economy with net zero driven rising unemployment is not my idea of reindustrialising anything other than China, India etc.
And the shocker
Wandsworth Council is proposing a significant 94% council tax hike, which would add £958 to the annual bill for households, bringing the total to £1,978. This substantial increase is being considered in response to a projected budget deficit of £215 million by 2030-31. The council attributes this financial challenge to considerable cuts in government funding and the financial situation inherited from the previous [Labour] administration. – London Local
The idea is redistribution…. Take from us in (Conservative) Wandsworth and give it to spendthrift Labour councils.
Maybe it might be a little esoteric outside England, but…
Jam tomorrow(but never today) is an absurd dictum which first appeared in Lewis Carroll’s story: “Through the Looking-Glass and What Alice Found There”. It is now commonly used to signify a promise which will never be satisfied.
Thanks for that.
The government of BC is skilled at making announcements of spending that had actually been announced previously.
A version of what I call ‘slide by you’.
In Dearborn Michigan, the city government has been replacing holidays with Muslim celebrations. Those who have complained have been told to move as they are no longer welcome in town.
Actually, it would bring Council Tax in London closer to what the rest of the country is paying. Here in the North West a D band pays over £2000 per year, double that of Wandsworth now. That’s socialism for you and the voters in Wandsworth just elected it.
The council has always been among the lowest rates in the country because it has been run well, at least until the Labour lot got in and wrecked it. The voters in Wandsworth voted in a conservative council to get rid of Labour and now that council is being punished…
Wandsworth council tax row: Kemi Badenoch instructs lawyers to challenge cuts to Tory-run London council‘I think it is outrageous that Wandsworth Council is having to put up council tax. But they’re not doing it because they want to’ – Kemi Badenoch
If your council costs you more and/or is badly run fiscally like Birmingham and Croydon etc, that is not our problem. You need to fix it.
Quite. The only way to fix it is by voting for careful and ethical politicians who know they are spending other people’s money. No chance of that here, however often I tried.
It’s a process that is beginning to pick up some momentum. For example, the twee middle classes voted Lib Dem (migrant sanctuary party) in Piddington. As they say caveat emptor…
Reform councils have ditched net zero and given DIE a kicking. Saving money. It could catch on.
The problem is this. A party politician cannot be an ethical politician. Ethics requires that a representative represent their own conscience above all. A party politician surrenders that for the party ticket and must obey the party above all.
The democratic world is all party politics and so the chaos.
Here is a follow-up to last week’s Open Thread post. No AI.
This is a simplified exercise demonstrating propagation of uncertainty in a hypothetical step-iterated temperature response model. No unnecessary assumptions are posed.
The power intensity of energy input is a constant nominal value in W/m^2.
At step 0, the temperature is stable, and the exact temperature is known.
The sensitivity to the power intensity of energy input is: delta T = 0.27K/(W/m^2)
The epistemic uncertainty of the input is +/- 0.034 W/m^2 on a standard uncertainty basis. This is the only source of uncertainty in the model.
Each step is considered an independent instance in which the temperature result of the previous step is operated on using the nominal value of the input to obtain a new temperature result, which is then passed to the following step. The uncertainty is taken to be uncorrelated through the sequence of steps.
What is the standard uncertainty of the temperature after 17,520 steps? Use the Root-sum-square method to combine the uncertainties of the sequence of steps.
Answer:
The uncertainty contributed at each step is the same. +/- 0.034 W/m^2 * 0.27K/(W/m^2) = +/- .0092K
The final uncertainty is computed as sqrt (17520*(0.0092K)^2), giving a result of 1.22K, i.e. +/- 1.22K. This is on a standard uncertainty basis, i.e. one standard deviation.
Now someone may say, “Wait. The uncertainty shouldn’t accumulate! The uncertainty of the final temperature will just be +/- 0.0092K!” That would be true for a single instance of input -> response. But this is a step-iterated model, as described above. The buildup of uncertainty is unavoidable even as the temperature itself remains stable.
So what? This exercise points out a critical issue with the use of ANY time-step-iterated earth system model, running ANY scenario of emissions, to investigate the climate system response to the computed radiative “warming” tendency of incremental CO2. It was implausible all along to expect any diagnostic or prognostic value from that complex exercise. The accumulating uncertainty is far greater than the factor being investigated. It is circular. If you think you know the response in advance, then why the pre-stabilized, time-step-iterated models at all?
Thank you for your patient attention to this matter.
P.S. ######
Why those particular numbers for this hypothetical exercise?
The +/- 0.034 W/m^2 comes from the stated 100 ppm absolute accuracy of the TIM instrument aboard the International Space Station. We cannot measure Total Solar Irradiance any better than that. This uncertainty value corresponds to the nominal TSI divided by four, to represent the geometric average over a spherical surface.
The 0.27K/(W/m^2) sensitivity is a no-feedback value computed from an assumed 255.27K emission temperature vs a 255K emission temperature, which gives a 1 W/m^2 change.
https://lasp.colorado.edu/media/projects/tsis/documentation/README.TSIS.pdf
“1.1.1 Instruments
TSIS-1 consists of two instruments, the Total Irradiance Monitor (TIM) and the Spectral Irradiance
Monitor (SIM). …
TIM measures TSI across the entire solar spectrum. TIM is an ambient temperature, active cavity
radiometer. TIM measures TSI to an estimated absolute accuracy of 100 ppm (0.01%). TIM
measurements began on January 11, 2018.”
###### end P.S.
Let’s remember that the May 23, 2025 Executive Order “Restoring Gold Standard Science” includes this requirement in Section 4:
“(c) When using scientific information in agency decision-making, employees shall transparently acknowledge and document uncertainties, including how uncertainty propagates throughout any models used in the analysis.”
This is important for skeptics of climate alarm to know about, in my view. The EPA, the DOE, the USGCRP, etc. must all be held to this requirement.
David, good posting of the Section 4: (C) “When using scientific information in agency decision-making…”. When Geologists write an important report, commonly recommending the spending of millions of dollars, it is common (at least for me and those working for/with me) to include a section, just before Conclusions and Recommendations, titled “RISK ANALYSIS: FATAL FLAWS, CRITICAL PATHS, AND RISK/REWARD ANALYSIS.”
The most obvious example in the CAGW reports, is a lack of comparing the cost and risk of Mitigation versus Adaptation.
Yes, acknowledge factors not ‘controlled for’ in the research.
But POTUS Trump does not do what you quote. He is emotional and erratic, puts mouth in motion before brain in gear. Many politicians do but he is far worse than most.
Thanks, very interesting. It does seem quite logical that when you add one uncertain number to another uncertain number, the uncertainty would increase with each iteration. It does seem that the percent change in the total would decrease with each step but the total would grow beyond bound, The magnitude of the uncertainty in the actual value would be so high as to be totally useless. This maybe could be called the “Dibbell Uncertainty Paradox in
recursive Modelling”. The longer it runs the more useless it becomes.
I simply cannot understand why this simple progression can’t be understood by so-called physical scientists as well as mathematicians.
Assumption, measurement uncertainty = +/- 1
1.Input 10 +/- 1, the input range interval is from 9 to 11. The calculating algorithm needs to analyze *all* possibilities associated with the input range, 9 and 11. Let’s assume that the algorithm is just (output = input * 1)
The output from an input of 9 +/- 1 will be 9 +/- 1. ==> 8 to 10
The output from an input of 11 +/- 1 will be 11 +/- 1. ==> 10 to 12
Thus the input to the next stage will be 10 +/- 2
2.The input to the next step will be 8 +/- 1 and 12 +/- 1.
8 +/- 1 gives a range of 7 to 9
12 +/- 1 gives a range of 11 to 13
These become the possible inputs to the next stage, 7 and 13, or 10 +/- 3
At each step the measurement uncertainty ADDS.
It is just a simple progression. And it really doesn’t matter what the calculating algorithm is. That only affects the estimated central value, it doesn’t change the additive progression in measurement uncertainty.
There is only a “structural” correlation in the measurement uncertainties in that they are all assumed to be the same. That is *not* a requirement. The measurement uncertainty used for each step could be different. The uncertainties would still *add*.
There is no “calculation” correlation. Since the measurement uncertainties at each step are totally independent, i.e. the measurement uncertainty at step n is not determined by the measurement uncertainty in step n-1, there is no calculation correlation. Thus a simple addition of the measurement uncertainties is proper. Generate 17520 independent, random measurement uncertainty values, one for each step, and the same progression will ensue, Σu(i) from i=1 to 17520.
I even question the use of root-sum-square to add the uncertainties. The RSS method assumes some cancellation of random measurement uncertainty among multiple uncertainty components. But in a step progression, there are only two components, the measurement uncertainty of the input and the measurement uncertainty added by the algorithm to each possible uncertain input value. Assuming a partial cancellation between just two components is a stretch. Think of the direct addition as the worst possible result and the RSS addition as the best possible result.
There is absolutely no use of a 1/(n-1) factor against the measurement uncertainty in this. the n-1 factor is used to estimate SAMPLING uncertainty, not measurement uncertainty. There is no *sampling* involved in a step progression, just a plain calculation of (output = X * input). X may be additive, multiplicative, linear, non-linear, etc. NO sampling! And no sampling of measurement uncertainty.
Thank you for your reply. “Think of the direct addition as the worst possible result and the RSS addition as the best possible result.”
No disagreement there.
Well, not completely. DD has assumed that the error factor generated by a single calculation has a “standard” shape, (common, but still an assumption) so he can use a “standard deviation” to measure the expected error range per calculation and compound it accordingly. Your example assumes a uniformly distributed error, (an error of +1 or -1 is as likely as 0), which really is a highly unlikely mistake for even the Thermometer-Readers to make in a Model.
The point is to establish an interval. Technically, NIST and others recommend multiplying the combined standard uncertainty by a factor of two in order to achieve a confidence interval of 95%. That is what science requires, but oh no, climate science knows better. Their belief is that averaging can disparate measurements can cancel out all random error and corrected records can eliminate systematic error. (I bet drug companies would love the ability to do this!)
This would make your +1 and -1 into +2 and -2. I never push this because if the 68% interval exceeds the values of the measurements being touted. That is the real issue climate science never touches.
Technically, it adds in quadrature. This is well known and not challengeable. The reason you never hear about the uncertainty of reported prophecies of future temperature (based on models) is because the uncertainty value far exceeds claimed value for an increase or decrease.
An honest reporting of the uncertainty 20 years out rendered them meaningless, obviously so.
The reason the uncertainty is so large is because the system being analysed is so poorly understood. The chance of it being understood really well anytime soon in low.
So, if we have a bunch of spotters all looking at the same time with some instrument counting individuals of a rare species over period of time knowing their speed of movement. Taking four observers at NSEW and getting 9 7 6 8 Sum 7 for their assigned area. Subdivide all the rest of the territory area, how far from the real number will the observations be each. Highly likely 2
Who says? Which mathematical genius has proven the method recommended? Which other statistician/mathematical expert has a different method getting a different result?
Is anyone here sufficiently highly expert in this field to explain it to an expert in many fields but not in mathematical statistics. And NOT in SYMBOLS
I ask this because a new statistics was needed for electrons and the one invented/discovered is now called Bose/Einstein statistics. The bog standard usual statistics did not work on them and it had something to do with the objects counted being individual or identical.
When you do these calculations: Does the earth rotate and orbit the sun? Are the effects of moon the tides taken into account? Last winter in the Yukon and NWT air temperature plunged to -50° C which broke all previous low temperature records. Climate models usual address warming, but never about cold winters like in Canada where I live. What are winters like where you live?
There is recently a whole lot of foolish and silly talk about “climate change”. About 80% of the earth’s climate is water, ice and snow. Activities of humans will never affect the climates of the vast Pacific, Indian and Atlantic oceans, the Alps, Andes, Himalaya and Rocky mountains, and the Sahara, Gobi, Mojave and Atacama deserts. Activities of humans can modify local climates due urban island effects. In some regions activities of humans and their animals can cause vast reduction of plant life which results desertification.
“When you do these calculations: Does the earth rotate and orbit the sun? Are the effects of moon the tides taken into account?”
No, because there was no need. This particular post poses a hypothetical case where only the most fundamental concept of temperature response to the power intensity of energy input is considered, to highlight the buildup of uncertainty by step-iterated modeling. No disagreement with your points about the real planet.
Now someone may say, “Wait. The uncertainty shouldn’t accumulate! The uncertainty of the final temperature will just be +/- 0.0092K!” That would be true for a single instance of input -> response. But this is a step-iterated model, as described above. The buildup of uncertainty is unavoidable even as the temperature itself remains stable.
This is an important point. Many of the responses to Dr. Pat Frank’s paper used the reasoning that the uncertainty only applied at the 1st response and nothing thereafter. Thereafter it was “baked into” the remaining calculations. That would be true if the 1st response was the only value used in following calculations. It is not true if the same energy input is used in each calculation. The uncertainty of the energy input is added to each calculation that uses it.
Measurement uncertainty is based upon a functional relationship having defined input quantities. The combined uncertainty is calculated from the relative value of each input quantity to the final total. The energy input is an input quantity in each calculation; therefore, it’s uncertainty must be included for each calculation (iteration).
The uncertainty of the other input quantities must also be calculated and propagated for the combined uncertainty to be accurate.
Some have postulated that these are not really measurements but indexes instead. They have crossed into model land where the numbers are what is important and not the actual measurements. If that is the position of climate science, then they should no longer claim that their findings are measurements whose value has a physical meaning of °C, °F, or K. They should show their findings as “index/absolute temperature”, that is, a percentage increase.
A 0.02 monthly increase divided by 16 equals a 0.1% change.
“The energy input is an input quantity in each calculation; therefore, it’s uncertainty must be included for each calculation (iteration).”
Thanks for taking note of this point.
This is why I composed the exercise with no mention of the duration of the step. But even at, say, 30 minutes per time-step, the uncertainty of the energy input at each iteration in the complex models cannot be ignored. Some might say, “But the 0.27K/(W/m^2) sensitivity should only apply to longer intervals! Think of the huge thermal mass!” On the other hand, the surface skin and the lower atmosphere warm and cool quickly. So it’s only a tiny fraction of the total thermal mass in any case that is responsive to the daily cycle of solar input.
Nice, but it leaves out a few practical issues. 17,520 time steps is 48 years of daily data, but no one will be using TSIS-1 data in a few years after TSIS-2 launches, which won’t be on the ISS. The new instrument probably will have similar uncertainty characteristics, we’ll see.
I use annual time steps in my models which helps to reduce the uncertainty problem significantly.
Regardless of TSI uncertainty, no one knows what 48 years of future sunspots (or TSI) will look like.
It is preferable to go only one solar cycle into the future at a time, but that won’t give the desired answer for 2100 or whenever. People want more certainty in their climate models than is realistic.
Be careful of how you propagate uncertainty here. The sum of 365 data points has 365 input quantities. Each of those input quantity’s uncertainty combine in quadrature for a combined uncertainty.
Climate science operates on the fact that if you have enough “pieces” an average will result in a vastly diminished uncertainty. Lay 9051 bricks of 7 ±0.5″ end to end and say it will be 5280 feet long because all the uncertainty cancels in the average is what climate science does. The average will mislead one of what the actual value may be. In actuality the uncertainty is 5280 ±4 feet.
The CU doc does not use the standard language of the GUM, but instead states: “estimated absolute accuracy of 100 ppm (0.01%)”. Exactly what this means isn’t clear, the cavity radiometer calibration result?
The +/- 0.034 W/m^2 comes from the stated 100 ppm absolute accuracy of the TIM instrument aboard the International Space Station.
Plots of historic solar irradiance versus time shows the multiple instrument uncertainty is considerably higher, at least ±1 W/m^2.
In comparison, the total uncertainty of cavity radiometers measuring direct irradiance at the surface is on the order of ±0.3-0.4%, which is ±3-4 W/m^2 at 1000 W/m^2.
This uncertainty value corresponds to the nominal TSI divided by four, to represent the geometric average over a spherical surface.
