Euthanasia, Not Hockey, Is Now the Canadian National Pastime
Canada has become known as a haven for euthanasia since the passage of its Orwellian MAID (“Medical Assistance in Dying”) Act. But it’s not just for killing granny anymore. The country has also been committing economic suicide for going on a decade and a half, and under its arch globalist deep state poster boy premier is now is hell-bent on committing geopolitical hari kari as well.
Canada was once on a par–above actually–the US in per capita GDP. Not any more. Like Europe, Canada has stagnated while the US has chugged along. So now. Canadian per capital GDP is less than 65 percent of the US level.
- 2007: 92.9% World Bank API+1
- 2011 (peak): 104.4% World Bank API+1
- 2014: 92.7% World Bank API+1
- 2016: 73.4% World Bank API+1
- 2020: 68.5% World Bank API+1
- 2022: 73.4% World Bank API+1
- 2024 (latest in this series): 64.3% World Bank API+1
And it’s not as if the US has been a growth juggernaut. Yet it has lapped Canada.
This stagnation–or what would Jimmah have called it? malaise?–is the result of an overdose of statism in Canada, something that was particularly evident in its draconian Covidianism. (Something it shared with the rest of the Anglosphere, ex US (to some degree)–all of which have also been economic laggards. No doubt Canada’s immigration policy–which makes the horrid US policy of the Biden years look enlightened–has also contributed
In sum, Canada has been committing slow motion economic suicide.
And now under the execrable Mark Carney (and execrable is the nicest thing I can think of calling him) it seems hell bent on committing geopolitical suicide. Carney just visited China, and based on the results, traveled with heavy duty kneepads in his luggage.
The trip is being portrayed with good reason as a Canadian pivot from the US to China in response to the big meanie to the south.
On trade, Carney touted a big deal–in which Canada will import 47,000 Chinese EVs. I see. Fighting against US restrictions on Canadian exports by taking Chinese imports that will compete against one of the industries (autos) that are hit by Trump tariffs. And a deal with a country that will take no manufactured goods from Canada. Brilliant!
Carney also said he and Xi see eye-to-eye on geopolitics generally, and Greenland specifically. And Carney has also said that Canada will defend Greenland if the US invades.
Might I ask: With what military, exactly? Canada has hollowed out its armed forces for decades. It is one of the biggest free riders on the US military, spending a whopping 1.3 percent of its GDP on defense. Canadian forces wouldn’t even be a speed bump: they would be roadkill.
In brief, Carney has positioned Canada as an adversary to the US by kowtowing to America’s biggest enemy and attempting to thwart US security initiatives.
It is beyond idiocy, but some idiots think it’s genius!
Er, no-he doesn’t get it. In a Westphalian power politics world allying with a malign distant power that is an adversary of the massive power right on your border is the epitome of idiocy. Especially since doing so infuriates the leader of the hegemon on your border.
Canada. So close to the US, so far from China. Do the strategery, “@DjStrategy.” (BTW considering anyone who calls themselves a “strategist” a self-important moron is an excellent heuristic–seldom fails!)
Now of course, Canada has been deeply penetrated by China (as a money laundry and intelligence sieve) for decades. Which makes one of Carney’s other statements particularly disgusting:
OK, asshole: want to compare the number of people killed in Canada by US guns to the number of Americans killed by fentanyl that flooded into my country from Canada? Orders of magnitude different.
Again, this is utterly suicidal. Canada and Carney’s globalist buddies may get off biting Trump’s ankles but it will not end well. The imbalance in power is so immense–and as the economic data presented above shows, has only become greater over time–that only a fool would pick a fight with the mercurial man wielding the power.
And if Carney thinks China is going to bail him out, he’s an even bigger idiot than I thought humanly possible. Maybe Carney should place a call to prison and ask Maduro how that works out.
And this is true too:
Not just an enemy–a hypocritical one.
It’s always been something of a joke to note that the US has long had plans to invade Canada. Maybe Hegseth should make sure they are up to date, cuz someone’s cruisin’ for a bruisin’.
Yeah, but … why???
This is what my friends and I are banging our heads over.
‘Whom the gods would destroy, they first make mad.’
