Tomas Fürst explains the dangers in believing models are reality in his Brownstone article Mathematical Models Are Weapons of Mass Destruction. Excerpts in italics with my bolds and added images.
Great Wealth Destroyed in Mortgage Crisis by Trusting a Financial Model
In 2007, the total value of an exotic form of financial insurance called Credit Default Swap (CDS) reached $67 trillion. This number exceeded the global GDP in that year by about fifteen percent. In other words – someone in the financial markets made a bet greater than the value of everything produced in the world that year.
What were the guys on Wall Street betting on? If certain boxes of financial pyrotechnics called Collateralized Debt Obligations (CDOs) are going to explode. Betting an amount larger than the world requires a significant degree of certainty on the part of the insurance provider.
What was this certainty supported by?
A magic formula called the Gaussian Copula Model. The CDO boxes contained the mortgages of millions of Americans, and the funny-named model estimated the joint probability that holders of any two randomly selected mortgages would both default on the mortgage.
The key ingredient in this magic formula was the gamma coefficient, which used historical data to estimate the correlation between mortgage default rates in different parts of the United States. This correlation was quite small for most of the 20th century because there was little reason why mortgages in Florida should be somehow connected to mortgages in California or Washington.
But in the summer of 2006, real estate prices across the United States began to fall, and millions of people found themselves owing more for their homes than they were currently worth. In this situation, many Americans rationally decided to default on their mortgage. So, the number of delinquent mortgages increased dramatically, all at once, across the country.
The gamma coefficient in the magic formula jumped from negligible values towards one and the boxes of CDOs exploded all at once. The financiers – who bet the entire planet’s GDP on this not happening – all lost.
This entire bet, in which a few speculators lost the entire planet, was based on a mathematical model that its users mistook for reality. The financial losses they caused were unpayable, so the only option was for the state to pay for them. Of course, the states didn’t exactly have an extra global GDP either, so they did what they usually do – they added these unpayable debts to the long list of unpayable debts they had made before. A single formula, which has barely 40 characters in the ASCII code, dramatically increased the total debt of the “developed” world by tens of percent of GDP. It has probably been the most expensive formula in the history of mankind.
Covid Panic and Social Devastation from Following an Epidemic Model
After this fiasco, one would assume people would start paying more attention to the predictions of various mathematical models. In fact, the opposite happened. In the fall of 2019, a virus began to spread from Wuhan, China, which was named SARS-CoV-2 after its older siblings. His older siblings were pretty nasty, so at the beginning of 2020, the whole world went into a panic mode.
If the infection fatality rate of the new virus was comparable to its older siblings, civilization might really collapse. And exactly at this moment, many dubious academic characters emerged around the world with their pet mathematical models and began spewing wild predictions into the public space.
Journalists went through the predictions, unerringly picked out only the most apocalyptic ones, and began to recite them in a dramatic voice to bewildered politicians. In the subsequent “fight against the virus,” any critical discussion about the nature of mathematical models, their assumptions, validation, the risk of overfitting, and especially the quantification of uncertainty was completely lost.
Most of the mathematical models that emerged from academia were more or less complex versions of a naive game called SIR. These three letters stand for Susceptible–Infected–Recovered and come from the beginning of the 20th century, when, thanks to the absence of computers, only the simplest differential equations could be solved. SIR models treat people as colored balls that float in a well-mixed container and bump into each other.
When red (infected) and green (susceptible) balls collide, two reds are produced. Each red (infected) turns black (recovered) after some time and stops noticing the others. And that’s all. The model does not even capture space in any way – there are neither cities nor villages. This completely naive model always produces (at most) one wave of contagion, which subsides over time and disappears forever.
And exactly at this moment, the captains of the coronavirus response made the same mistake as the bankers fifteen years ago: They mistook the model for reality. The “experts” were looking at the model that showed a single wave of infections, but in reality, one wave followed another. Instead of drawing the correct conclusion from this discrepancy between model and reality—that these models are useless—they began to fantasize that reality deviates from the models because of the “effects of the interventions” by which they were “managing” the epidemic. There was talk of “premature relaxation” of the measures and other mostly theological concepts. Understandably, there were many opportunists in academia who rushed forward with fabricated articles about the effect of interventions.