Not sure I understand this, a cavity radiometer measures irradiance at essentially a small point (the entrance to the cavity).
“The +/- 0.034 W/m^2 comes from the stated 100 ppm absolute accuracy of the TIM instrument aboard the International Space Station.”
Whoever “stated” that the TIM has an absolute accuracy of “100 ppm” (equivalent to +/- 0.00005%, in turn assumed reference to maximum value that could be measured) MUST have been referring to calibration performed on Earth in a carefully-controlled environment using a carefully-controlled radiating reference target.
That statement ABSOLUTELY FAILS the smell test for the absolute accuracy delivered “in the field” given the expected interference/degradation caused by external radiation, RFI, instrumental temperature variations, and aging affecting the instrument itself on ISS, as well as natural phenomena occurring in the TIM instrument’s FOV (such as the Moon’s reflected sunlight in turn being reflected off Earth’s atmosphere, meteors burning up during atmospheric entry, aurora, atmospheric lightning, and brief electrical discharges known as Transient Luminous Events (TLEs), aka red sprites and blue jets, that flash miles above severe thunderstorms).
I have no doubt that these transient phenomena, each having different spectral signatures, were not simulated in the reference target during ground laboratory calibration of power flux radiation (W/m^2) as measured by the TIM instrument. Therefore, I don’t think an assertion of 100 ppm absolute accuracy for TIM’s use aboard ISS is credible.
It is a baseline figure used in an example to show the problem with calculating uncertainty.
What you are discussing is an actual uncertainty budget that takes different contributions to uncertainty. It is like the folks that want to use the uncertainty in a PRT sensor in weather station but never add categories that add to that. Housing temp, wind speed, drift, siting, and a host of other things that affect field measurements.
In all the climate papers I have read, I have NEVER seen an uncertainty budget for each station used. It is like buying 100 balance beam scales, distributing them to various locations and assuming they all have the same uncertainty regardless of the conditions they are used in. Not even scales weighing grain trucks get to do this. They must meet individual calibration schedules.
“Therefore, I don’t think an assertion of 100 ppm absolute accuracy for TIM’s use aboard ISS is credible.”
No disagreement there. It just served as a value that had been stated out there, however unrealistic, that sets a lower bound to the uncertainty in TSI.
Thanks for your reply. “I realize this is a best-case example…” Indeed so, to show that the buildup of uncertainty in the iteration makes the complex step-iterated modeling pointless.
About the 0.034 W/m^2 – take 100 ppm of 1361 W/m^2 to get +/- .136 W/m^2; divide by four to get +/- 0.034 W/m^2 as applied to the spherical surface area. Similar to Loeb 2018 where a an uncertainty of +/- 0.13 W/m^2 is stated.
Climate science in general has very little appreciation of radiometric measurements and instrumentation — ±0.13 W/m^2 is a relative uncertainty of ±0.01 %, which is absurdly small.
The solution to the apparent paradox is to only use models with one step. 🙂
However, it makes sense that a model forecasting out 10,000 years can’t be expected to have the same uncertainty as one that is only forecasting out one hour. Perhaps there is something that we are overlooking such as careful analysis of the units used. Implied in a single calculation is units of ‘measurement uncertainty per calculation’ resulting from not knowing the precision exactly, where a calculation is only expected once as in converting from one standard unit to another, e.g. C to F. An alternative assignment might be explicitly accounting for temporal drift with units of ‘measurement uncertainty per unit of time,’ recognizing that other variables that are assumed to be constant may change over time. Also, calibration can also change with the change in the independent variable; that is, the radius of the bore of a LIG thermometer may change both with temporal changes in temperature and positional changes of the liquid along the axis of the thermometer.
I’m suggesting that one can reasonably expect uncertainty in calculated dependent variables to increase in time series, but that the measurement uncertainty should be the same whether there are 100 measurements or 1,000 measurements over the same amount of time. I do think that we are missing something.
My biggest problem is climate science having the hutpah to say they “forcast” into the future far enough and accuratly enough to make policy recommendations today. Measurement uncertainty is only part of the problem. Ultimately, measurement uncertainty accumulates. The GUM and all my current metrology books show that. All the equations have plus signs when combining uncorrelated input quantities.
Climate science wants to believe that measurement uncertainty is a group of errors that can cancel. Then, since a plus error can cancel a minus error, the best indication of the true value is the mean and the standard deviation of the mean is the best determination of the interval surrounding the mean. Th error paradigm says if you want better measurements just make more and more measurements using the same procedures and the same equipment.
That paradigm has sailed into oblivion. The new paradigm is that random readings can define a distribution of readings providing an interval where the true value may lay. That interval is the standard deviation of the resulting distribution. And, most national bodies like NIST recommend increasing that by a factor of two for a confidence factor of 95%. From that, the best ESTIMATE of the true value is the mean of the distribution if it is Gaussian. If you want a better estimate, use better methods and equipment to obtain higher resolution and better precision.
The error paradigm defines the mean AS the true value with a smaller and smaller interval surrounding it. The uncertainty paradigm defines the mean as an ESTIMATE that can be anywhere in a larger interval.
Modeling should be set up to take uncertainty into account. The computers they are using could easily and quickly do the necessary calculations. The real issue is how accurate the real random occurances like volcanoes, tectonics, Nino/Nina’s, clouds, etc., are handled. These all make outputs of temperature to the 100ths of a degree hilarious.
Jim, I think that you and your brother know me well enough that you realize that we are almost always in agreement. However, I’m troubled by the assertion that the iterative-uncertainty in the nth value in a time-series should be n-times larger than the zeroth measurement uncertainty. I haven’t yet been able to completely wrap my head around the problem, but something has been nagging at me for some time. It may be related to being an octogenarian who has been removed from formal mathematics for decades. That, however, may be an advantage. I’m asking myself whether it makes sense that a calculated uncertainty should be constrained by the number of samples taken in a given time interval.
Consider the following: One’s boss has a deadline to submit a graph to upper management and the main computer is down, but he has 100 engineers at his disposal. He sends out an email to all his engineers and says, “I need this back in 1 hour. Please calculate the mean value of all the tabular inputs for the day that corresponds to your employee number and substitute the mean in the function given below. Also, calculate the standard deviation, which I will assume to be the uncertainty range of the mean of the measurements. I will plot the graph.” Assuming that all the engineers are competent, and still have the hand calculators they were issued when they were hired, it should be trivial to do the calculations, with the biggest obstacle being the time for data entry.
If each and every calculation is done independently, from the same raw data, using the same brand of calculator, and the boss simply transposes the final calculations to a spreadsheet for graphing, why should the uncertainties (SD) grow over time when each point is calculated independently? If upper management gives the boss a reprieve until the next day, and to refine the results he decides to ask the staff to do the same thing for an additional 100 interpolated points, should he expect the results of the additional 100 points to have different range boundaries?
However, I’m troubled by the assertion that the iterative-uncertainty in the nth value in a time-series should be n-times larger than the zeroth measurement uncertainty.
Here is what I think.
If T0 = x ±u and the calculation is Ti = x + y ±v, then the combined uncertainty u꜀ = √(u² + v²). If Ti is inserted in the next iteration it inherits u꜀ and increased again by “v”.
So the issue is not that the original uncertainty is doubled, tripled, or multiplied by 17,000. The issue is what occurs in the calculations.
If an input quantity keeps the same uncertainty throughout, then it is a constant. If it increases at each iteration then the uncertainty must increase in each iteration.
Thank you for your thoughts.
“I do think that we are missing something.” Perhaps so. “The solution to the apparent paradox is to only use models with one step.” Or at least to recognize that the time-step-iteration problem is real and blurs the result, limiting the reliability.
But let’s be reminded that the time-step-iterated climate models do indeed work this way – i.e. the mass and energy states of the earth system are completely re-computed as they evolve through every dynamic iteration, closing the energy-in and energy-out flows and all the internal energy-storage-and-release interactions, and pass the result to the next iteration.
So where are we? We have decades of investigation using dozens of versions of pre-stabilized-by-tuning models running radiative transfer coding which always gives a baked-in “warming” result for the rising concentrations of GHGs in the specified scenarios.
One more thing. Willis Eschenbach’s model – which uses “constructal law” optimization to converge on a result – is a fundamentally different computational approach that presumably avoids the time-step-iteration buildup of uncertainty. There are other sources of uncertainty, for sure, but it’s interesting to think about.
But let’s be reminded that the time-step-iterated climate models do indeed work this way – i.e. the mass and energy states of the earth system are completely re-computed as they evolve through every dynamic iteration, closing the energy-in and energy-out flows and all the internal energy-storage-and-release interactions, and pass the result to the next iteration.
David, you raise an extremely important point here. That is the method of calculation! Different methodologies or schemas of calculation should not result in different answers for the sum or final point; that includes the uncertainties associated with the intermediate or final outputs. That is, multiplication should give the same answer as multiple additions. If iteration gives a different answer than multiple calculations that are concatenated, then iteration-uncertainty is not done right.
Similarly, the final uncertainty of a calculated output should be the same whether 2n or 1000n intervals are used to arrive at the final point in the time-series. It appears that what you and Jim and Tim are recommending becomes a function of the multiplier of the number of time steps, n. If they do result in different answers, then it should give one pause.
Thank you for your further reply.
“If they do result in different answers, then it should give one pause.”
Yes. It should have given pause to “climate” investigators long ago (’60’s to ’90’s) that the discretized time-stepped dynamic models developed for weather prediction do, in fact, give different estimates of uncertainty (in a projection) depending on the time step chosen. That computation method for estimating the long-term energy-state influence of rising CO2 should have been recognized as not capable of ever providing a reliable answer.
But here we are, decades later, discussing why it was unsound all along to have made that choice.
Similarly, the final uncertainty of a calculated output should be the same whether 2n or 1000n intervals are used to arrive at the final point in the time-series.
That is not exactly what I am saying. Each input quantity in a functional relationship will add to the combined uncertainty. If I₀ is used in each iteration, its uncertainty is added to that’s iteration uncertainty. If
T1 = I₀×T₀, then u(T1) = √(u(I₀)+u(T₀)), and T2 = I₀×T1, then u(T2) = √(u(I₀)+u(T1)).
This means u(I₀) is added again. u(T1) also contains u(T₀) so it is added again.
I am no expert on the inards of GCM’s. I do know that an iterative process adds uncertainty at each step. It is no different than laying bricks end to end. The uncertainty in each brick adds to the overall uncertainty.
Dr. Pat Frank showed that GCM’s turn into linear projections. That makes it even easier to show that uncertainty is added at each iteration. Adding 2 ±0.5 over and over, the uncertainty adds (probably in quadrature).
Rather than answering the uncertainty criticism climate science has refused to even show minimal evidence of how uncertainty is addressed inside the GCM.
NOAA’s Tides and Currents page is being redone.
If you follow the link, this terse sign comes up:
This site will no longer be available after September 30, 2026. Please visit the new, integrated Sea Level Trends and Extremes – BETA site. If you have any questions regarding this forthcoming change, please contact our customer service support at tide.predictions@noaa.gov.
I expect the new page will be a full of glitzy images with no useable content.
For example, the
“…absolute global sea level rise is believed to be 1.7-1.8 millimeters/year.“
statement will be more buried than it is already or totally gone.
People generally know the textbooks methods like GUM on how to measure uncertainty, but many avoid doing it in favour of silence, or maybe because the uncertainty is so large that the validity of their work is shown to be questionable.
Some agencies like Australia’s Bureau of Meteorology insist on dividing their uncertainty result by the square root of the number of observations, which is fine for synthetic numbers without confounding factors, but does not apply to field observations such as daily surface air temperatures. This is an unforgiveable error for the mathematically educated. Its use is giving Science a bad name. For 100 observations, this division by 10 creates a false but large decrease in the real uncertainty.
“Some agencies like Australia’s Bureau of Meteorology insist on dividing their uncertainty result by the square root of the number of observations”
This is *NOT* measurement uncertainty. It is SAMPLING uncertainty. The use of the (n-1) factor is only a shortcut for determining the standard deviation of the means of multiple samples, i.e. the SEM. The absolute correct method for determining this is to make multiple samples of the population consisting of “estimated value +/- measurement uncertainty”, take the mean of the estimated values from each sample, and determine the standard deviation of those sample means.
The sampling uncertainty equation should be SEM = σ/sqrt(n)
where σ is the population standard deviation.
Since the population standard deviation is probably unknown and many times only one sample is available the shortcut estimate SEM = s/sqrt(n-1) is used. If you assume that the sample is IID with the population the formula would actually be SEM = s/sqrt(n). If the single sample is not IID then s/(n-1) has its own uncertainty. For large n, 1/sqrt(n) and 1/sqrt(n-1) converge but the SEM calculated from a single sample may still be inaccurate since “s” may be significantly different than σ, especially if the population distribution is not Gaussian (or at least well-behaved).
Bottom line? Sampling uncertainty is *NOT* measurement uncertainty.
One can fudge a little on the definition of simultaneity and have many measurements in a second and say that the time difference between measurements is small enough to legitimately claim that the thermal inertia is high enough that the measurements are essentially simultaneous, by the same instrument, of the same parcel of air or water. The only real advantage is if there is a voltage spike that is more than 2 or 3-sigma, and the original data are retained, it will be obvious that it is an outlier that should be deleted. If it isn’t retained, then the multiple samples are a waste of processing.
This is a measurement system that digitizes temperature data from a single sensor over a given time period, then averages the readings into a single temperature. However the temperature varies during the time period (and the electronics), there will be n numbers of samples that aren’t equal to each other, and a standard deviation associated with the average. Climate science ignores and throws this standard deviation away (along with those associated with any other subsequent averages). But the standard deviation should be included in an account of the uncertainty of this measurement system, and reported with the final measurement result. Outlier determination and treatment then lays in the realm of statistical process control.
What I’m really arguing for is that I acknowledge “One can never step in the same stream twice,” is literally valid. However, considering the several steps that might be necessary to get across the stream, it might be good enough for government work to just assume, at least as a first-order approximation, that all the steps were in the same stream.
The GUM covers some of this. Sections F.1.1.2 and H.6 deal with measurements of not the same thing. H.6 deal with testing hardness where the same point cannot be reused. They both say the standard deviation of the various measurements should be added to the measurement uncertainty. No divide by the √n, no fiddling, just add.
Keep up the good work, Geoff! And thanks for mentioning Pat Frank’s 2019 paper, which stands out in the published literature on propagation of uncertainty.
This WIKI entry is wrong. It assumes Earth radiates as a BB which I have demonstrated is wrong. Its reason for dividing Io by 4 is ½ & ½ nonsense. Io is divided by 4 to change the model from discular area to spherical area at ToA. This is Fourier’s model which even Pierrhumbert says is no good. It also uses a GHE balance graphic which I have demonstrated is also no good. It uses AU for some reason and never calcs W/m^2 correctly.
Calculation of equilibrium temperature
Consider a planet orbiting its host star. The star emits radiation isotropically, and some fraction of this radiation reaches the planet. The amount of radiation arriving at the planet is referred to as the incident solar radiation, I_oalbedo that depends on the characteristics of its surface and atmosphere, and therefore only absorbs a fraction of radiation. The planet absorbs the radiation that isn’t reflected by the albedo, and heats up. One may assume that the planet radiates energy like a blackbody at some temperature according to the Stefan–Boltzmann law. Radiative equilibrium exists when the power supplied by the star is equal to the power emitted by the planet. The temperature at which this balance occurs is the planetary equilibrium temperature.[4][5][6]
Derivation
In equilibrium, the solar flux absorbed by the planet from the star is equal to the flux emitted by the planet:[4][5][6]
F_abs=F_emit
A_B
F_abs=(1-A_B ) F_solar
F_solar
F_solar=I_o/4
6] The factor of 1/4 in the above formula comes from the fact that only a single hemisphere is lit at any moment in time (creates a factor of 1/2), and from integrating over angles of incident sunlight on the lit hemisphere (creating another factor of 1/2).[6]
Assuming the planet radiates as a blackbody according to the Stefan–Boltzmann law at some equilibrium temperature
T
e
q
{\displaystyle {T}_{eq}}, a balance of the absorbed and outgoing fluxes produces
Assuming the planet radiates as a blackbody according to the Stefan–Boltzmann law at some equilibrium temperature T_eq
F_emit=σ” ” T_eq^4
σ
(1-A_B )(I_o/4)=σT_eq^4
T_eq=((I_o (1-A_B ))/(4″ ” σ))^(1/4)
T_eq=((L_o (1-A_B ))/(16″ ” σ” ” π” ” d^2 ))^(1/4)
L_0 3.828⋅10^26 ” W” d
T_eq=1.07652⋅10^8 (1-A_B )^(1/4) (d/”meter” )^(-1/2) ” K”
T_eq=278.3296⋅(1-A_B )^(1/4) (d/”Au” )^(-1/2) ” K”
where the distance is given in astronomical units.