Comment by Ex-Global Super-Regulator on Lunch Break — January 17, 2026 @ 3:49 pm
As a Conservative Canadian, I’ve almost wrenched my head off my shoulders shaking it so much since Mark Carnage has taken power.
Low information voters were absolutely ready to ditch the Liberals until PDJT poked fun at our feckless leader PMJT. A simple joke at a dinner table was all it took to ignite the idiots into fits or fake patriotism. Patriotism that their anoited Liberal leaders haven’t practiced in a full 10 years of power.
Canada’s only hope is that there’s a spring election and Carnage is thrown out of power. That he would lose at this point is beyond debate as the MSM has been spending all it’s efforts attacking the opposition leader (who I suppport but the spelling of his last name eludes my Anglo brain).
Unfortunately, the Socialists (NDP) and seperatists (Bloq PQ), either can’t afford an election (NDP) or don’t want an election (Bloq) when there’s more money to extort from the ROC (rest of Canada).
When the US invades us, I won’t be picking up a gun to stop it. I’ll most likely be hosting a kegger where my Conservative friends and I will mourn the passing of Canada and await the terms of our surrender.
Hoping we get an election, not an invasion.
At least there wouldn’t be many lives lost as our total millitary complament is around 17,000 and they’re so under funded and ill prepared that they’d most likely just surrender without much fight.
Cheers!
Comment by Geoff H — January 17, 2026 @ 5:41 pm
I’m don’t think USA is capable of annexing Canada by force and come out ahead. USA gets pretty much all the upside of what the Canadian territory can provide without the hassle of having to govern it. Also, wouldn’t it be cheaper to wait for provinces to begin to secede, and annex piece by piece, peacefully?
Comment by Michael — January 17, 2026 @ 7:07 pm
Err, and who is still China’s biggest trading partner, directly & indirectly via trade rerouting (by some margin)?
Comment by David Mercer — January 18, 2026 @ 2:49 am
Off topic: a few weeks ago I commented on how easy it would be to lock much of the US Navy in port by using, say, minelaying submarines. Someone else suggested they could be drones.
I thought he might be interested in this link. https://wattsupwiththat.com/2026/01/17/a-speculation-on-military-risk-with-offshore-wind-ai-submarines/
Comment by dearieme — January 18, 2026 @ 7:26 am
“… the number of Americans killed by fentanyl that flooded into my country from Canada?”
That’s not what the interception numbers say, Craig. That The Donald liked it as a sound-bite doesn’t make it true.
Comment by dcardno — January 18, 2026 @ 12:38 pm
@Deari – didn’t our resident climate-denying apocalypse-monger Pat Frank reference that website a few years back? Cracking article BTW – top-tier research from a man clearly in the know (and waay off the spectrum). It’s funny that there was no mention of the risk that these AI subs could presumably also hide under oil rigs or oil tankers in transit, in yacht marinas etc. No point unnecessarily upsetting his overlords I guess.
The pop-up ads on the website did pique my interest. Who knew there was such a strong correlation between climate-denial and BMI? Perhaps they’re spending too much time sat on their lardy ar5es whilst browsing websites like this? Just a theory.
Comment by David Mercer — January 18, 2026 @ 12:54 pm
I think that anyone who claims to believe the climate hysteria is either an ignorant twerp or someone who expects to profit from it. But what would I know? A career spent on modelling physico-chemical interactions, modelling fluid flows, developing finite element computational methods, using infra-red spec to measure CO2 concentrations, studying rates of heat transfer and temperature measurement – well, what could I know?
Comment by dearieme — January 18, 2026 @ 4:12 pm
@Geoff H there may be a ‘happy ending’ here, if Alberta decides to hoist the black flag and secede. British Columbia might have to follow soon afterwards, while the decrepit east would fall into financial crisis as their funding has disappeared.
Please forgive me for repeating myself: ‘Whom the gods would destroy, they first make mad’.
Comment by Ex-Global Super-Regulator on Lunch Break — January 18, 2026 @ 6:42 pm
Regarding per capita GDP differences between US and Canada, It’s almost like something important happened between 2014 and 2016. I feel like you don’t really discuss the driver (oil).