Meanwhile, the virus did its thing, ignoring the mathematical models. Few people noticed, but during the entire epidemic, not a single mathematical model succeeded in predicting (at least approximately) the peak of the current wave or the onset of the next wave.
Unlike Gaussian Copula Models, which – besides having a funny name – worked at least when real estate prices were rising, SIR models had no connection to reality from the very beginning. Later, some of their authors started to retrofit the models to match historical data, thus completely confusing the non-mathematical public, which typically does not distinguish between an ex-post fitted model (where real historical data are nicely matched by adjusting the model parameters) and a true ex-ante prediction for the future. As Yogi Berra would have it: It’s tough to make predictions, especially about the future.
While during the financial crisis, misuse of mathematical models brought mostly economic damage, during the epidemic it was no longer just about money. Based on nonsensical models, all kinds of “measures” were taken that damaged many people’s mental or physical health.
Nevertheless, this global loss of judgment had one positive effect: The awareness of the potential harm of mathematical modelling spread from a few academic offices to wide public circles. While a few years ago the concept of a “mathematical model” was shrouded in religious reverence, after three years of the epidemic, public trust in the ability of “experts” to predict anything went to zero.
Moreover, it wasn’t just the models that failed – a large part of the academic and scientific community also failed. Instead of promoting a cautious and sceptical evidence-based approach, they became cheerleaders for many stupidities the policymakers came forward with. The loss of public trust in the contemporary Science, medicine, and its representatives will probably be the most significant consequence of the epidemic.
Demolishing Modern Civilization Because of Climate Model Predictions
Which brings us to other mathematical models, the consequences of which can be much more destructive than everything we have described so far. These are, of course, climate models. The discussion of “global climate change” can be divided into three parts.
1. The real evolution of temperature on our planet. For the last few decades, we have had reasonably accurate and stable direct measurements from many places on the planet. The further we go into the past, the more we have to rely on various temperature reconstruction methods, and the uncertainty grows. Doubts may also arise as to what temperature is actually the subject of the discussion: Temperature is constantly changing in space and time, and it is very important how the individual measurements are combined into some “global” value. Given that a “global temperature” – however defined – is a manifestation of a complex dynamic system that is far from thermodynamic equilibrium, it is quite impossible for it to be constant. So, there are only two possibilities: At every moment since the formation of planet Earth, “global temperature” was either rising or falling. It is generally agreed that there has been an overall warming during the 20th century, although the geographical differences are significantly greater than is normally acknowledged. A more detailed discussion of this point is not the subject of this essay, as it is not directly related to mathematical models.
2. The hypothesis that increase in CO2 concentration drives increase in global temperature. This is a legitimate scientific hypothesis; however, evidence for the hypothesis involves more mathematical modelling than you might think. Therefore, we will address this point in more detail below.
3. The rationality of the various “measures” that politicians and activists propose to prevent global climate change or at least mitigate its effects. Again, this point is not the focus of this essay, but it is important to note that many of the proposed (and sometimes already implemented) climate change “measures” will have orders of magnitude more dramatic consequences than anything we did during the Covid epidemic. So, with this in mind, let’s see how much mathematical modelling we need to support hypothesis 2.
Yes, they are projecting spending more than 100 Trillion US$.
At first glance, there is no need for models because the mechanism by which CO2 heats the planet has been well understood since Joseph Fourier, who first described it. In elementary school textbooks, we draw a picture of a greenhouse with the sun smiling down on it. Short-wave radiation from the sun passes through the glass, heating the interior of the greenhouse, but long-wave radiation (emitted by the heated interior of the greenhouse) cannot escape through the glass, thus keeping the greenhouse warm. Carbon dioxide, dear children, plays a similar role in our atmosphere as the glass in the greenhouse.