One example from your post’s second paragraph: “The amount of radiation arriving at the planet is referred to as the incident solar radiation, I_oalbedo that depends on the characteristics of its surface and atmosphere, and therefore only absorbs a fraction of radiation.”
The amount of radiation from a star that arrives at an orbiting planet DOES NOT depend on the the planet’s albedo . . . that arriving radiation is even indepent of the planet having, or not having, an atmosphere.
Another example from your cited “Derivation”: “Assuming the planet radiates as a blackbody according to the Stefan–Boltzmann law at some equilibrium temperature T_eq F_emit=σ” ” T_eq^4″
It is a well-known fact that Earth DOES NOT radiate as a blackbody and therefore it’s average emissivity to space, which you include in your calculations as the symbol σ must have a value less than 1. However, it mysteriously disappears towards the end of your “derivation”, which I find impossible to follow as posted.
Black-body refers to a TYPE of radiative emission. We can all see the pictures of a blue and white glowing jewel in the black of space.
This bloke simply does not get it.
The term “grey body” distinguishes radiators that have an emissivity less than 1 from blackbodies that by definition have an emissivity of exactly 1.
There is only one type of radiative emission from bodies having a temperature above absolute zero and such is independent of emissivity: that of EM photons, with acknowledgement of the wave-particle duality of EM photons.
Is the molten iron being poured out of a blast furnace radiating as a mix of isotopes of iron or as a really hot thing shedding energy by radiation?
I expect that the discussions and the measurements of the electromagnetic energy exchange of the ocean waters and the atmosphere be deal as if it were the latter.
Humans giving different words to things do not change the reality of reality. Black, grey, absorption spectra, emission spectra are just words and our dealing with actual observations requires that we take into account the true nature of the mechanisms of energy flow and exchange of the ACTUAL substances being investigated.
Radiative equilibrium exists when the power supplied by the star is equal to the power emitted by the planet. The temperature at which this balance occurs is the planetary equilibrium temperature.
The Earth has not reached this point of radiative equilibrium yet, as the planet is still cooling, losing around 44 TW or so.
Your calculations seem to be based on at least totally incorrect assumption. Assume the surface is molten everywhere, do your calculation, and tell me what the calculated temperature.
My back of the envelope calculation based on measurements and basic physics gives me an “average” surface temperature of around 17 C, with a maximum possible of around 90 C.
This reflects the existence of an atmosphere. For the Moon, max comes out at around 130 C, close to measured surface temps.
Just for fun, AI burbles NASA nonsense about the Moons surface temps initially, but in response to my first follow-up question, responded –
You are entirely right to call that out, and I apologize for the confusing phrasing. Heat transfer follows the exact same laws of physics in a vacuum as it does anywhere else.
AI was repeating the silly meme that the Moon gets hot because it has a long lunar day. At least the AI realised that NASA was talking nonsense. Most people don’t.
The actual earth looked at by actual eyes or actual cameras radiates as a glowing blue and white globe in the visible spectrum,
NOBODY pretends it is an actual black body. The first work looking at other planets had them doing a thought experiment – a planet the size of earth in its present average distance from the sun but totally emissive (no particular colour) was calculated to reach a certain temperature.
Then the theory added an atmosphere and the calculation was repeated.
The theoretical model earth was warmer at the surface when there was a blanket of atmosphere around it. CRUDE BUT PROOF OF CONCEPT
No consideration was given to the thermal conductivity of the rock or the presence of rotation. It was a THOUGHT EXPERIMENT!
The phenomenon was then given a name because of its likeness to a familiar structure, a greenhouse. Sunlight is actually black-body radiation for most intents and purposes.
The finding of spectral lines in the light from stars was a surprise but they are all emitting black-body like radiation with the TRACE presence of the spectra of elements.
Not so cosmic “dust” clouds and other celestial phenomena which glow from other stimulation rather than raw energy.
Look – no numbers. My primary school children understand it.
The actual earth looked at by actual eyes or actual cameras radiates as a glowing blue and white globe in the visible spectrum, …
The peak of the visible spectrum is in green light. However, the appearance is shifted to longer wavelengths (orange-yellow) because of Rayleigh scattering, which is what causes the sky to appear blue.
A white sky happens when there is lots of aerosol scattering. The sun, OTOH, is so bright that the eye can’t detect the green peak wavelengths. When it is low in the sky with scattering the color shifts to yellow and red.
Can they balance your checkbook?? Can they explain 63 + 63 = 63?
Wow, what a haboob of appeal to authority, esoteric subject changes, hand wavium, ad homonym, gorilla dust.
Let’s yank this out of the weeds and back on track.
Ya know, I have thoroughly plowed this dead horse but here goes once more.
1. Earth is cooler w atmospheric/water vapor/30% albedo not warmer. Yes/No & why.
2. GHE balance graphics don’t plus violate GAAP & LoT. Yes/No & why.
3. Kinetic heat transfer processes of contiguous atmospheric molecules (mistaken for “back” radiation) render “extra” GHE energy from a BB surface impossible. Yes/No & why.
Near Earth space is a 260 F convection oven not a near abs zero ice box.
TFK_bams09 has 63 twice, once originating from the 342 ISR and again from the out-of-thin-air 396 S-B BB calculation violating GAAP.
Incoming 1,368/4 = 342 *(1-.3) = 239-79 =160 & Outgoing 17 + 80 + 63 the 1st & balanced!!
Imaginary 396 S-B BB 16 C. Calculated, not real, fills denominator of emissivity ratio: 63/396=0.16 needed to correct IR that sees targets as BB.
Imaginary 333 “back” component of the 396 also not real
Imaginary 63 the 2nd has no place to go and must return & -396/+333/+63 GHE loop implodes to 0 like the Titan.
Over a week ago at a local King Soopers I crossed paths with a EE I worked with over twenty years ago had not seen since.
We now live abut 10 miles apart.
I snail mailed to him a copy of my position paper.
It has yet to be delivered.
USPS AI leaned on by influencers?
USPS will not platform my “misinformation.”
That just strengthens my resolve.
Charles Bukowski: “Censorship is the tool of those who have the need to hide actualities from themselves and from others.”
Voltaire: “What does censorship reveal? It reveals fear. Think for yourselves and let others enjoy the privilege to do so, too.”
Does the USPS open your mail? It takes 3 to 5 to 7 days for a letter to go across town or a state.
King Soopers – – never heard of this. There are Freddy’s around.
King Soopers are common in Colorado. I have a King Soopers member card that I routinely use at my Ohio Kroger chain, after more than 20 years. They are all owned by Kroger.
How do you know it wasn’t delivered?
The USPS does offer ways to receive “proof of delivery”. It cost more but it’s available.
(You may need to go to a post office to send it.)
Maybe he read it and doesn’t want to tell you what shite it is.
You know… EE’s spend some time in engineering school calculating component temperatures on electronic chassis….with “back-radiation” from components nearby, the negative Tcold^4 part of P= eσFA [Thot ^4 – Tcold^4]…the view factor of slightly cooler surrounding components causes overheating of the hotter component moreso than would occur if the “less warm” component was not present….It’s ”back radiation” from the surroundings that they calculate… a proven and easily understandable physics concept which you deny exists…but you know, WTH?…a conspiracy theory fits too, one of their benefits, especially since the post office is known for heat transfer creedo and must be out to get you… “Neither snow nor rain nor HEAT nor gloom of night stays these couriers from the swift completion of their appointed rounds.”
ISR aka Io = 1,368 W/m^2 (Luminosity W/spherical area m^2 at Au)
Divide by 4 to convert discular cross sectional area to ToA spherical area.
1,368 W/m^2 / 4 = 342 W/m^2
Apply 30% Bond (James) albedo.
(1 – 0.3) * 342 = ASR 240 W/m^2
ASR = OLR
OLR S-B equilibrium for 240 W/m^2 = 255 K, -18 C.
OLR equilibrium temperature without esoteric hocus pos handwavium.
Troposphere is full of molecular KE heat transfer processes which negates 396 BB/333 “back”/63 duplicate imaginary GHE loop.
Hmmmm . . . please state what average global emissivity you used for calculating OLR to deep space. After all, it is well-known that Earth does not radiate as a blackbody, considering either just ground surface or as integrated at TOA (ground plus atmosphere).
Please clarify/give an example of “diagrams comparing the sun to the earth”.
Secondarily, the fact that there are “notches” in Earth’s radiation spectrum as measured from space is exact proof that Earth does not radiate as a blackbody!
Practical question, asked seriously.
Suggest the alternative mathematical or theoretical model to use on the sun – earth – space energy flows being discussed.
There are some people here with fixed ideas which we are powerless to change. I refuse to lose sleep over it.
They confuse mathematical formulae with reality!
Plank found a mathematical way to describe the electromagnetic absorption properties of a hole in a cavity to far better represent reality that the classical way, which very very inaccurately described observation. The quantum nature of reality was absent.
Applying that formula to the planet is the closest tool available in the quest for an understanding of the flow of energy of the planet. There is no other formula which comes within a country mile of approximating it.
So NOTHING is a black body IN REALITY unless people think a pin hole in a big empty space is a thing.
Plank found a mathematical way to describe the electromagnetic absorption properties of a hole in a cavity to far better represent reality that the classical way, which very very inaccurately described observation.”
Talk about a confusing statement!
Max Planck laid the foundational groundwork for, and is widely considered the originator of, quantum theory. Quantum theory is the largely-mathematical description of the reality of the universe at small scale . . . sub-atomic and smaller dimensions.
At larger dimensions, Maxwell’s equations describing EM radiation and absorption work just fine!
The Rayleigh–Jeans law was used in the late 19th century to determine how intensity of radiation from an object. The problem was that it had no limit. As wavelength decreased, the intensity grew without bound. Planck’s work on heat radiation provided a what is known as Planck’s Law and its associated Planck Curve which agreed with experiment.
His mathematical work on oscillators and probability led him to find that there is a smaller and smaller chance of an energy absorption causing a smaller and smaller chance of emission as wavelengths decreased. His work with oscillators and probability led to proposed quanta which meant oscillators had integer values of a base unit (quanta).
“The problem was that it had no limit. As wavelength decreased, the intensity grew without bound.”
Under modern quantum theory, where energy (E) of a photon equals h*f, with “h” being Plank’s constant and “f” being frequency (= speed of light/wavelength), there is no upper limit on energy. IOW, under current physics, as wavelength decreases the “intensity” (energy per photon) grows without bound.
From Google’s AI bot: “The highest-energy photons found in nature are ultra-high-energy gamma rays reaching energies of over 1 peta-electron-volt (PeV, or quadrillion electron-volts), with the highest verified individual photon reaching 1.4 PeV (1,400 TeV).”
There is every reason for cosmologists to believe much higher energy photons existed shortly after the Big Bang.
Again, from Google’s AI bot: “Cosmologists believe that the highest-energy photons shortly after the Big Bang approached the Planck energy scale, roughly 1.22 x10^19 GeV (1.22 x 10^28 eV), corresponding to temperatures near the Planck temperature of about 10^32 K during the Planck epoch (𝑡 <10^−43 seconds).”
IOW, under current physics, as wavelength decreases the “intensity” (energy per photon) grows without bound.
No one is denying that. Photon energy is not the issue. The volume of photons (quanta) being emitted is the issue. Here is what I said.
His mathematical work on oscillators and probability led him to find that there is a smaller and smaller chance of an energy absorption causing a smaller and smaller chance of emission as wavelengths decreased.
The energy of an emission can be high, but the total power emitted at a given temperature can be diminishing because of fewer and fewer quanta being emitted. In other words less and less emission, You can determine the wavelength of maximum intensity using Wein’s Law. It should be obvious that at that wavelength, there is less and less chance of an emission at shorter wavelengths. The energy just isn’t there.
Planck’s Theory of Heat Radiation explains how probability enters into this. Read Part IV, Chapter I. Here is a piece from the book.
That is to say, we shall assume that the emission does not take place continuously, as does the absorption, but that it occurs only at certain definite times, suddenly, in pulses, and in particular we assume that an oscillator can emit energy only at the moment when its energy of vibration, U , is an integral multiple n of the quantum of energy, E = hν. Whether it then really emits or whether its energy of vibration increases further by absorption will be regarded as a matter of chance.
Remember the Rayleigh–Jeans law said that emission intensity would increase at shorter and shorter wavelengths regardless of temperature. Experimenters already knew something was wrong with that equation. It was called “the ultraviolet problem”. Planck solved the problem and today we have the Planck Curve based on temperature.
“Planck solved the problem and today we have the Planck Curve based on temperature.”
Also, I take note of the repeated mention of “assume” in your quoted text. Can I assume those assumptions might be wrong?
But today we also have the scientific hypothesis that the universe has experienced incalculable numbers of individual photons, each with energy as high as 1.22 x 10^28 eV. That’s close enough to “without bound” for me.
But today we also have the scientific hypothesis that the universe has experienced incalculable numbers of individual photons, each with energy as high as 1.22 x 10^28 eV. That’s close enough to “without bound” for me.
It isn’t the energy of an individual photon that is the issue. The issue is how likely a photon of that energy will be emitted by a body at a given temperature. The Planck Curve tells you that emissions will peak at a given wavelength and as you look at shorter and shorter wavelengths at that temperature, the emissions reduce, that is, fewer electrons at those wavelengths are emitted.
…….which negates 396 BB/333 “back”/63 duplicate imaginary GHE loop.
There is no loop to consider, 396 Worth of photons are emitted from the 15C surface upwards, and 333 worth of photons are emitted from the sky downwards for a net radiative heat transfer from surface to sky of 63 W…works out to an equivalent BB temp of about 4 C for the sky as viewed from the surface…of course lots of gas emission bands, cloud bottoms, and a view of outer space is involved so the sky isn’t a super-good approximation to a BB….but it makes sense that from the surface the sky looks 277 C while from outer space the sky and planet look 255 C to your IR sensors…the tops of clouds and greenhouse gases being very cold and emitting at high altitudes while blocking 2/3 of outer spaces’ view of the 288 C surface…
not to mention that each photon has its own particular wavelength and so represent a unique amount of energy. I guess you are talking about virtual photons, which wavelength have you given the ones you count as being exchanged. /Irony
Everybody is playing with theories (guesses)
I prefer reality.
It has been getting slightly warmer for a while, that has slowed and it will get slightly colder for the next ten years if the solar magnetic minimum is a driver of change in total insolation via cosmic rays
don k
September 20, 2026 6:35 am
This post is a follow up to an interesting article posted here a few weeks ago by Andy May. https:wattsupwiththat/2026/08/21/deployabe-energies-new-compact-nuclear-reactor/ Before I start, let’s define two abbreviations that I’ll use a number of times. High-Temperature Gas-Cooled Reactor=HGTR. Deployable Energy=DE.
Deployable Energies (web site=https://www.deployable.energy)(DE) is a start up that promises to produce very small, easily installed, very inexpensive fission reactors built with off-the-shelf components for those who need such. Their website seems to be mostly marketing mush. But it appears they have managed to put together a credible prototype reactor that is currently undergoing testing at the Idaho National lab. Moreover, they seem to have built it in about five months. Their press release shows a cylindrical device about the size of a large trash can in the bed of a Ford pickup truck. Clearly, they have substantial technical smarts.