Comment by John Hall — January 18, 2026 @ 6:56 pm
It’s adorable how this post throws around the phrase ‘order of magnitude’ as if it’s a magic spell. Let’s look at the actual orders of magnitude, shall we? There are three orders of magnitude more fentanyl coming across the southern border than the northern one (21,000 lbs vs 43 lbs). To call Canada the problem is like blaming a raindrop for a flood.
On the flip side, there is a massive ‘order of magnitude’ difference in illegal gun flows. The U.S. exports thousands of illegal firearms into Canada every year—accounting for nearly 90% of crime guns in our major cities. It takes a special kind of ‘Streetwise’ genius to ignore a mountain of American-made corpses in Canada while hyperventilating over a molehill of Canadian-made chemicals.
And while we’re talking about national strength, nothing says ‘Global Leader’ quite like the U.S. administration folding on fentanyl tariffs the second Xi Jinping promised to buy more soybeans. It turns out the ‘national pastime’ isn’t suicide or hockey—it’s Washington trading its drug policy for bean exports while lecturing neighbors who actually live 5 years longer than they do. Maybe focus on your own life expectancy stats before calling the house next door a morgue
Comment by [email protected] — January 18, 2026 @ 7:56 pm
@deari yet you reference a website with articles like this? Are you sufficiently familiar with autonomous substance systems, sonar etc to validate what the author claimed?
Comment by David Mercer — January 19, 2026 @ 1:57 am
@David: the author claimed very little: heavens, he entitled his piece “A speculation on …. ” Why are you getting your knickers in a twist?
Comment by dearieme — January 19, 2026 @ 5:01 am
I see this administration continues to turn the USA (and the political content of this blog) into an episode of South Park. Maybe you can all sing “Blame Canada” as you invade a peaceful trading partner because your dear leader’s feelings were hurty-wurty.
Comment by HibernoFrog — January 19, 2026 @ 6:25 am
Deari – so the author claimed very little, yet you felt it worthy enough to post a link here. I think you’ve been away from science a bit too long (you do know proper academics read this blog? Hard to believe i know)
Comment by David Mercer — January 19, 2026 @ 11:36 am
@6 David: “ their lardy ar5es”
My “climate-denial” regular workout includes 3 sets of 70 push-ups. And you?
You brought in the notion of an apocalypse monger. Ironically, that description fits you, what with your brain-dead embrace of the CO₂ demon.
No surprise that a guy so mentally feeble – not to say so low of character – as to favor Muslim rape-gangs over British girls would also whole-hog swallow UN climate propaganda. All of a suicidal self-exculpating kind, David.
And as you were referring to my work concerning your fave millennialist apocalypse …
Air temperature projections are physically meaningless:
https://doi.org/10.3389/feart.2019.00223
The historical air temperature record is silk purse from sow’s ear:
https://doi.org/10.3390/s23135976
No evidence of a CO₂ climate-driver over the past 66 million years:
https://doi.org/10.3390/geosciences14090238
And just to tingle your social justice bone, Exxon didn’t know:
https://doi.org/10.13140/RG.2.2.11035.64808/1
Meanwhile, do enjoy snarking about those doing better while all around you the UK elite erases the Enlightenment.
The great people and extraordinary culture that derived the rights of Man, eliminated the slave trade, and brought us David Hume and John Locke now jettison freedom of speech and of conscience. Perhaps the greatest tragedy of our time. Perhaps of any time.
Comment by Pat Frank — January 19, 2026 @ 1:18 pm
Hey Pat! Do you know anything about these AI subs? Asking for a friend.
PS Is one of these the one you were so coy telling me about before?
Comment by David Mercer — January 19, 2026 @ 2:10 pm
@16: Friend?
I don’t recall being coy about any of them, once published.
What you remember may have been mention of the Cenozoic paper while still in preparation.
Comment by Pat Frank — January 19, 2026 @ 6:51 pm
Is Virginia Canada now too? These socialists stink.
Comment by jeff carter — January 21, 2026 @ 1:25 pm
Well the wheels have really flown off this whole Trump Corollary thingy, haven’t they, what with Canada striking a trade deal with China, MERCOSUR a free trade agreement with the EU, and most spectacularly, Europe collectively telling Trump to go f*ck himself over Greenland? C’mon, even you all must appreciate the sheer size and heft of Macron’s gonads, not to mention the coolness of his sunglasses. He really is da man.