This “explanation,” after which the entire greenhouse effect is named, and which we call the “greenhouse effect for kindergarten,” suffers from a small problem: It is completely wrong. The greenhouse keeps warm for a completely different reason. The glass shell prevents convection – warm air cannot rise and carry the heat away. This fact was experimentally verified already at the beginning of the 20th century by building an identical greenhouse but from a material that is transparent to infrared radiation. The difference in temperatures inside the two greenhouses was negligible.
OK, greenhouses are not warm due to greenhouse effect (to appease various fact-checkers, this fact can be found on Wikipedia). But that doesn’t mean that carbon dioxide doesn’t absorb infrared radiation and doesn’t behave in the atmosphere the way we imagined glass in a greenhouse behaved. Carbon dioxide actually does absorb radiation in several wavelength bands. Water vapor, methane, and other gases also have this property. The greenhouse effect (erroneously named after the greenhouse) is a safely proven experimental fact, and without greenhouse gases, the Earth would be considerably colder.
It follows logically that when the concentration of CO2 in the atmosphere increases, the CO2 molecules will capture even more infrared photons, which will therefore not be able to escape into space, and the temperature of the planet will rise further. Most people are satisfied with this explanation and continue to consider the hypothesis from point 2 above as proven. We call this version of the story the “greenhouse effect for philosophical faculties.”
The important point here is the red line. This is what Earth would radiate to space if you were to double the CO2 concentration from today’s value. Right in the middle of these curves, you can see a gap in spectrum. The gap is caused by CO2 absorbing radiation that would otherwise cool the Earth. If you double the amount of CO2, you don’t double the size of that gap. You just go from the black curve to the red curve, and you can barely see the difference.
The problem is, of course, that there is so much carbon dioxide (and other greenhouse gases) in the atmosphere already that no photon with the appropriate frequency has a chance to escape from the atmosphere without being absorbed and re-emitted many times by some greenhouse gas molecule.
A certain increase in the absorption of infrared radiation induced by higher concentration of CO2 can thus only occur at the edges of the respective absorption bands. With this knowledge – which, of course, is not very widespread among politicians and journalists – it is no longer obvious why an increase in the concentration of CO2 should lead to a rise in temperature.
In reality, however, the situation is even more complicated, and it is therefore necessary to come up with another version of the explanation, which we call the “greenhouse effect for science faculties.” This version for adults reads as follows: The process of absorption and re-emission of photons takes place in all layers of the atmosphere, and the atoms of greenhouse gases “pass” photons from one to another until finally one of the photons emitted somewhere in the upper layer of the atmosphere flies off into space. The concentration of greenhouse gases naturally decreases with increasing altitude. So, when we add a little CO2, the altitude from which photons can already escape into space shifts a little higher. And since the higher we go, the colder it is, the photons there emitted carry away less energy, resulting in more energy remaining in the atmosphere, making the planet warmer.
Note that the original version with the smiling sun above the greenhouse got somewhat more complicated. Some people start scratching their heads at this point and wondering if the above explanation is really that clear. When the concentration of CO2 increases, perhaps “cooler” photons escape to space (because the place of their emission moves higher), but won’t more of them escape (because the radius increases)? Shouldn’t there be more warming in the upper atmosphere? Isn’t the temperature inversion important in this explanation? We know that temperature starts to rise again from about 12 kilometers up. Is it really possible to neglect all convection and precipitation in this explanation? We know that these processes transfer enormous amounts of heat. What about positive and negative feedbacks? And so on and so on.
The more you ask, the more you find that the answers are not directly observable but rely on mathematical models. The models contain a number of experimentally (that is, with some error) measured parameters; for example, the spectrum of light absorption in CO2 (and all other greenhouse gases), its dependence on concentration, or a detailed temperature profile of the atmosphere.
This leads us to a radical statement: The hypothesis that an increase in the concentration of carbon dioxide in the atmosphere drives an increase in global temperature is not supported by any easily and comprehensibly explainable physical reasoning that would be clear to a person with an ordinary university education in a technical or natural science field. This hypothesis is ultimately supported by mathematical modelling that more or less accurately captures some of the many complicated processes in the atmosphere.