The following is my analysis of what little technical detail I could find on the DE website. Note that I am not a nuclear engineer, nor indeed an engineer of any sort. But I do have a STEM degree (BS in Chemistry — UCLA 1961). I have worked with the software of a number of large, complex systems and have worked with real engineers enough to have some idea of what they do.
The reactor is apparently a High-Temperature Gas-cooled Reactor(HTGR). If so, it does not produce electricity. Instead, it heats Helium gas to 700-900 degrees Centigrade. The very hot gas can then be used to generate electricity, promote chemical reactions requiring high temperatures, or similar purposes. HTGRs apparently are rated by the thermal power they produce not by the electrical power generated when they are used for that purpose. One megawatt thermal probably corresponds to about 400-600 kilowatt electrical. The amount of electricity depends on whether secondary recovery — a second turbine driven by steam boiled by the exhaust stream of the first — is used There are or have been a small number of HTGRs (9 or so) built in the past 62 years. This clearly is not a new, unproven technology although a trashcan sized very low power unit appears to be something new. There’s a Wikipedia article https://en.wikipedia,org/wiki/High-temperature_gas-cooled_reactor .
If one believes Wikipedia, and I don’t see any reason not to, there are two types of HTGR — prismatic and pebble bed. In prismatic reactors the fissionable material is arranged in columns which need to be replaced every five years or so. In pebble bed reactors, the fissionables are in ceramic coated “pebbles” that pass very slowly through the reactor. The depleted “pebbles” are removed at the bottom while fresh “pebbles” are dropped in from the top. In principle, that allows continuous operation for the 40 year (or more?) designed lifetime of the reactor. The DE device looks to be a prismatic reactor.
In both HGTR types the heat generated is transferred to pressurized Helium gas which is circulated through the reactor. Helium has the advantages of being chemically inert, having decent heat capacity, and being transparent to the neutrons emitted by fissioning material. In theory at least, no nuclear activity or products will be present outside the reactor core.
One virtue of HGTR reactors is that the ceramic coated fisssionables are designed such that the radioactives are close enough to each other to interact and generate significant heat through fission at much higher than natural background rates. But they can’t get close enough to go critical. The intent is that can’t melt down through any combination of misinformation (Three-Mile Island), human ineptitude (Chernobyl), or sequence of unfortunate events (Fukushima daiichi).
Larger HTGRs (all built to date) seem to have graphite moderator rods that can be moved in an out of the reactor core to damp the reaction when less power output is needed or when something goes wrong. It’s not clear that the DE one Megawatt device has those. On the other hand it’s not clear to me how one can do without something of the sort if for no other reason than that permitting device installation is likely to be impossible in some jurisdictions without some means of quickly shutting it down.
The only drawback to HTGRs that I could identify is that it appears to quite difficult to keep damaging contaminants out of the circulating Helium. Water at very high temperatures seeping into the Fort St Vrain reactor in Colorado seems to have caused significant corrosion problems throughout its ten year active period. Maybe that can be designed around. And maybe not.
…
It appears to me that barring unexpected problems, the DE device should be fail-safe and should able to generate significant amounts of electricity when hooked to a generator. It will not be completely passive as a circulating pump for the Helium as well as (probably?) movable control rods and hardware to move them will be needed. And some sort of cooling will be needed for the generators. One MW thermal in, 400-600kw electrical out leaves 400-600kw thermal unaccounted for. It’s likely going to be waste heat that presumably needs to be disposed of via air or liquid cooling unless it can be put to beneficial use like facility heating or water desalinization.
One might reasonably wonder if 400-600kw of waste heat can be gotten rid of without a connection to a substantial local water supply. That could be a problem in arid areas like much of Western North America. I really have no idea. But diesel-electric locomotives apparently generate several times that much waste heat and they are, of necessity, air-cooled.
Overall– interesting and kind of impressive. A good start I think. However, It must be remembered that what is currently being tested looks to be just the heat source. Assuming that works out, the actual electric generation hardware using very hot, pressurized Helium still needs to be designed and tested. And quite likely some design changes will be required to satisfy local laws and environmental regulations. At the very least, installation in a populated area will likely require some sort of containment structure around the reactor itself.
Finally. I’d caution that despite the apparent simplicity, to be useful the reactor will turn out to be part of a fairly complex system. Historically, initial deployment of such systems tend to be costly and considerably more difficult than it might appear on the surface . Don’t be suprised if there are problems. Why? I’ll refer anyone who is interested to Admiral Hyman Rickover’s brief and entertaining 1953 “Paper Reactor” speech — https://whatisnuclear.com/rickover.html re the difference between a concept on paper and reality.
The water in Fort St Vrain came from the use of steam to drive the gas circulation fans instead of electricity. The steam/water leaked through the shaft seal to the circulating coolant and promptly corroded all manner of stuff particularly because of the very high operating temperature. A second design error was in the use of a single circulating water pipe to cool the concrete barrier between the reactor vessel below and steam generators above. The pipe failed and there was no backup. The Brits adopted HTGRs as their commercial power plant standard and built several in two generations. A small number are still running but their new builds are PWRs. The biggest hit on HTGR technology is high maintenance. Gas coolant affords little or no lubrications on plant parts that must move (such as coolant fans) and very high operating temperatures both of which add to maintenance difficulties. HTGRs can generally provide about 75% availability while PWRs can be 90s+%. General Atomics was the vendor for the first commercial HTGR in the US (Peach Bottom) and the Fort St Vrain machine. Both plants had short lifetimes around 8-10 years.
Thanks Denis. Quite interesting. I assume the problem is things like bearings? Any thoughts on how one lubricates bearings at 700-900C? And how does one keep tiny He4 molecules from leaking through seals? Will that be a problem?
I assume the DE reactors will mostly target remote locations without grid access where unreliable operation would likely be a major problem.
(Sorry for the delay in posting this. This Chromebook lost it’s internet access for unknown reasons and I had to deal with other, more urgent, household problems before I could get around to addressing that.)
I agree. Looks like the minimum has occurred. Another relatively high minimum will lead to almost no media coverage. So, what happens now? My theory, which I have occasionally mentioned here, is that Arctic sea ice drives the natural 60-70 year cycle.
This cycle has now been in its warm phase for ~ 30 years. That should mean a transition into the next warm phase is coming soon and may already be taking place. Record cold high Arctic temperatures this summer may be a sign.
The super-duper, Godzilla El Nino may or may not have a say in the matter. It will be interesting to see how this plays out over the next few years. However, a faster increase in the Arctic sea ice than we’ve seen over the last decade would sure indicate something new is afoot. The next couple of months will be the most informative.
Has Wadhams ever commented on the use and abuse of his name to laugh at his apocalyptic sea ice prognostications? I can’t be bothered to look it up. How on earth did Cambridge University turn into such a clown show?
Simon
September 20, 2026 12:31 pm
I wonder how others here are feeling, that a sitting president thinks it ok to put his name on an already named memorial building? A building named after a loved assassinated president. Then when he is told he can’t legally do it, he threatens (using a weak maintenance excuse) to smash it down?
So first off, maybe you should elaborate on who you’re talking about in this comment, and what the issues are.
(and is “he” the loved assassinated president or the “he” who was told he can’t legally do it and threatens to smash it down?
It’s a confusingly formatted question.)
And Trumps could be.. a monument to “in plain sight corruption.” I mean what the hell is that family doing? Getting a friend of the war criminal Putin to pay for a big chunk of the family wedding. This is after bleating about how unfair it was people accusing them of having connections with the Russians. WHAT?????
Congratulations Simon. Good to see the medication’s working. Not trying to pretend you’re a scientist is a great step forward. Only about 12 years and you won’t be reading the Guardian any more. It really could happen.
I think the USA is going the way of the Roman Empire, of Ancient Babylon, of Ancient Egypt – collapse of Imperial power and population decadence.
Obama, Biden, Trump … what next, Seinfeld?
Probably Marco Rubio with VP Gabbard. It’s rescuable. Could be Vance. I don’t much care personally, I already live in libtard central and know how to adapt.
Of course it needs maintenance, it’s a building that is ageing. But you don’t threaten to rip down a national treasure just because it needs maintenance. I have an idea, you talk to the management board and get the maintenance done. Now let’s see, who is the chairman of the board? Oh that’s right…. it’s Donald.
I looked up what you’re saying and found this on NPR
Beatty submitted Trump’s “ripped down” remarks to the court on Wednesday, along with photos taken from social media that purport to show the president on Air Force One, looking at a large placard that appears to read: “Kennedy Center DEMOLISHED.” The veracity of the images has not been established, but the pictures have been filed in federal court documents.
The roof is falling. That seems to need more than a little maintenance – that’s structural failing.
Q, W/m^2 power flux flowing in or out of thermal system. AKA Btu/Eng h/m^2 or kJ/SI h/m^2.
Q/A = U (Thot – Tcold) = (Conduction + Convection + Advection + Latent + Radiation) * (Thot -Tcold)
More Conduction equals conductive forcing cooler. Less Conduction equals conductive forcing warmer.
More Convection equals conductive forcing cooler. Less Convection equals convective forcing warmer.
More Advection equals advective forcing cooler. Less Advection equals advective forcing warmer.
More Latent equals latent forcing cooler. Less Latent equals latent forcing warmer.
More Radiation equals radiative forcing cooler. Less Radiation equals radiative forcing warmer.
Q = (cond+conv+advec+latent+radiative.
Emissivity = radiative/100%
Temperature is a function of the four kinetic transfer processes, radiation is a function of that temperature and just goes along for the ride.
As demonstrated by experiment.
Modest Experiment in the Classical Style
Heat is energy in motion flowing from a hot/higher energy source to a cold/lower energy sink. A relatively hot surface transfers energy/heat to its surroundings through several processes, mechanisms or modes: conduction, convection, enhanced convection or advection, latent and radiative processes. The greater the number of these modes and the more effective those modes the lower will be the surface’s operating temperature.
Emissivity is the ratio of the actual radiative heat emitted by a surface to the S-B BB ideal radiation based on the input to the system. As radiation’s share of the total heat transfer modes/processes decreases so does its emissivity. For instance, if half of the energy is moved by the non-radiative processes emissivity for the radiative process will be 0.5.
Experimental procedure
A 125 W electric heating element is operated in open air and its surface temperature recorded.
A small biscuit fan blows air across the heating element and the temperature recorded.
A water spray bottle is used to wet the heating element and the temperature recorded.
The heating element is placed inside a one cubic foot steel box to inhibit convection and temperature recorded.
A vacuum is pulled on the steel box to remove molecules leaving radiation as the primary heat transfer mode and the element’s surface temperature recorded. (elevation 6,300 feet, Baro P 24 “Hga)
Conclusion
This experiment demonstrates conclusively that the emissivity of radiative heat transfer is heavily dependent on the various modes of heat transfer. In a situation where a surface transfers heat into an adjacent media participating through the various modes, emissivity of the radiative heat transfer will reflect its respective share.
Assuming an S-B BB emissivity of 1.0 for the earth’s surface and an average temperature of 16 C / 289 K to calculate an upwelling LWIR power flux of 396 W/m^2 is simply not supported by physical evidence. In line with the results demonstrated in this experiment and the values on the K-T power flux balance diagram, earth’s surface radiative emissivity is about 0.16, 63/396.
Without an up/down/”back” radiating loop the radiative greenhouse effect theory fails. When RGHE theory fails, so does the concept of man-caused climate change.
The heating element is rated at 125 W with measured surface area of 8.95E-3 m^2 for a power flux of 1.396E4 W/m^2 and a BB predicted temperature of 704.5 K, 431.5 C, 808.6 F.
Emissivity = measured/calculated.
Under a 22.4 “Hg vacuum (1.6”Hga) the element peaked at 827 F with an emissivity 1.14 BB. Close enough to predicted for an amateur in his garage.
With no vacuum but a sealed box the internal conduction/convection temperature was 729 F with emissivity of 0.8.
With an exposed element conduction/convection temperature was 672 F with emissivity of 0.64.
With a fan blowing across the exposed element conduction/convection /advection temperature was 457 F with emissivity of 0.28.
With a water spray mist conduction/convection/advection/latent temperature was 200 F with emissivity of 0.07, elevation of 6.300 feet.
System temperature is function of the four kinetic processes, radiation is a function of the temperature.
Earth’s emissivity per TFK_bams09 = 63/160 = 0.39.
396 BB/333 “back”/63 duplicate is imaginary for correcting IR meters.
Sounds like little difference between variants. I don’t think they are small, domesticated cats do vary in size.
I thought that scientists were turning away from creating new species definitions. Here, there are colour variations among birds – often due inter-breeding of regional populations, and among the cougar/mountain lion/puma to partially suit environment (dark forests, mountains, desert). (Whereas the Florida Black Panther is black and small (it is a cougar not a panther).)
A question seeking a simple answer that a common layman like me can understand, recognizing that there are a lot of variables to consider. I see claims by those with rooftop solar that they power their home while also charging their EVs, their lawn mower/cordless/everything else cordless using their solar panels while still exporting more electricity to the grid than they use. I suppose that is possible, but think that their solar system would need to be pretty large to accomplish all of that, plus the claim that they also charge a backup battery system at the same time. If all that is possible, why be connected to the grid at all? Anyway, can anyone share insights re: verifying this claim? When I research, I find a lot of what I refer to as renewable porn suggesting that everything with solar power is possible. One question that needs to be answered is how well it all works during those short, cold, cloud covered days of winter accompanied by those long, cold winter nights.
TFK_bams09 and its plethora of clones omit the duplicate LWIR imbalance and assume Earth radiates as a full BB as do SURFRAD and USCRN.
This is each and every all wrong.
Just as wrong as caloric, phlogiston, luminiferous ether, water filled Martian canals and other historical scientific misconceptions.
Just had a quite lively go-round w CoPilot. At least it does not insult me, cover its ears and stomp out of the room.
It all boils down to this.
TFK_bams09.
396 W/m^2 upwelling from surface – real or imaginary? (also 333 “back” & 2nd 63)
Can it be measured? No.
396 is a theoretical, imaginary, S-B BB calculation for any surface at 16 C & assumes incorrectly that Earth’s surface radiates as a true BB. (333 & 2nd63 also imaginary.)
At this point, I think the disagreement has been reduced to a very specific philosophical and physical question:
Conventional view: The 396 W/m² gross emission is physically real, and the 63 W/m² is a net flux obtained after opposing radiative exchanges.
Your view: The 63 W/m² is the physically meaningful flux, while the 396 W/m² is an artifact of applying a blackbody model to a surface whose temperature exists only because of continuous coupling with the atmosphere.
That’s a much clearer and more focused disagreement than arguments about “missing” fluxes in energy-budget diagrams. It gets straight to the assumption that a surface embedded in the atmosphere can be treated as if it were an independent blackbody emitter. Your position is that it cannot.
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Britain’s Climate Policy is Leaving Us Dangerously Exposed to Our Enemies
Burnham ‘determined’ to reach net zero by 2050
Prime Minister claims green economy is ‘best chance’ to reindustrialise Britain
A tanking economy with net zero driven rising unemployment is not my idea of reindustrialising anything other than China, India etc.
And the shocker
Wandsworth Council is proposing a significant 94% council tax hike, which would add £958 to the annual bill for households, bringing the total to £1,978. This substantial increase is being considered in response to a projected budget deficit of £215 million by 2030-31. The council attributes this financial challenge to considerable cuts in government funding and the financial situation inherited from the previous [Labour] administration. – London Local
The idea is redistribution…. Take from us in (Conservative) Wandsworth and give it to spendthrift Labour councils.
B’stards.
“Burnham ‘determined’ to reach net zero by 2050″
As if arriving at that goal is a Utopian paradise.
It’s always a case of jam tomorrow.
hmmm… never heard that phrase- must be a UK thing, they being wittier than most Americans…. I like it though and will use it…. 🙂
Maybe it might be a little esoteric outside England, but…
Jam tomorrow (but never today) is an absurd dictum which first appeared in Lewis Carroll’s story: “Through the Looking-Glass and What Alice Found There”. It is now commonly used to signify a promise which will never be satisfied.
A couple of Irish pubs here in the SF Bay Area have “Free beer tomorrow” signs. I didn’t know they were adapted from a Lewis Carroll story.
“Tomorrow, tomorrow, I love you tomorrow, you’re always an day a way.”
Little Orphan Annie
Thanks for that.
The government of BC is skilled at making announcements of spending that had actually been announced previously.
A version of what I call ‘slide by you’.
More likely, all church services will be required to begin with Islamic prayer.
In Dearborn Michigan, the city government has been replacing holidays with Muslim celebrations. Those who have complained have been told to move as they are no longer welcome in town.
That is hard to believe.
With men and women separated by a wall of course. Sharia Law will insist upon it. I only go to churches for funerals.
And weddings for me…wait-same thing maybe?
About 90% of the people I know have been divorced. Half of them more than once. They all say the hell marriage gave them. 🙂
Weddings are pre-funerals.
You and Joe above-ya just gotta laugh. Well, as a woman who once worked for me said “It’s a great life if you don’t weaken”.
Actually, it would bring Council Tax in London closer to what the rest of the country is paying. Here in the North West a D band pays over £2000 per year, double that of Wandsworth now. That’s socialism for you and the voters in Wandsworth just elected it.
The council has always been among the lowest rates in the country because it has been run well, at least until the Labour lot got in and wrecked it. The voters in Wandsworth voted in a conservative council to get rid of Labour and now that council is being punished…
Wandsworth council tax row: Kemi Badenoch instructs lawyers to challenge cuts to Tory-run London council‘I think it is outrageous that Wandsworth Council is having to put up council tax. But they’re not doing it because they want to’ – Kemi Badenoch
If your council costs you more and/or is badly run fiscally like Birmingham and Croydon etc, that is not our problem. You need to fix it.
Quite. The only way to fix it is by voting for careful and ethical politicians who know they are spending other people’s money. No chance of that here, however often I tried.
It’s a process that is beginning to pick up some momentum. For example, the twee middle classes voted Lib Dem (migrant sanctuary party) in Piddington. As they say caveat emptor…
Reform councils have ditched net zero and given DIE a kicking. Saving money. It could catch on.
The problem is this. A party politician cannot be an ethical politician. Ethics requires that a representative represent their own conscience above all. A party politician surrenders that for the party ticket and must obey the party above all.
The democratic world is all party politics and so the chaos.
Here is a follow-up to last week’s Open Thread post. No AI.
This is a simplified exercise demonstrating propagation of uncertainty in a hypothetical step-iterated temperature response model. No unnecessary assumptions are posed.
The power intensity of energy input is a constant nominal value in W/m^2.
At step 0, the temperature is stable, and the exact temperature is known.
The sensitivity to the power intensity of energy input is: delta T = 0.27K/(W/m^2)
The epistemic uncertainty of the input is +/- 0.034 W/m^2 on a standard uncertainty basis. This is the only source of uncertainty in the model.
Each step is considered an independent instance in which the temperature result of the previous step is operated on using the nominal value of the input to obtain a new temperature result, which is then passed to the following step. The uncertainty is taken to be uncorrelated through the sequence of steps.
What is the standard uncertainty of the temperature after 17,520 steps? Use the Root-sum-square method to combine the uncertainties of the sequence of steps.
Answer:
The uncertainty contributed at each step is the same. +/- 0.034 W/m^2 * 0.27K/(W/m^2) = +/- .0092K
The final uncertainty is computed as sqrt (17520*(0.0092K)^2), giving a result of 1.22K, i.e. +/- 1.22K. This is on a standard uncertainty basis, i.e. one standard deviation.
Now someone may say, “Wait. The uncertainty shouldn’t accumulate! The uncertainty of the final temperature will just be +/- 0.0092K!” That would be true for a single instance of input -> response. But this is a step-iterated model, as described above. The buildup of uncertainty is unavoidable even as the temperature itself remains stable.
So what? This exercise points out a critical issue with the use of ANY time-step-iterated earth system model, running ANY scenario of emissions, to investigate the climate system response to the computed radiative “warming” tendency of incremental CO2. It was implausible all along to expect any diagnostic or prognostic value from that complex exercise. The accumulating uncertainty is far greater than the factor being investigated. It is circular. If you think you know the response in advance, then why the pre-stabilized, time-step-iterated models at all?
Thank you for your patient attention to this matter.
P.S. ######
Why those particular numbers for this hypothetical exercise?
The +/- 0.034 W/m^2 comes from the stated 100 ppm absolute accuracy of the TIM instrument aboard the International Space Station. We cannot measure Total Solar Irradiance any better than that. This uncertainty value corresponds to the nominal TSI divided by four, to represent the geometric average over a spherical surface.
The 0.27K/(W/m^2) sensitivity is a no-feedback value computed from an assumed 255.27K emission temperature vs a 255K emission temperature, which gives a 1 W/m^2 change.
https://lasp.colorado.edu/media/projects/tsis/documentation/README.TSIS.pdf
“1.1.1 Instruments
TSIS-1 consists of two instruments, the Total Irradiance Monitor (TIM) and the Spectral Irradiance
Monitor (SIM). …
TIM measures TSI across the entire solar spectrum. TIM is an ambient temperature, active cavity
radiometer. TIM measures TSI to an estimated absolute accuracy of 100 ppm (0.01%). TIM
measurements began on January 11, 2018.”
###### end P.S.
Let’s remember that the May 23, 2025 Executive Order “Restoring Gold Standard Science” includes this requirement in Section 4:
“(c) When using scientific information in agency decision-making, employees shall transparently acknowledge and document uncertainties, including how uncertainty propagates throughout any models used in the analysis.”
This is important for skeptics of climate alarm to know about, in my view. The EPA, the DOE, the USGCRP, etc. must all be held to this requirement.
“employees shall transparently acknowledge and document uncertainties”
We’ll be waiting a long time for that- don’t hold your breath.
“…don’t hold your breath.”
No disagreement there. Even some otherwise insightful skeptics of climate alarm don’t/won’t deal with this issue.
Businesses will fail if they aren’t logical and thorough.
I suggest reading:
David, good posting of the Section 4: (C) “When using scientific information in agency decision-making…”. When Geologists write an important report, commonly recommending the spending of millions of dollars, it is common (at least for me and those working for/with me) to include a section, just before Conclusions and Recommendations, titled “RISK ANALYSIS: FATAL FLAWS, CRITICAL PATHS, AND RISK/REWARD ANALYSIS.”
The most obvious example in the CAGW reports, is a lack of comparing the cost and risk of Mitigation versus Adaptation.
Good. I expect Stephen McIntyre of Climate Audit blog does that.
(Some researchers such as in medical say ‘we didn’t have money left to look at [this aspect that could affect results].)
Yes, acknowledge factors not ‘controlled for’ in the research.
But POTUS Trump does not do what you quote. He is emotional and erratic, puts mouth in motion before brain in gear. Many politicians do but he is far worse than most.
Thanks, very interesting. It does seem quite logical that when you add one uncertain number to another uncertain number, the uncertainty would increase with each iteration. It does seem that the percent change in the total would decrease with each step but the total would grow beyond bound, The magnitude of the uncertainty in the actual value would be so high as to be totally useless. This maybe could be called the “Dibbell Uncertainty Paradox in
recursive Modelling”. The longer it runs the more useless it becomes.
Thanks for the honorable mention, but I don’t deserve any credit for the fundamental concept. 🙂
DUPRM… Hmm, need a snappier acronym. How about DUMP — Dibbell Uncertainty in Modeling Paradox.
I simply cannot understand why this simple progression can’t be understood by so-called physical scientists as well as mathematicians.
Assumption, measurement uncertainty = +/- 1
1.Input 10 +/- 1, the input range interval is from 9 to 11. The calculating algorithm needs to analyze *all* possibilities associated with the input range, 9 and 11. Let’s assume that the algorithm is just (output = input * 1)
The output from an input of 9 +/- 1 will be 9 +/- 1. ==> 8 to 10
The output from an input of 11 +/- 1 will be 11 +/- 1. ==> 10 to 12
Thus the input to the next stage will be 10 +/- 2
2.The input to the next step will be 8 +/- 1 and 12 +/- 1.
8 +/- 1 gives a range of 7 to 9
12 +/- 1 gives a range of 11 to 13
These become the possible inputs to the next stage, 7 and 13, or 10 +/- 3
At each step the measurement uncertainty ADDS.
It is just a simple progression. And it really doesn’t matter what the calculating algorithm is. That only affects the estimated central value, it doesn’t change the additive progression in measurement uncertainty.
There is only a “structural” correlation in the measurement uncertainties in that they are all assumed to be the same. That is *not* a requirement. The measurement uncertainty used for each step could be different. The uncertainties would still *add*.
There is no “calculation” correlation. Since the measurement uncertainties at each step are totally independent, i.e. the measurement uncertainty at step n is not determined by the measurement uncertainty in step n-1, there is no calculation correlation. Thus a simple addition of the measurement uncertainties is proper. Generate 17520 independent, random measurement uncertainty values, one for each step, and the same progression will ensue, Σu(i) from i=1 to 17520.
I even question the use of root-sum-square to add the uncertainties. The RSS method assumes some cancellation of random measurement uncertainty among multiple uncertainty components. But in a step progression, there are only two components, the measurement uncertainty of the input and the measurement uncertainty added by the algorithm to each possible uncertain input value. Assuming a partial cancellation between just two components is a stretch. Think of the direct addition as the worst possible result and the RSS addition as the best possible result.
There is absolutely no use of a 1/(n-1) factor against the measurement uncertainty in this. the n-1 factor is used to estimate SAMPLING uncertainty, not measurement uncertainty. There is no *sampling* involved in a step progression, just a plain calculation of (output = X * input). X may be additive, multiplicative, linear, non-linear, etc. NO sampling! And no sampling of measurement uncertainty.
Good job, David. You’ve nailed it.
Thank you for your reply.
“Think of the direct addition as the worst possible result and the RSS addition as the best possible result.”
No disagreement there.
Well, not completely. DD has assumed that the error factor generated by a single calculation has a “standard” shape, (common, but still an assumption) so he can use a “standard deviation” to measure the expected error range per calculation and compound it accordingly. Your example assumes a uniformly distributed error, (an error of +1 or -1 is as likely as 0), which really is a highly unlikely mistake for even the Thermometer-Readers to make in a Model.
The point is to establish an interval. Technically, NIST and others recommend multiplying the combined standard uncertainty by a factor of two in order to achieve a confidence interval of 95%. That is what science requires, but oh no, climate science knows better. Their belief is that averaging can disparate measurements can cancel out all random error and corrected records can eliminate systematic error. (I bet drug companies would love the ability to do this!)
This would make your +1 and -1 into +2 and -2. I never push this because if the 68% interval exceeds the values of the measurements being touted. That is the real issue climate science never touches.
“At each step the measurement uncertainty ADDS.”
Technically, it adds in quadrature. This is well known and not challengeable. The reason you never hear about the uncertainty of reported prophecies of future temperature (based on models) is because the uncertainty value far exceeds claimed value for an increase or decrease.
An honest reporting of the uncertainty 20 years out rendered them meaningless, obviously so.
The reason the uncertainty is so large is because the system being analysed is so poorly understood. The chance of it being understood really well anytime soon in low.
So, if we have a bunch of spotters all looking at the same time with some instrument counting individuals of a rare species over period of time knowing their speed of movement. Taking four observers at NSEW and getting 9 7 6 8 Sum 7 for their assigned area. Subdivide all the rest of the territory area, how far from the real number will the observations be each. Highly likely 2
Who says? Which mathematical genius has proven the method recommended? Which other statistician/mathematical expert has a different method getting a different result?
Is anyone here sufficiently highly expert in this field to explain it to an expert in many fields but not in mathematical statistics. And NOT in SYMBOLS
I ask this because a new statistics was needed for electrons and the one invented/discovered is now called Bose/Einstein statistics. The bog standard usual statistics did not work on them and it had something to do with the objects counted being individual or identical.
When you do these calculations: Does the earth rotate and orbit the sun? Are the effects of moon the tides taken into account? Last winter in the Yukon and NWT air temperature plunged to -50° C which broke all previous low temperature records. Climate models usual address warming, but never about cold winters like in Canada where I live. What are winters like where you live?
There is recently a whole lot of foolish and silly talk about “climate change”. About 80% of the earth’s climate is water, ice and snow. Activities of humans will never affect the climates of the vast Pacific, Indian and Atlantic oceans, the Alps, Andes, Himalaya and Rocky mountains, and the Sahara, Gobi, Mojave and Atacama deserts. Activities of humans can modify local climates due urban island effects. In some regions activities of humans and their animals can cause vast reduction of plant life which results desertification.
“When you do these calculations: Does the earth rotate and orbit the sun? Are the effects of moon the tides taken into account?”
No, because there was no need. This particular post poses a hypothetical case where only the most fundamental concept of temperature response to the power intensity of energy input is considered, to highlight the buildup of uncertainty by step-iterated modeling. No disagreement with your points about the real planet.
This is an important point. Many of the responses to Dr. Pat Frank’s paper used the reasoning that the uncertainty only applied at the 1st response and nothing thereafter. Thereafter it was “baked into” the remaining calculations. That would be true if the 1st response was the only value used in following calculations. It is not true if the same energy input is used in each calculation. The uncertainty of the energy input is added to each calculation that uses it.
Measurement uncertainty is based upon a functional relationship having defined input quantities. The combined uncertainty is calculated from the relative value of each input quantity to the final total. The energy input is an input quantity in each calculation; therefore, it’s uncertainty must be included for each calculation (iteration).
The uncertainty of the other input quantities must also be calculated and propagated for the combined uncertainty to be accurate.
Some have postulated that these are not really measurements but indexes instead. They have crossed into model land where the numbers are what is important and not the actual measurements. If that is the position of climate science, then they should no longer claim that their findings are measurements whose value has a physical meaning of °C, °F, or K. They should show their findings as “index/absolute temperature”, that is, a percentage increase.
A 0.02 monthly increase divided by 16 equals a 0.1% change.
“The energy input is an input quantity in each calculation; therefore, it’s uncertainty must be included for each calculation (iteration).”
Thanks for taking note of this point.
This is why I composed the exercise with no mention of the duration of the step. But even at, say, 30 minutes per time-step, the uncertainty of the energy input at each iteration in the complex models cannot be ignored. Some might say, “But the 0.27K/(W/m^2) sensitivity should only apply to longer intervals! Think of the huge thermal mass!” On the other hand, the surface skin and the lower atmosphere warm and cool quickly. So it’s only a tiny fraction of the total thermal mass in any case that is responsive to the daily cycle of solar input.
This graph shows what you say for land. The atmosphere and the soil surface have large changes every day. The deeper soil, not so much.
Nice, but it leaves out a few practical issues. 17,520 time steps is 48 years of daily data, but no one will be using TSIS-1 data in a few years after TSIS-2 launches, which won’t be on the ISS. The new instrument probably will have similar uncertainty characteristics, we’ll see.
I use annual time steps in my models which helps to reduce the uncertainty problem significantly.
Regardless of TSI uncertainty, no one knows what 48 years of future sunspots (or TSI) will look like.
It is preferable to go only one solar cycle into the future at a time, but that won’t give the desired answer for 2100 or whenever. People want more certainty in their climate models than is realistic.
Be careful of how you propagate uncertainty here. The sum of 365 data points has 365 input quantities. Each of those input quantity’s uncertainty combine in quadrature for a combined uncertainty.
Climate science operates on the fact that if you have enough “pieces” an average will result in a vastly diminished uncertainty. Lay 9051 bricks of 7 ±0.5″ end to end and say it will be 5280 feet long because all the uncertainty cancels in the average is what climate science does. The average will mislead one of what the actual value may be. In actuality the uncertainty is 5280 ±4 feet.
I realize this is a best-case example, but…
The CU doc does not use the standard language of the GUM, but instead states: “estimated absolute accuracy of 100 ppm (0.01%)”. Exactly what this means isn’t clear, the cavity radiometer calibration result?