Flows and Feedbacks for Climate Models
However, this casts a completely different light on the whole problem. In the context of the dramatic failures of mathematical modelling in the recent past, the “greenhouse effect” deserves much more attention. We heard the claim that “science is settled” many times during the Covid crisis and many predictions that later turned out to be completely absurd were based on “scientific consensus.”
Almost every important scientific discovery began as a lone voice going against the scientific consensus of that time. Consensus in science does not mean much – science is built on careful falsification of hypotheses using properly conducted experiments and properly evaluated data. The number of past instances of scientific consensus is basically equal to the number of past scientific errors.
Mathematical modelling is a good servant but a bad master. The hypothesis of global climate change caused by the increasing concentration of CO2 in the atmosphere is certainly interesting and plausible. However, it is definitely not an experimental fact, and it is most inappropriate to censor an open and honest professional debate on this topic. If it turns out that mathematical models were – once again – wrong, it may be too late to undo the damage caused in the name of “combating” climate change.
Beware getting sucked into any model, climate or otherwise.
Addendum on Chameleon Models
Footnote: Classic Cartoon on Models
Science Matters 
Hi Ron
Glad you wrote this because explaining that models are not real science that can be tested and proved right, and are often wrong, with serious examples of what people lived through.
Getting this over to the lumpen proletariat at even the most basic level is hard, and your piece won’t do it. But its a good model to reduce. A problem I am trying to address..
Very important at the most basic level, that cliamte science is nota science, its made up in models, and doesn’t predict what actually happens, because the models are wrong. Again.
It’s what Billy Connolly would call a “pretendy science”, made up to con people. Models are not real science as most people know it. Nothing they can prove.
Climate science was created by UN Marxists who funded it to claim a political ideology must be imposed that would end economic development in the West, and make the West dependnent on Asia.
YOur key point is sound of course.
Climate science is modelled science, not a deterministic science anyone can prove, so is dangerous to rely on when it matters. It has to match the observations…. it doesn’t, wildly wrong.
I am still wrestling with explaining this difference between a deterministic model that uses absolute data and laws, and a numerical computer model that doesn’t. And the sorts of scientists who would pretend the one they use is the one you can prove, when its really the one you can’t, and they made it up to prove a political claim.
To me that is the real and large challenge in a few words. Real scientists are probably not direct enough in this matter.
Joe public is not going to read the number of words that you wrote, or I am prone to, explaining properly.
They can’t or won’t hold the thoughts for long enough to put the larger picture together. This is obvious because they still haven’t after years of failed predictions of every kind.
It has to be bite sized, accessible, but somehow connectable, simply.
IMPORTANT DETAIL: What made me write to you…. To my understanding of the body of academic science at least, not modelled………. the radioactive greenhouse effect does not work as you described.
Almost no thermal energy is absorbed in the atmosphere by CO2 GHG scattering at the greenhouse gas frequencies, which creates lossless quantum binding energy excitation and relaxation, so the net effect is that it is simply harder for radiation at those characteristic frequencies to escape to space, and because its eventually from much higher up in the Tropopause its colder, so less energy is lost per Dr. Stefan and Dr. Boltzmann
The effect of greenhouse gases is to reduce the radiative energy LOSS to space from the surface at a given temperature, not to heat the insulator. The atmosphere is Transparent Kapok at GHG frequencies, that raises the surface temperature because heat loss is reduced, not because the insulation is heated.
The whole system response to this is an energy imbalance that heats the planet, which loses more long wave infrared radiation to space from ALL causes, and the surface keeps being heated until the energy balance is restored, at a new equilibrium energy flux at a new, higher, equilibrium temperature – c. 288K average. Not simple.
I am just about to publish a paper on this overall energy balance system. This attempts an empirical AKA deterministic quantification of the overall Earth energy balance system, using well checked and accepted data, not a numerical one built on guesses and attribution.
SO rather than guessing what some chosen radiative perturbation might do, I calculate the natural radiative response from all variables to any given radiative perturbation per degree SST.
So the effect of any known perturbation on Earth’s average planetary surface temperature can by calculated with reasonable accuracy, not guessed.
I spent a long time understanding that the only real question is that regarding the scale and causes of natural change which modellers deny, so they can attribute all the observed change to AGW.