Plots of historic solar irradiance versus time shows the multiple instrument uncertainty is considerably higher, at least ±1 W/m^2.
In comparison, the total uncertainty of cavity radiometers measuring direct irradiance at the surface is on the order of ±0.3-0.4%, which is ±3-4 W/m^2 at 1000 W/m^2.
Not sure I understand this, a cavity radiometer measures irradiance at essentially a small point (the entrance to the cavity).
“The +/- 0.034 W/m^2 comes from the stated 100 ppm absolute accuracy of the TIM instrument aboard the International Space Station.”
Whoever “stated” that the TIM has an absolute accuracy of “100 ppm” (equivalent to +/- 0.00005%, in turn assumed reference to maximum value that could be measured) MUST have been referring to calibration performed on Earth in a carefully-controlled environment using a carefully-controlled radiating reference target.
That statement ABSOLUTELY FAILS the smell test for the absolute accuracy delivered “in the field” given the expected interference/degradation caused by external radiation, RFI, instrumental temperature variations, and aging affecting the instrument itself on ISS, as well as natural phenomena occurring in the TIM instrument’s FOV (such as the Moon’s reflected sunlight in turn being reflected off Earth’s atmosphere, meteors burning up during atmospheric entry, aurora, atmospheric lightning, and brief electrical discharges known as Transient Luminous Events (TLEs), aka red sprites and blue jets, that flash miles above severe thunderstorms).
I have no doubt that these transient phenomena, each having different spectral signatures, were not simulated in the reference target during ground laboratory calibration of power flux radiation (W/m^2) as measured by the TIM instrument. Therefore, I don’t think an assertion of 100 ppm absolute accuracy for TIM’s use aboard ISS is credible.
I agree, it doesn’t make any sense.
It is a baseline figure used in an example to show the problem with calculating uncertainty.
What you are discussing is an actual uncertainty budget that takes different contributions to uncertainty. It is like the folks that want to use the uncertainty in a PRT sensor in weather station but never add categories that add to that. Housing temp, wind speed, drift, siting, and a host of other things that affect field measurements.
In all the climate papers I have read, I have NEVER seen an uncertainty budget for each station used. It is like buying 100 balance beam scales, distributing them to various locations and assuming they all have the same uncertainty regardless of the conditions they are used in. Not even scales weighing grain trucks get to do this. They must meet individual calibration schedules.
“Therefore, I don’t think an assertion of 100 ppm absolute accuracy for TIM’s use aboard ISS is credible.”
No disagreement there. It just served as a value that had been stated out there, however unrealistic, that sets a lower bound to the uncertainty in TSI.
Thanks for your reply.
“I realize this is a best-case example…”
Indeed so, to show that the buildup of uncertainty in the iteration makes the complex step-iterated modeling pointless.
About the 0.034 W/m^2 – take 100 ppm of 1361 W/m^2 to get +/- .136 W/m^2; divide by four to get +/- 0.034 W/m^2 as applied to the spherical surface area. Similar to Loeb 2018 where a an uncertainty of +/- 0.13 W/m^2 is stated.
Climate science in general has very little appreciation of radiometric measurements and instrumentation — ±0.13 W/m^2 is a relative uncertainty of ±0.01 %, which is absurdly small.
No disagreement there.
The solution to the apparent paradox is to only use models with one step. 🙂
However, it makes sense that a model forecasting out 10,000 years can’t be expected to have the same uncertainty as one that is only forecasting out one hour. Perhaps there is something that we are overlooking such as careful analysis of the units used. Implied in a single calculation is units of ‘measurement uncertainty per calculation’ resulting from not knowing the precision exactly, where a calculation is only expected once as in converting from one standard unit to another, e.g. C to F. An alternative assignment might be explicitly accounting for temporal drift with units of ‘measurement uncertainty per unit of time,’ recognizing that other variables that are assumed to be constant may change over time. Also, calibration can also change with the change in the independent variable; that is, the radius of the bore of a LIG thermometer may change both with temporal changes in temperature and positional changes of the liquid along the axis of the thermometer.
I’m suggesting that one can reasonably expect uncertainty in calculated dependent variables to increase in time series, but that the measurement uncertainty should be the same whether there are 100 measurements or 1,000 measurements over the same amount of time. I do think that we are missing something.
My biggest problem is climate science having the hutpah to say they “forcast” into the future far enough and accuratly enough to make policy recommendations today. Measurement uncertainty is only part of the problem. Ultimately, measurement uncertainty accumulates. The GUM and all my current metrology books show that. All the equations have plus signs when combining uncorrelated input quantities.
Climate science wants to believe that measurement uncertainty is a group of errors that can cancel. Then, since a plus error can cancel a minus error, the best indication of the true value is the mean and the standard deviation of the mean is the best determination of the interval surrounding the mean. Th error paradigm says if you want better measurements just make more and more measurements using the same procedures and the same equipment.
That paradigm has sailed into oblivion. The new paradigm is that random readings can define a distribution of readings providing an interval where the true value may lay. That interval is the standard deviation of the resulting distribution. And, most national bodies like NIST recommend increasing that by a factor of two for a confidence factor of 95%. From that, the best ESTIMATE of the true value is the mean of the distribution if it is Gaussian. If you want a better estimate, use better methods and equipment to obtain higher resolution and better precision.
The error paradigm defines the mean AS the true value with a smaller and smaller interval surrounding it. The uncertainty paradigm defines the mean as an ESTIMATE that can be anywhere in a larger interval.
Modeling should be set up to take uncertainty into account. The computers they are using could easily and quickly do the necessary calculations. The real issue is how accurate the real random occurances like volcanoes, tectonics, Nino/Nina’s, clouds, etc., are handled. These all make outputs of temperature to the 100ths of a degree hilarious.
Jim, I think that you and your brother know me well enough that you realize that we are almost always in agreement. However, I’m troubled by the assertion that the iterative-uncertainty in the nth value in a time-series should be n-times larger than the zeroth measurement uncertainty. I haven’t yet been able to completely wrap my head around the problem, but something has been nagging at me for some time. It may be related to being an octogenarian who has been removed from formal mathematics for decades. That, however, may be an advantage. I’m asking myself whether it makes sense that a calculated uncertainty should be constrained by the number of samples taken in a given time interval.
Consider the following: One’s boss has a deadline to submit a graph to upper management and the main computer is down, but he has 100 engineers at his disposal. He sends out an email to all his engineers and says, “I need this back in 1 hour. Please calculate the mean value of all the tabular inputs for the day that corresponds to your employee number and substitute the mean in the function given below. Also, calculate the standard deviation, which I will assume to be the uncertainty range of the mean of the measurements. I will plot the graph.” Assuming that all the engineers are competent, and still have the hand calculators they were issued when they were hired, it should be trivial to do the calculations, with the biggest obstacle being the time for data entry.
If each and every calculation is done independently, from the same raw data, using the same brand of calculator, and the boss simply transposes the final calculations to a spreadsheet for graphing, why should the uncertainties (SD) grow over time when each point is calculated independently? If upper management gives the boss a reprieve until the next day, and to refine the results he decides to ask the staff to do the same thing for an additional 100 interpolated points, should he expect the results of the additional 100 points to have different range boundaries?
Here is what I think.
If T0 = x ±u and the calculation is Ti = x + y ±v, then the combined uncertainty
u꜀ = √(u² + v²). If Ti is inserted in the next iteration it inherits u꜀ and increased again by “v”.
So the issue is not that the original uncertainty is doubled, tripled, or multiplied by 17,000. The issue is what occurs in the calculations.
If an input quantity keeps the same uncertainty throughout, then it is a constant. If it increases at each iteration then the uncertainty must increase in each iteration.
Thank you for your thoughts.
“I do think that we are missing something.”
Perhaps so.
“The solution to the apparent paradox is to only use models with one step.”
Or at least to recognize that the time-step-iteration problem is real and blurs the result, limiting the reliability.
But let’s be reminded that the time-step-iterated climate models do indeed work this way – i.e. the mass and energy states of the earth system are completely re-computed as they evolve through every dynamic iteration, closing the energy-in and energy-out flows and all the internal energy-storage-and-release interactions, and pass the result to the next iteration.
So where are we? We have decades of investigation using dozens of versions of pre-stabilized-by-tuning models running radiative transfer coding which always gives a baked-in “warming” result for the rising concentrations of GHGs in the specified scenarios.
One more thing. Willis Eschenbach’s model – which uses “constructal law” optimization to converge on a result – is a fundamentally different computational approach that presumably avoids the time-step-iteration buildup of uncertainty. There are other sources of uncertainty, for sure, but it’s interesting to think about.
All the best to you.
David, you raise an extremely important point here. That is the method of calculation! Different methodologies or schemas of calculation should not result in different answers for the sum or final point; that includes the uncertainties associated with the intermediate or final outputs. That is, multiplication should give the same answer as multiple additions. If iteration gives a different answer than multiple calculations that are concatenated, then iteration-uncertainty is not done right.
Similarly, the final uncertainty of a calculated output should be the same whether 2n or 1000n intervals are used to arrive at the final point in the time-series. It appears that what you and Jim and Tim are recommending becomes a function of the multiplier of the number of time steps, n. If they do result in different answers, then it should give one pause.
Thank you for your further reply.
“If they do result in different answers, then it should give one pause.”
Yes. It should have given pause to “climate” investigators long ago (’60’s to ’90’s) that the discretized time-stepped dynamic models developed for weather prediction do, in fact, give different estimates of uncertainty (in a projection) depending on the time step chosen. That computation method for estimating the long-term energy-state influence of rising CO2 should have been recognized as not capable of ever providing a reliable answer.
But here we are, decades later, discussing why it was unsound all along to have made that choice.
That is not exactly what I am saying. Each input quantity in a functional relationship will add to the combined uncertainty. If I₀ is used in each iteration, its uncertainty is added to that’s iteration uncertainty. If
T1 = I₀×T₀, then u(T1) = √(u(I₀)+u(T₀)), and
T2 = I₀×T1, then u(T2) = √(u(I₀)+u(T1)).
This means u(I₀) is added again. u(T1) also contains u(T₀) so it is added again.
I am no expert on the inards of GCM’s. I do know that an iterative process adds uncertainty at each step. It is no different than laying bricks end to end. The uncertainty in each brick adds to the overall uncertainty.
Dr. Pat Frank showed that GCM’s turn into linear projections. That makes it even easier to show that uncertainty is added at each iteration. Adding 2 ±0.5 over and over, the uncertainty adds (probably in quadrature).
Rather than answering the uncertainty criticism climate science has refused to even show minimal evidence of how uncertainty is addressed inside the GCM.
NOAA’s Tides and Currents page is being redone.
If you follow the link, this terse sign comes up:
This site will no longer be available after
September 30, 2026. Please visit the new,
integrated Sea Level Trends and Extremes –
BETA site. If you have any questions
regarding this forthcoming change, please
contact our customer service support at
tide.predictions@noaa.gov.
I expect the new page will be a full of glitzy images with no useable content.
For example, the
“…absolute global sea level rise is believed to be 1.7-1.8 millimeters/year.“
statement will be more buried than it is already or totally gone.
“Believed”
Thank you, David.
I have been promoting proper estimates of uncertainty on blogs including WUWT for more than 5 years. Here is the first of a 3-part article of 20 August 2022, link:
Uncertainty Estimates for Routine Temperature Data Sets – Watts Up With That?
The 2 main lessons from this exercise were –
Carrying forward the error by time steps as in many climate models compounds the errror, errrror errrrror, as elegantly shown by Dr Pat Frank in this 2019 paper:
Frontiers | Propagation of Error and the Reliability of Global Air Temperature Projections
Geoff S
“Some agencies like Australia’s Bureau of Meteorology insist on dividing their uncertainty result by the square root of the number of observations”
This is *NOT* measurement uncertainty. It is SAMPLING uncertainty. The use of the (n-1) factor is only a shortcut for determining the standard deviation of the means of multiple samples, i.e. the SEM. The absolute correct method for determining this is to make multiple samples of the population consisting of “estimated value +/- measurement uncertainty”, take the mean of the estimated values from each sample, and determine the standard deviation of those sample means.
The sampling uncertainty equation should be SEM = σ/sqrt(n)
where σ is the population standard deviation.
Since the population standard deviation is probably unknown and many times only one sample is available the shortcut estimate SEM = s/sqrt(n-1) is used. If you assume that the sample is IID with the population the formula would actually be SEM = s/sqrt(n). If the single sample is not IID then s/(n-1) has its own uncertainty. For large n, 1/sqrt(n) and 1/sqrt(n-1) converge but the SEM calculated from a single sample may still be inaccurate since “s” may be significantly different than σ, especially if the population distribution is not Gaussian (or at least well-behaved).
Bottom line? Sampling uncertainty is *NOT* measurement uncertainty.
And in a time series, n can never be greater than 1!
One can fudge a little on the definition of simultaneity and have many measurements in a second and say that the time difference between measurements is small enough to legitimately claim that the thermal inertia is high enough that the measurements are essentially simultaneous, by the same instrument, of the same parcel of air or water. The only real advantage is if there is a voltage spike that is more than 2 or 3-sigma, and the original data are retained, it will be obvious that it is an outlier that should be deleted. If it isn’t retained, then the multiple samples are a waste of processing.
This is a measurement system that digitizes temperature data from a single sensor over a given time period, then averages the readings into a single temperature. However the temperature varies during the time period (and the electronics), there will be n numbers of samples that aren’t equal to each other, and a standard deviation associated with the average. Climate science ignores and throws this standard deviation away (along with those associated with any other subsequent averages). But the standard deviation should be included in an account of the uncertainty of this measurement system, and reported with the final measurement result. Outlier determination and treatment then lays in the realm of statistical process control.
What I’m really arguing for is that I acknowledge “One can never step in the same stream twice,” is literally valid. However, considering the several steps that might be necessary to get across the stream, it might be good enough for government work to just assume, at least as a first-order approximation, that all the steps were in the same stream.
The GUM covers some of this. Sections F.1.1.2 and H.6 deal with measurements of not the same thing. H.6 deal with testing hardness where the same point cannot be reused. They both say the standard deviation of the various measurements should be added to the measurement uncertainty. No divide by the √n, no fiddling, just add.
Keep up the good work, Geoff! And thanks for mentioning Pat Frank’s 2019 paper, which stands out in the published literature on propagation of uncertainty.
This WIKI entry is wrong. It assumes Earth radiates as a BB which I have demonstrated is wrong. Its reason for dividing Io by 4 is ½ & ½ nonsense. Io is divided by 4 to change the model from discular area to spherical area at ToA. This is Fourier’s model which even Pierrhumbert says is no good. It also uses a GHE balance graphic which I have demonstrated is also no good. It uses AU for some reason and never calcs W/m^2 correctly.
Calculation of equilibrium temperature
Consider a planet orbiting its host star. The star emits radiation isotropically, and some fraction of this radiation reaches the planet. The amount of radiation arriving at the planet is referred to as the incident solar radiation, I_oalbedo that depends on the characteristics of its surface and atmosphere, and therefore only absorbs a fraction of radiation. The planet absorbs the radiation that isn’t reflected by the albedo, and heats up. One may assume that the planet radiates energy like a blackbody at some temperature according to the Stefan–Boltzmann law. Radiative equilibrium exists when the power supplied by the star is equal to the power emitted by the planet. The temperature at which this balance occurs is the planetary equilibrium temperature.[4][5][6]
Derivation
In equilibrium, the solar flux absorbed by the planet from the star is equal to the flux emitted by the planet:[4][5][6]
F_abs=F_emit
A_B
F_abs=(1-A_B ) F_solar
F_solar
F_solar=I_o/4
6] The factor of 1/4 in the above formula comes from the fact that only a single hemisphere is lit at any moment in time (creates a factor of 1/2), and from integrating over angles of incident sunlight on the lit hemisphere (creating another factor of 1/2).[6]
Assuming the planet radiates as a blackbody according to the Stefan–Boltzmann law at some equilibrium temperature
T
e
q
{\displaystyle {T}_{eq}}, a balance of the absorbed and outgoing fluxes produces
Assuming the planet radiates as a blackbody according to the Stefan–Boltzmann law at some equilibrium temperature T_eq
F_emit=σ” ” T_eq^4
σ
(1-A_B )(I_o/4)=σT_eq^4
T_eq=((I_o (1-A_B ))/(4″ ” σ))^(1/4)
T_eq=((L_o (1-A_B ))/(16″ ” σ” ” π” ” d^2 ))^(1/4)
L_0 3.828⋅10^26 ” W” d
T_eq=1.07652⋅10^8 (1-A_B )^(1/4) (d/”meter” )^(-1/2) ” K”
T_eq=278.3296⋅(1-A_B )^(1/4) (d/”Au” )^(-1/2) ” K”
where the distance is given in astronomical units.
149597870700 m.[
So many words . . . so wrong.
One example from your post’s second paragraph:
“The amount of radiation arriving at the planet is referred to as the incident solar radiation, I_oalbedo that depends on the characteristics of its surface and atmosphere, and therefore only absorbs a fraction of radiation.”
The amount of radiation from a star that arrives at an orbiting planet DOES NOT depend on the the planet’s albedo . . . that arriving radiation is even indepent of the planet having, or not having, an atmosphere.
Another example from your cited “Derivation”:
“Assuming the planet radiates as a blackbody according to the Stefan–Boltzmann law at some equilibrium temperature T_eq
F_emit=σ” ” T_eq^4″
It is a well-known fact that Earth DOES NOT radiate as a blackbody and therefore it’s average emissivity to space, which you include in your calculations as the symbol σ must have a value less than 1. However, it mysteriously disappears towards the end of your “derivation”, which I find impossible to follow as posted.
Black-body refers to a TYPE of radiative emission. We can all see the pictures of a blue and white glowing jewel in the black of space.
This bloke simply does not get it.
The term “grey body” distinguishes radiators that have an emissivity less than 1 from blackbodies that by definition have an emissivity of exactly 1.
There is only one type of radiative emission from bodies having a temperature above absolute zero and such is independent of emissivity: that of EM photons, with acknowledgement of the wave-particle duality of EM photons.
Is the molten iron being poured out of a blast furnace radiating as a mix of isotopes of iron or as a really hot thing shedding energy by radiation?
I expect that the discussions and the measurements of the electromagnetic energy exchange of the ocean waters and the atmosphere be deal as if it were the latter.
Humans giving different words to things do not change the reality of reality. Black, grey, absorption spectra, emission spectra are just words and our dealing with actual observations requires that we take into account the true nature of the mechanisms of energy flow and exchange of the ACTUAL substances being investigated.
Why do you pose this as an either-or question? In reality, it is BOTH.
Science 101.
sigma is the S-B constant.
TFK_bams 09 396 is BB Earth
The Earth has not reached this point of radiative equilibrium yet, as the planet is still cooling, losing around 44 TW or so.
Your calculations seem to be based on at least totally incorrect assumption. Assume the surface is molten everywhere, do your calculation, and tell me what the calculated temperature.
My back of the envelope calculation based on measurements and basic physics gives me an “average” surface temperature of around 17 C, with a maximum possible of around 90 C.
This reflects the existence of an atmosphere. For the Moon, max comes out at around 130 C, close to measured surface temps.
Just for fun, AI burbles NASA nonsense about the Moons surface temps initially, but in response to my first follow-up question, responded –
AI was repeating the silly meme that the Moon gets hot because it has a long lunar day. At least the AI realised that NASA was talking nonsense. Most people don’t.
The actual earth looked at by actual eyes or actual cameras radiates as a glowing blue and white globe in the visible spectrum,
NOBODY pretends it is an actual black body. The first work looking at other planets had them doing a thought experiment – a planet the size of earth in its present average distance from the sun but totally emissive (no particular colour) was calculated to reach a certain temperature.
Then the theory added an atmosphere and the calculation was repeated.
The theoretical model earth was warmer at the surface when there was a blanket of atmosphere around it. CRUDE BUT PROOF OF CONCEPT
No consideration was given to the thermal conductivity of the rock or the presence of rotation. It was a THOUGHT EXPERIMENT!
The phenomenon was then given a name because of its likeness to a familiar structure, a greenhouse.
Sunlight is actually black-body radiation for most intents and purposes.
The finding of spectral lines in the light from stars was a surprise but they are all emitting black-body like radiation with the TRACE presence of the spectra of elements.
Not so cosmic “dust” clouds and other celestial phenomena which glow from other stimulation rather than raw energy.
Look – no numbers. My primary school children understand it.
The peak of the visible spectrum is in green light. However, the appearance is shifted to longer wavelengths (orange-yellow) because of Rayleigh scattering, which is what causes the sky to appear blue.
What has happened to the white to fool human eyes?
The sky? Or the sun?
A white sky happens when there is lots of aerosol scattering. The sun, OTOH, is so bright that the eye can’t detect the green peak wavelengths. When it is low in the sky with scattering the color shifts to yellow and red.
Can they balance your checkbook?? Can they explain 63 + 63 = 63?
Wow, what a haboob of appeal to authority, esoteric subject changes, hand wavium, ad homonym, gorilla dust.
Let’s yank this out of the weeds and back on track.
Ya know, I have thoroughly plowed this dead horse but here goes once more.
1. Earth is cooler w atmospheric/water vapor/30% albedo not warmer. Yes/No & why.
2. GHE balance graphics don’t plus violate GAAP & LoT. Yes/No & why.
3. Kinetic heat transfer processes of contiguous atmospheric molecules (mistaken for “back” radiation) render “extra” GHE energy from a BB surface impossible. Yes/No & why.
Near Earth space is a 260 F convection oven not a near abs zero ice box.
TFK_bams09 has 63 twice, once originating from the 342 ISR and again from the out-of-thin-air 396 S-B BB calculation violating GAAP.
Incoming 1,368/4 = 342 *(1-.3) = 239-79 =160 & Outgoing 17 + 80 + 63 the 1st & balanced!!
Imaginary 396 S-B BB 16 C. Calculated, not real, fills denominator of emissivity ratio: 63/396=0.16 needed to correct IR that sees targets as BB.
Imaginary 333 “back” component of the 396 also not real
Imaginary 63 the 2nd has no place to go and must return & -396/+333/+63 GHE loop implodes to 0 like the Titan.
Over a week ago at a local King Soopers I crossed paths with a EE I worked with over twenty years ago had not seen since.
We now live abut 10 miles apart.
I snail mailed to him a copy of my position paper.
It has yet to be delivered.
USPS AI leaned on by influencers?
USPS will not platform my “misinformation.”
That just strengthens my resolve.
Charles Bukowski: “Censorship is the tool of those who have the need to hide actualities from themselves and from others.”
Voltaire: “What does censorship reveal? It reveals fear. Think for yourselves and let others enjoy the privilege to do so, too.”
Does the USPS open your mail? It takes 3 to 5 to 7 days for a letter to go across town or a state.
King Soopers – – never heard of this. There are Freddy’s around.
King Soopers are common in Colorado. I have a King Soopers member card that I routinely use at my Ohio Kroger chain, after more than 20 years. They are all owned by Kroger.
It’s been 2 weeks.
A SASE took less than a week.
He lives 10 miles from me.
How do you know it wasn’t delivered?
The USPS does offer ways to receive “proof of delivery”. It cost more but it’s available.
(You may need to go to a post office to send it.)
How do you know it wasn’t delivered?
I would bet that he just never responded.
We noticed that you didn’t give an elapsed time since mailing.
USPS isn’t monitoring your mail. You’re not important.
Maybe he read it and doesn’t want to tell you what shite it is.
You know… EE’s spend some time in engineering school calculating component temperatures on electronic chassis….with “back-radiation” from components nearby, the negative Tcold^4 part of P= eσFA [Thot ^4 – Tcold^4]…the view factor of slightly cooler surrounding components causes overheating of the hotter component moreso than would occur if the “less warm” component was not present….It’s ”back radiation” from the surroundings that they calculate… a proven and easily understandable physics concept which you deny exists…but you know, WTH?…a conspiracy theory fits too, one of their benefits, especially since the post office is known for heat transfer creedo and must be out to get you…
“Neither snow nor rain nor HEAT nor gloom of night stays these couriers from the swift completion of their appointed rounds.”
It’s been two weeks. I’ll ask him over breakfast.
This “back” radiation is the molecular kinetic processes at play.
Not that it matters.
The 333 originates with the 396 which is pure fantasy.
Yes, he received it. Went on the stack unopened. Hypothesis disproven.
Will meet for breakfast and discuss.
ISR aka Io = 1,368 W/m^2 (Luminosity W/spherical area m^2 at Au)
Divide by 4 to convert discular cross sectional area to ToA spherical area.
1,368 W/m^2 / 4 = 342 W/m^2
Apply 30% Bond (James) albedo.
(1 – 0.3) * 342 = ASR 240 W/m^2
ASR = OLR
OLR S-B equilibrium for 240 W/m^2 = 255 K, -18 C.
OLR equilibrium temperature without esoteric hocus pos handwavium.
Troposphere is full of molecular KE heat transfer processes which negates 396 BB/333 “back”/63 duplicate imaginary GHE loop.
“OLR S-B equilibrium for 240 W/m^2 = 255 K, -18 C.”
Hmmmm . . . please state what average global emissivity you used for calculating OLR to deep space. After all, it is well-known that Earth does not radiate as a blackbody, considering either just ground surface or as integrated at TOA (ground plus atmosphere).
ROTFL.
From your post:” After all, it is well-known that Earth does not radiate as a blackbody,…”
If true why are there diagrams comparing the sun to the earth? Or the earth by itself from space showing the various notches?
Please clarify/give an example of “diagrams comparing the sun to the earth”.
Secondarily, the fact that there are “notches” in Earth’s radiation spectrum as measured from space is exact proof that Earth does not radiate as a blackbody!
Practical question, asked seriously.
Suggest the alternative mathematical or theoretical model to use on the sun – earth – space energy flows being discussed.
I do believe you have confused asking a question with requesting an action.
BTW, I did not receive a reply to my earlier request of you.
There are some people here with fixed ideas which we are powerless to change. I refuse to lose sleep over it.
They confuse mathematical formulae with reality!
Plank found a mathematical way to describe the electromagnetic absorption properties of a hole in a cavity to far better represent reality that the classical way, which very very inaccurately described observation. The quantum nature of reality was absent.
Applying that formula to the planet is the closest tool available in the quest for an understanding of the flow of energy of the planet. There is no other formula which comes within a country mile of approximating it.
So NO THING is a black body IN REALITY unless people think a pin hole in a big empty space is a thing.
Talk about a confusing statement!
Max Planck laid the foundational groundwork for, and is widely considered the originator of, quantum theory. Quantum theory is the largely-mathematical description of the reality of the universe at small scale . . . sub-atomic and smaller dimensions.
At larger dimensions, Maxwell’s equations describing EM radiation and absorption work just fine!
The Rayleigh–Jeans law was used in the late 19th century to determine how intensity of radiation from an object. The problem was that it had no limit. As wavelength decreased, the intensity grew without bound. Planck’s work on heat radiation provided a what is known as Planck’s Law and its associated Planck Curve which agreed with experiment.
His mathematical work on oscillators and probability led him to find that there is a smaller and smaller chance of an energy absorption causing a smaller and smaller chance of emission as wavelengths decreased. His work with oscillators and probability led to proposed quanta which meant oscillators had integer values of a base unit (quanta).
Under modern quantum theory, where energy (E) of a photon equals h*f, with “h” being Plank’s constant and “f” being frequency (= speed of light/wavelength), there is no upper limit on energy. IOW, under current physics, as wavelength decreases the “intensity” (energy per photon) grows without bound.
From Google’s AI bot:
“The highest-energy photons found in nature are ultra-high-energy gamma rays reaching energies of over 1 peta-electron-volt (PeV, or quadrillion electron-volts), with the highest verified individual photon reaching 1.4 PeV (1,400 TeV).”
There is every reason for cosmologists to believe much higher energy photons existed shortly after the Big Bang.
Again, from Google’s AI bot:
“Cosmologists believe that the highest-energy photons shortly after the Big Bang approached the Planck energy scale, roughly 1.22 x10^19 GeV (1.22 x 10^28 eV), corresponding to temperatures near the Planck temperature of about 10^32 K during the Planck epoch (𝑡 <10^−43 seconds).”
No one is denying that. Photon energy is not the issue. The volume of photons (quanta) being emitted is the issue. Here is what I said.
The energy of an emission can be high, but the total power emitted at a given temperature can be diminishing because of fewer and fewer quanta being emitted. In other words less and less emission, You can determine the wavelength of maximum intensity using Wein’s Law. It should be obvious that at that wavelength, there is less and less chance of an emission at shorter wavelengths. The energy just isn’t there.
Planck’s Theory of Heat Radiation explains how probability enters into this. Read Part IV, Chapter I. Here is a piece from the book.
Remember the Rayleigh–Jeans law said that emission intensity would increase at shorter and shorter wavelengths regardless of temperature. Experimenters already knew something was wrong with that equation. It was called “the ultraviolet problem”. Planck solved the problem and today we have the Planck Curve based on temperature.
Also, I take note of the repeated mention of “assume” in your quoted text. Can I assume those assumptions might be wrong?
But today we also have the scientific hypothesis that the universe has experienced incalculable numbers of individual photons, each with energy as high as 1.22 x 10^28 eV. That’s close enough to “without bound” for me.
ROTFL.
It isn’t the energy of an individual photon that is the issue. The issue is how likely a photon of that energy will be emitted by a body at a given temperature. The Planck Curve tells you that emissions will peak at a given wavelength and as you look at shorter and shorter wavelengths at that temperature, the emissions reduce, that is, fewer electrons at those wavelengths are emitted.
There is no loop to consider, 396 Worth of photons are emitted from the 15C surface upwards, and 333 worth of photons are emitted from the sky downwards for a net radiative heat transfer from surface to sky of 63 W…works out to an equivalent BB temp of about 4 C for the sky as viewed from the surface…of course lots of gas emission bands, cloud bottoms, and a view of outer space is involved so the sky isn’t a super-good approximation to a BB….but it makes sense that from the surface the sky looks 277 C while from outer space the sky and planet look 255 C to your IR sensors…the tops of clouds and greenhouse gases being very cold and emitting at high altitudes while blocking 2/3 of outer spaces’ view of the 288 C surface…
”…It’s easy if you try…” Imagine, John Lennon.
not to mention that each photon has its own particular wavelength and so represent a unique amount of energy. I guess you are talking about virtual photons, which wavelength have you given the ones you count as being exchanged. /Irony
Everybody is playing with theories (guesses)
I prefer reality.
It has been getting slightly warmer for a while, that has slowed and it will get slightly colder for the next ten years if the solar magnetic minimum is a driver of change in total insolation via cosmic rays
This post is a follow up to an interesting article posted here a few weeks ago by Andy May. https:wattsupwiththat/2026/08/21/deployabe-energies-new-compact-nuclear-reactor/ Before I start, let’s define two abbreviations that I’ll use a number of times. High-Temperature Gas-Cooled Reactor=HGTR. Deployable Energy=DE.
Deployable Energies (web site=https://www.deployable.energy)(DE) is a start up that promises to produce very small, easily installed, very inexpensive fission reactors built with off-the-shelf components for those who need such. Their website seems to be mostly marketing mush. But it appears they have managed to put together a credible prototype reactor that is currently undergoing testing at the Idaho National lab. Moreover, they seem to have built it in about five months. Their press release shows a cylindrical device about the size of a large trash can in the bed of a Ford pickup truck. Clearly, they have substantial technical smarts.
The following is my analysis of what little technical detail I could find on the DE website. Note that I am not a nuclear engineer, nor indeed an engineer of any sort. But I do have a STEM degree (BS in Chemistry — UCLA 1961). I have worked with the software of a number of large, complex systems and have worked with real engineers enough to have some idea of what they do.