AND we absolutely KNOW at least one credible cause of natural cyclic change from solar insolation at the levels involved from CERES AND ALSO from geology, archeology and history of the natural world. So the assumptions of modellers are provably wrong on the measurements made to test them. So their models are wrong. Their response? Deny the measured reality.
So how much of the small measured change is natural, really?
The measured reality of natural change seriously questions the magnitude of the carbon dioxide contribution to the overall change since the coldest its been in 8,000 years in 1850, 2-3 degrees colder that 8Ka BP, at the coldest minimum in the natural cycle since then.
CO2 is certainly not responsible for all the change since 1850.
Again, this is the basic problem of the usual approach of multi variate models that hold other things constant to attribute an effect to a chosen variable. Earth doesn’t work like that.
Everything, all the time.
The basic problem of models is that they only vary their chosen effects, choosing to attribute little or no effect to other variables, so as to attribute all change to their chosen effect.
The variability of solar insolation change that we now measure to be several W/m^2 in a few years , more that the 1.6W/m^2 AGW effect since 1850, and perhaps other possibilities in the 99.96% of the atmosphere that is not CO2, show these presumptions to be false..
IT appears to me, TBC, these natural causes are totally excluded in the calculations of most models, which is why natural change must be denied.
So fake science was created by charlatans like Mann and Marcott , and recently by the IPCC itself, Hokey Stick 2.0 in AR6, in more models, created to prove the false presumptions, that denied over 1,000 papers researching natural change as real and cyclic, using disparate data concatenated in an overtly contrived and fraudulent way, processed in a computer using statistical filtering to deny any significant natural effects from 2000 years ago to 1850.
This is clearly proven false on the proxy temperature measurements, archaeological finds, and written history of the last thousand years . But it cannot be allowed to be believed, because then there is nothing for CO2 to account for. Right?
The people must be told. BUt how?
Most don’t understand basic finance or science, or they would not believe what the moronic and fraudulent liars, without science of any kind, in government – and their well rewarded pseudo scientist charlatans in Academe, tell them the facts are.
They clearly don’t check any of it. Communicating the truth is really hard. Especially when the mediahas no understanding of what is real science and the editorial management is captured.
etc. If you disgree with the GHE science summaraised above, can we talk?
Brian Catt 01932 772731 07770 931144
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Thanks for your extended discussion, and for your dedication to educating the public on this issue. My blog has always been my attempt to provide a portal for people to get information otherwise ignored or discounted by legacy and social media.
As for the piece above, the text is not mine but the POV of the author. My most recent attempt to explain in plain language GHG theory and its shortcomings is here:
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Sorry, Ron. Thought I was replying to you directly. I am on brian.catt@deconfused.com (My poorly maintained website domain for matters climate and energy). I will read your version of events. FYI – and everyone else here.
Only observations prove reality, not numerical or statistical models. Detrministoc models using observations and laws, that cliamte models are not.
Denying that GHE exists, as some realists do, because the effects of CO2 on overall change are small, is pointless, because it is real. Seen in the spectra measured from space, and also the spectra of downwelling radiation.
From Space:
Spectrally Resolved Fluxes from IASI Data: Retrieval Algorithm for Clear-Sky Measurements: Simon Whitburn, simon.whitburn@ulb. ac.be
https://journals.ametsoc.org/view/journals/clim/33/16/jcliD190523.xml
Downwelling – All GHE frequencies?
Earth Syst. Sci. Data, 13, 4303–4312, 2021
https://doi.org/10.5194/essd-13-4303-2021
The truth is multivariate, and the idiot claim that one tiny and diminishing effect of CO2 now controls Earth’s climate, after 500Ma of evident stability in a significantly changing solar controlled environment, is demonstrable nonsense. You have to be very stupid to believe these claims, even at this simple level. How can they be true?
What matters in the Earth energy balance system is the magnitude of the change, and the feedback to it from each component of the natural feedback system. Which is very different from claiming CO2 controls the climate and all the change within it.
For a start the Sun that creates the atmosphere, oceans and the equilibrium energy balance is in control of it all. The atmospheric lapse rate is natural thermodynamics and mostly not due to the radiative GHE/GHGs, only a bit. MOst important, the natural control feedbacks are far larger than the AGW, which is no more than a change in a small internal energy balance system variable, never a control, a lagging effect of warming from whatever cause, before and after industrialisation. So most change must be natural, and it is now verifiably at the rate, range and period measured in the natural cycles before industrialisation.
https://journals.ametsoc.org/view/journals/clim/33/16/jcliD190523.xml
They think people are stupid, or too lazy minded , busy or gullible. And they are right, sadly. How to get people to understand how they have been systematically lied to and so massively defrauded by the elites who have confiscated their wealth in the name of a lie they paid to have contrived, not a mistake, to save the planet the fraudulent renewable solutions the pay for can have no measurable effect on. …….except to enrich the elites with their snouts in the subsidy and tax troughs they filled with our money in the name of the climate lie they paid academics to “prove” in models they made up. Because it can’t be proven by observations. It is quite ibviously disproven by the observations, of natural change and actal climate change of the last 45 years. No unusual/anomalous change to be seen. A Lie.
Carl Sagan saw this coming: https://www.youtube.com/watch?v=izLgNlXjhjQ
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Thanks Brian. Regarding observations disputing GHG theory see my more technical post:
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I just looked at Murray Salby’s position. In know of him from others. Read your 2016 post. Fearless Physics and spot on the real issues, not arguing down modellers’ rabbit holes or within a narrow specialisation as others do.(AKA real physics).
The Myopia problem also struck me a as I looked closely at the whole energy balance system. It is close to the core understandings I had arrived at independently by empirical means, could have saved some time reading Murray Salby’s work. BUT I did mine from the ground up so am not being told what to believe… and, rather than just disputing the presumptions and omissions of models, which I do first, for all the reasons we all know, I put my engineer’s hat on to ask “how does that work, really?”)”.
So I have created an empirical evidence based way to model the whole Earth energy system as a simple and strongly controlled, not at all open, control system, using the observations we now have, and hence quantifying the system’s radiative feedback response to any radiative energy perturbation, inherently including all internal atmospheric factors by considering all the sources of radiative feedback to space, and in particular including the main feedback, which is not initially radiative and from within the system, the oceanic evaporative cooling response tat becomes radiation to space at the Tropopause by condensation, that has an established value and varies at 7% per degree K SST over a wide range of humidity and temperature. That is in the energy balance, but not apparently in the models?
……. and then estimated the other effects by scale and temperature variability. Probably. What happens that we can measure, not what might happen that someone makes up in a model. So I have put a heating engineer’s numbers to the realities the academics suggest – but don’t quantify. Because most of them are too narrowly specialised to even grasp the whole system? Big claim?
Coming soon. Abstract is up and describes the paper kinda, but pre-print paper not accepted yet. Fingers crossed … here’s the abstract teaser. Definitely fearless physics, hopefully with some merit. The academic snobs won’t like it. CO2 has a bit part in the dynamic system. Goo. Big in photosynthesis, though.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4950769
But 15,000 words are ultimately no use. Ending the scam is not not about explaining to those who have the formation across disciplines necessary to understanding what the holistic system in space looks like, as we can measure it. It’s how to explain it quickly and simply, in a way that will convince lay people of the fraud enacted by claiming all the actually small and normal global warming of the last 50 years was caused by CO2.
Change we observe is mostly natural, barely changed by CO2’s tiny effect, but has been all and falsely attributed to CO2 by denying everything else, the truth of which is obvious, measurable and quantifiable if you simply use the observations of all the other factors. Utterly bogus. If I have it right. If I don’t, where am I wrong? TBC
It’s like a greeny believing the primary factor in a winning F1 car design is it has the best energy recovery system … tyres, aerodynamics, brakes, power maybe a bit important, to create the energy to recover for a start, etc. ……
“There are more things in heaven and earth, modeller, than are dreamt of in your philosophy.” or..
“Models? We don’t need no steenking models”. (Because we have observations that describe the whole system)
Thanks for your additions to my knowledge. Brian
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Good to know you are publishing on this. Your link allowed me to download a pdf of your paper, which I browsed with great interest. I need to read more deeply, it’s a considerable treatise.