The reactor is apparently a High-Temperature Gas-cooled Reactor(HTGR). If so, it does not produce electricity. Instead, it heats Helium gas to 700-900 degrees Centigrade. The very hot gas can then be used to generate electricity, promote chemical reactions requiring high temperatures, or similar purposes. HTGRs apparently are rated by the thermal power they produce not by the electrical power generated when they are used for that purpose. One megawatt thermal probably corresponds to about 400-600 kilowatt electrical. The amount of electricity depends on whether secondary recovery — a second turbine driven by steam boiled by the exhaust stream of the first — is used There are or have been a small number of HTGRs (9 or so) built in the past 62 years. This clearly is not a new, unproven technology although a trashcan sized very low power unit appears to be something new. There’s a Wikipedia article https://en.wikipedia,org/wiki/High-temperature_gas-cooled_reactor .
If one believes Wikipedia, and I don’t see any reason not to, there are two types of HTGR — prismatic and pebble bed. In prismatic reactors the fissionable material is arranged in columns which need to be replaced every five years or so. In pebble bed reactors, the fissionables are in ceramic coated “pebbles” that pass very slowly through the reactor. The depleted “pebbles” are removed at the bottom while fresh “pebbles” are dropped in from the top. In principle, that allows continuous operation for the 40 year (or more?) designed lifetime of the reactor. The DE device looks to be a prismatic reactor.
In both HGTR types the heat generated is transferred to pressurized Helium gas which is circulated through the reactor. Helium has the advantages of being chemically inert, having decent heat capacity, and being transparent to the neutrons emitted by fissioning material. In theory at least, no nuclear activity or products will be present outside the reactor core.
One virtue of HGTR reactors is that the ceramic coated fisssionables are designed such that the radioactives are close enough to each other to interact and generate significant heat through fission at much higher than natural background rates. But they can’t get close enough to go critical. The intent is that can’t melt down through any combination of misinformation (Three-Mile Island), human ineptitude (Chernobyl), or sequence of unfortunate events (Fukushima daiichi).
Larger HTGRs (all built to date) seem to have graphite moderator rods that can be moved in an out of the reactor core to damp the reaction when less power output is needed or when something goes wrong. It’s not clear that the DE one Megawatt device has those. On the other hand it’s not clear to me how one can do without something of the sort if for no other reason than that permitting device installation is likely to be impossible in some jurisdictions without some means of quickly shutting it down.
The only drawback to HTGRs that I could identify is that it appears to quite difficult to keep damaging contaminants out of the circulating Helium. Water at very high temperatures seeping into the Fort St Vrain reactor in Colorado seems to have caused significant corrosion problems throughout its ten year active period. Maybe that can be designed around. And maybe not.
DE HTGR Reactor — Part 2 (Part1 is above)
…
It appears to me that barring unexpected problems, the DE device should be fail-safe and should able to generate significant amounts of electricity when hooked to a generator. It will not be completely passive as a circulating pump for the Helium as well as (probably?) movable control rods and hardware to move them will be needed. And some sort of cooling will be needed for the generators. One MW thermal in, 400-600kw electrical out leaves 400-600kw thermal unaccounted for. It’s likely going to be waste heat that presumably needs to be disposed of via air or liquid cooling unless it can be put to beneficial use like facility heating or water desalinization.
One might reasonably wonder if 400-600kw of waste heat can be gotten rid of without a connection to a substantial local water supply. That could be a problem in arid areas like much of Western North America. I really have no idea. But diesel-electric locomotives apparently generate several times that much waste heat and they are, of necessity, air-cooled.
Overall– interesting and kind of impressive. A good start I think. However, It must be remembered that what is currently being tested looks to be just the heat source. Assuming that works out, the actual electric generation hardware using very hot, pressurized Helium still needs to be designed and tested. And quite likely some design changes will be required to satisfy local laws and environmental regulations. At the very least, installation in a populated area will likely require some sort of containment structure around the reactor itself.
Finally. I’d caution that despite the apparent simplicity, to be useful the reactor will turn out to be part of a fairly complex system. Historically, initial deployment of such systems tend to be costly and considerably more difficult than it might appear on the surface . Don’t be suprised if there are problems. Why? I’ll refer anyone who is interested to Admiral Hyman Rickover’s brief and entertaining 1953 “Paper Reactor” speech — https://whatisnuclear.com/rickover.html re the difference between a concept on paper and reality.
The water in Fort St Vrain came from the use of steam to drive the gas circulation fans instead of electricity. The steam/water leaked through the shaft seal to the circulating coolant and promptly corroded all manner of stuff particularly because of the very high operating temperature. A second design error was in the use of a single circulating water pipe to cool the concrete barrier between the reactor vessel below and steam generators above. The pipe failed and there was no backup. The Brits adopted HTGRs as their commercial power plant standard and built several in two generations. A small number are still running but their new builds are PWRs. The biggest hit on HTGR technology is high maintenance. Gas coolant affords little or no lubrications on plant parts that must move (such as coolant fans) and very high operating temperatures both of which add to maintenance difficulties. HTGRs can generally provide about 75% availability while PWRs can be 90s+%. General Atomics was the vendor for the first commercial HTGR in the US (Peach Bottom) and the Fort St Vrain machine. Both plants had short lifetimes around 8-10 years.
Thanks Denis. Quite interesting. I assume the problem is things like bearings? Any thoughts on how one lubricates bearings at 700-900C? And how does one keep tiny He4 molecules from leaking through seals? Will that be a problem?
I assume the DE reactors will mostly target remote locations without grid access where unreliable operation would likely be a major problem.
(Sorry for the delay in posting this. This Chromebook lost it’s internet access for unknown reasons and I had to deal with other, more urgent, household problems before I could get around to addressing that.)
“BS in Chemistry — UCLA 1961” The year I graduated from high school.
Still doing “wet chemistry” back then. And, of course, Centigrade. 🙂
I’m going to go out on a limb and “call it” for the Arctic sea-ice (daily) minimum for 2026.
All of that AI data center processing power needs something to generate “hallucinations” from.
.
NSIDC data URL : https://noaadata.apps.nsidc.org/NOAA/G02135/north/daily/data/
JAXA data URL : https://ads.nipr.ac.jp/vishop/#/extent
I agree. Looks like the minimum has occurred. Another relatively high minimum will lead to almost no media coverage. So, what happens now? My theory, which I have occasionally mentioned here, is that Arctic sea ice drives the natural 60-70 year cycle.
This cycle has now been in its warm phase for ~ 30 years. That should mean a transition into the next warm phase is coming soon and may already be taking place. Record cold high Arctic temperatures this summer may be a sign.
The super-duper, Godzilla El Nino may or may not have a say in the matter. It will be interesting to see how this plays out over the next few years. However, a faster increase in the Arctic sea ice than we’ve seen over the last decade would sure indicate something new is afoot. The next couple of months will be the most informative.
Has Wadhams ever commented on the use and abuse of his name to laugh at his apocalyptic sea ice prognostications? I can’t be bothered to look it up. How on earth did Cambridge University turn into such a clown show?
I wonder how others here are feeling, that a sitting president thinks it ok to put his name on an already named memorial building? A building named after a loved assassinated president. Then when he is told he can’t legally do it, he threatens (using a weak maintenance excuse) to smash it down?
Well, most of us here think rather than feel.
So first off, maybe you should elaborate on who you’re talking about in this comment, and what the issues are.
(and is “he” the loved assassinated president or the “he” who was told he can’t legally do it and threatens to smash it down?
It’s a confusingly formatted question.)
He = JFK. Now I’d love to know what you “think?”
Don’t really care, Margaret.
But here’s the thing Margaret, would you care if it was … say…. Obama doing this to the Reagan Library?
Nope. Someone will change it back eventually, or not. And maybe someone will eventually rename Obama’s library to the Monument to Dystopia.
And Trumps could be.. a monument to “in plain sight corruption.” I mean what the hell is that family doing? Getting a friend of the war criminal Putin to pay for a big chunk of the family wedding. This is after bleating about how unfair it was people accusing them of having connections with the Russians. WHAT?????
Congratulations Simon. Good to see the medication’s working. Not trying to pretend you’re a scientist is a great step forward. Only about 12 years and you won’t be reading the Guardian any more. It really could happen.
Brilliant comment. Go you. And yep you got me, I’m not a scientist like almost all of the commenters here.
What he forgot to mention:
https://justthenews.com/politics-policy/all-things-trump/biden-era-inspections-exposed-kennedy-center-disrepair-safety
I think the USA is going the way of the Roman Empire, of Ancient Babylon, of Ancient Egypt – collapse of Imperial power and population decadence.
Obama, Biden, Trump … what next, Seinfeld?
Even Seinfeld not as humorous as appointing a failed sex convict businessman
Probably Marco Rubio with VP Gabbard. It’s rescuable. Could be Vance. I don’t much care personally, I already live in libtard central and know how to adapt.
“using a weak maintenance excuse”
So you don’t think it needs maintenance?
Of course it needs maintenance, it’s a building that is ageing. But you don’t threaten to rip down a national treasure just because it needs maintenance. I have an idea, you talk to the management board and get the maintenance done. Now let’s see, who is the chairman of the board? Oh that’s right…. it’s Donald.
I looked up what you’re saying and found this on NPR
The roof is falling. That seems to need more than a little maintenance – that’s structural failing.
I wonder how it got in that condition?
Nope not the roof. It was the ceiling. The roof is the bit on the outside.
What Happened?
Government still pushing:
Boeing receives fuel-efficiency rule waiver to sell 35 777Fs
That’s a new airplane model whose deliveries have been delayed a few years. (A derivative of the established 777, with efficiency improvements.)
The FAA rule was enacted a mere two years ago with a deadline only three years hence. !
Q, W/m^2 power flux flowing in or out of thermal system. AKA Btu/Eng h/m^2 or kJ/SI h/m^2.
Q/A = U (Thot – Tcold) = (Conduction + Convection + Advection + Latent + Radiation) * (Thot -Tcold)
More Conduction equals conductive forcing cooler. Less Conduction equals conductive forcing warmer.
More Convection equals conductive forcing cooler. Less Convection equals convective forcing warmer.
More Advection equals advective forcing cooler. Less Advection equals advective forcing warmer.
More Latent equals latent forcing cooler. Less Latent equals latent forcing warmer.
More Radiation equals radiative forcing cooler. Less Radiation equals radiative forcing warmer.
Q = (cond+conv+advec+latent+radiative.
Emissivity = radiative/100%
Temperature is a function of the four kinetic transfer processes, radiation is a function of that temperature and just goes along for the ride.
As demonstrated by experiment.
Modest Experiment in the Classical Style
Heat is energy in motion flowing from a hot/higher energy source to a cold/lower energy sink. A relatively hot surface transfers energy/heat to its surroundings through several processes, mechanisms or modes: conduction, convection, enhanced convection or advection, latent and radiative processes. The greater the number of these modes and the more effective those modes the lower will be the surface’s operating temperature.
Emissivity is the ratio of the actual radiative heat emitted by a surface to the S-B BB ideal radiation based on the input to the system. As radiation’s share of the total heat transfer modes/processes decreases so does its emissivity. For instance, if half of the energy is moved by the non-radiative processes emissivity for the radiative process will be 0.5.
Experimental procedure
A 125 W electric heating element is operated in open air and its surface temperature recorded.
A small biscuit fan blows air across the heating element and the temperature recorded.
A water spray bottle is used to wet the heating element and the temperature recorded.
The heating element is placed inside a one cubic foot steel box to inhibit convection and temperature recorded.
A vacuum is pulled on the steel box to remove molecules leaving radiation as the primary heat transfer mode and the element’s surface temperature recorded. (elevation 6,300 feet, Baro P 24 “Hga)
Conclusion
This experiment demonstrates conclusively that the emissivity of radiative heat transfer is heavily dependent on the various modes of heat transfer. In a situation where a surface transfers heat into an adjacent media participating through the various modes, emissivity of the radiative heat transfer will reflect its respective share.
Assuming an S-B BB emissivity of 1.0 for the earth’s surface and an average temperature of 16 C / 289 K to calculate an upwelling LWIR power flux of 396 W/m^2 is simply not supported by physical evidence. In line with the results demonstrated in this experiment and the values on the K-T power flux balance diagram, earth’s surface radiative emissivity is about 0.16, 63/396.
Without an up/down/”back” radiating loop the radiative greenhouse effect theory fails. When RGHE theory fails, so does the concept of man-caused climate change.
The heating element is rated at 125 W with measured surface area of 8.95E-3 m^2 for a power flux of 1.396E4 W/m^2 and a BB predicted temperature of 704.5 K, 431.5 C, 808.6 F.
Emissivity = measured/calculated.
Under a 22.4 “Hg vacuum (1.6”Hga) the element peaked at 827 F with an emissivity 1.14 BB. Close enough to predicted for an amateur in his garage.
With no vacuum but a sealed box the internal conduction/convection temperature was 729 F with emissivity of 0.8.
With an exposed element conduction/convection temperature was 672 F with emissivity of 0.64.
With a fan blowing across the exposed element conduction/convection /advection temperature was 457 F with emissivity of 0.28.
With a water spray mist conduction/convection/advection/latent temperature was 200 F with emissivity of 0.07, elevation of 6.300 feet.
System temperature is function of the four kinetic processes, radiation is a function of the temperature.
Earth’s emissivity per TFK_bams09 = 63/160 = 0.39.
396 BB/333 “back”/63 duplicate is imaginary for correcting IR meters.
Slicing and dicing to claim scarcity:
Tiny wild cat newly identified as a species draws curious visitors in Bolivia – Victoria Times Colonist
A new cat species is discovered for the first time in over a century | AP News
Sounds like little difference between variants. I don’t think they are small, domesticated cats do vary in size.
I thought that scientists were turning away from creating new species definitions. Here, there are colour variations among birds – often due inter-breeding of regional populations, and among the cougar/mountain lion/puma to partially suit environment (dark forests, mountains, desert). (Whereas the Florida Black Panther is black and small (it is a cougar not a panther).)
A question seeking a simple answer that a common layman like me can understand, recognizing that there are a lot of variables to consider. I see claims by those with rooftop solar that they power their home while also charging their EVs, their lawn mower/cordless/everything else cordless using their solar panels while still exporting more electricity to the grid than they use. I suppose that is possible, but think that their solar system would need to be pretty large to accomplish all of that, plus the claim that they also charge a backup battery system at the same time. If all that is possible, why be connected to the grid at all? Anyway, can anyone share insights re: verifying this claim? When I research, I find a lot of what I refer to as renewable porn suggesting that everything with solar power is possible. One question that needs to be answered is how well it all works during those short, cold, cloud covered days of winter accompanied by those long, cold winter nights.
TFK_bams09 and its plethora of clones omit the duplicate LWIR imbalance and assume Earth radiates as a full BB as do SURFRAD and USCRN.
This is each and every all wrong.
Just as wrong as caloric, phlogiston, luminiferous ether, water filled Martian canals and other historical scientific misconceptions.
More climate goons:
Seniors arrested, charged with trespassing during climate protest on Parliament Hill – Victoria Times Colonist
Initiating force is wrong.
Blocking lawful access is a crime in Canada, a version of Mischief.
Just had a quite lively go-round w CoPilot. At least it does not insult me, cover its ears and stomp out of the room.
It all boils down to this.
TFK_bams09.
396 W/m^2 upwelling from surface – real or imaginary? (also 333 “back” & 2nd 63)
Can it be measured? No.
396 is a theoretical, imaginary, S-B BB calculation for any surface at 16 C & assumes incorrectly that Earth’s surface radiates as a true BB. (333 & 2nd63 also imaginary.)
At this point, I think the disagreement has been reduced to a very specific philosophical and physical question:
That’s a much clearer and more focused disagreement than arguments about “missing” fluxes in energy-budget diagrams. It gets straight to the assumption that a surface embedded in the atmosphere can be treated as if it were an independent blackbody emitter. Your position is that it cannot.
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You said:Kewl & thanks.
Copilot said:
You’re welcome.