Two thoughts. I see the NASA energy balance diagram is prominent including the back radiation, spuriously calculated by abusing S-B equation. I wondered if the ERBE diagram would be useful, since it is simply all in and all out transfers.
Your paper reminded me of another research along similar lines. The post covered two papers, one by Bokuchava & Semenov and the other by de Larminat.
FYI
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Ron,
Dictated in haste as I am unsure if I already replied to you and I’m absolutely swamped. Yes I removed the scattering from the energy balance and explain this, and GHE, at some length in sections 2 and 3, the quantification bits. Everything is explained at length to avoid people deliberately misunderstanding the essential difference to other rebuttals of climate models that I have tried to present, by using observations and basic properties of matter to directly estimate the natural feedback to any radiative perturbation. Wholly empirically so verifiably. What’s wrong with my numbers?
I clearly show that change due to CO2 is small, easily controlled and immaterial within the natural change of the overall climate system.
There is perhaps another empirical statement which would register with lay people. That is the engineer’s test of limiting conditions.
What happens if there is much more CO2 and much less CO2?
If CO2 increases its temperature effects are small and logarithmically diminishing. 0.2K since 1850 per Brian Catt’s paper. More is OK. Because its measurable effects are currently net positive as regards photosynthesis and extreme temperatures and NO increase in extreme weather, less deaths, and MUCH less temperature change is measured than was predicted 40 years ago when the UN made its science up to support their political agendas, by attributing all change to an insignificant variable within the overall Earthly system of the Sun shining and the Earth returning that heat to space, denying the natural changes and ignoring the larger variable negative feedbacks. So nothing like the change the UN predicted has happened, because it was simply made up in wholly unrepresentative computer models programmed to force a correlation between their chosen cause of CO2 (In fact to justify controls on the energy use of developed economies), and 50 years of a probably mostly natural warming phase of the Earth’s short term natural cycles – while ignoring the dominant controls of Earth’s energy, hence climate, balance to prove their lie.
REALITY WE KNOW TO SCARE THE SIMPLE PUBLIC OFF CLIMATE ACTION?
Being cold is bad for humans and the crops that feed them, and their livestock, and warmer is better for us, globally. And climate action to prevent a little more warming makes no logical sense.
How Does that Work? Suppose the claims were true and CO2 was the dominant cause of temperature change on Earth….
WE know 140ppm of CO2 may have created a slight warming with no problems measured, only benefits to plant life. The temperature effects of CO2 diminish logarithmically as it increases in concentration while CO2 starved plants benefit at closer to a linear rate… up to 2,000pm quite safely, say 1,000ppm for comparison. 680ppm away.
But if CO2 is decreased by human action then the decrease in temperature will accelerate exponentially and the Earth will cool at accelerating speed, until photosynthesis also ends at 150ppm and we all die. 270ppm away
Which seems the more sensible direction of travel to the man on the street?
Just a thought.
Limiting conditions are a good engineering tests of any system. Or when you have binary choices. For life on earth, warmer beats colder. Because we know we have much more and safe headroom for more CO2, with a small and diminishing warming consequence over hundreds of ppm. And it costs us nothing. No net zero required.
But an expensively created extinction is only 270ppm away. How lucky do we feel?
Our governments want to suck CO2 out of the atmosphere at huge and unnecessary cost, with no obvious benefits, to enrich lobbysists and impoverish the people. If theyw orked for us they would be trying to increase CO2 to keep us warm and well fed.
At 150ppm their unwanted and sceince denying actions will have exterminated carbon based life on Earth. What sense is there in any of this? It is not anything to do with saving the planet.
nb: Of course nature will deny such idiocy because the ocean holds 98% of all CO2 on the Earth’s surface in solution and will liberate some more to maintain Henry’s Law balance.
But why take the chance, when free warming and better plant growth are the only measured consequences of more CO2. By far the best option. How lucky do we feel regarding whether our governments have this right? In haste, I may have repeated myself… CEng, CPhys.
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