I shall personally be writing to the Nobel Committee to wholeheartedly recommend Lars Rasmussen for the Peace Prize. An absolute study of cool-headed diplomacy in the face of biblical scale idiocy.
Comment by David Mercer — January 22, 2026 @ 9:01 am
@ Pat Frank, my regular workout involves 3 sets of 75 push-ups. You wimp.
Comment by [email protected] — January 23, 2026 @ 8:59 am
Pat sheesh it was only a theory based on my observations. Surely as an alleged man of science you should respect this. Intriguingly there also appears to be some connection between this site’s readership and single ladies (please please spare us details of all your conquests, if you’re feeling insecure about this too).
Libte I do likewise but with a polar bear on my back. A real man’s man you know.
Comment by David Mercer — January 24, 2026 @ 7:35 am
@21 lardy ar5es was an opportunistic disparagement of climate-alarm skeptics grounded in your ignorant prejudice, with theory a divertissement awkwardly hung upon it.
You mentioned me by name as one among them, calling for a correction to set you right.
Human-caused climate change is a pseudo-scientific crock. A Bedlam of methodological hacks.
You leave every evidence of a pseudo-commentator; pretending critiques, producing snark.
Libte, on the other hand, invariably finds a new route to inane. Nice to see you possess the flexibility to participate. Must be a benefit of your polar-bear push-ups.
“alleged man of science: https://scholar.google.com/citations?hl=en&user=kjC64S8AAAAJ
Bite your tongue, David.
Comment by Pat Frank — January 24, 2026 @ 2:28 pm
inane? who started flexing with their push up routine, of all things! it is Patrick, the silly goose.
BTW, I had some time and finally looked at your ‘Air temperature projections are physically meaningless’ article,which you looooove to cross reference to. No wonder it was cited so few times since publication.
You just say that climate model temperature projections can be well fit by a straight line, and then conclude that the models themselves are therefore linear systems.
From this category error follows the rest: systematic cloud biases are rebranded as fresh, independent errors injected every year, linear error propagation is invoked, and uncertainty is allowed to grow without bound—despite the inconvenient fact that the models remain energetically stable and reproduce observed warming.
In short, a linear fit to model output is mistaken for linear physics, bias is mistaken for noise, and the resulting explosion of uncertainty is mistaken for insight. You should hang your head in shame.
Comment by [email protected] — January 24, 2026 @ 9:13 pm
@Pat Wow you are soo incredibly tender! Guessing you regularly get it in the neck at work from your esteemed colleagues. Do they have a nickname for you Pat? Play tricks on you? Poor lickle Pat.
It’s a small mercy that you haven’t visited the UK – you wouldn’t be able to cope with the banter. Seriously, you’d leave battered and bruised.
@Pat Libte: Ahh yes, citations. Don’t mention Francis Thomas, the crazy cat woman who left Pat a very fulsome review on one of the publisher’s sites. I did tell Pat she was exactly the demographic he should be targeting, but would he listen?
Comment by David Mercer — January 25, 2026 @ 3:28 am
@Pat Oh its I who does the polar bear push ups. Do try to keep up.
Comment by David Mercer — January 25, 2026 @ 3:34 am
@23 – congratulations on learning to cut-and-paste, libte.
1. “can be well fit by a straight line”
Wrong. Projections are a linear extrapolation of the fractional change in forcing. Your climate guru can’t even get the basics correct.
2. “ models themselves are therefore linear systems.?”
Wrong. Appears nowhere in my work.
3. “cloud biases … fresh, independent errors”
Wrong. Calibration uncertainty (not bias) in long wave cloud forcing. Ironically, your guru has made a category error. Uncertainty is not error.
4. “uncertainty is allowed to grow without bound—despite the inconvenient fact that the models remain energetically stable…”
Wrong. Treats uncertainty as error. Your climate guru has made a category error yet again. Epistemic uncertainty grows without bound.
5. “… and reproduce observed warming.”
Wrong. Tuned to a trend, tracks the trend. Extrapolation of a curve-fit.
6. “mistaken for linear physics, ”
Wrong. It’s about model behavior, not climate physics.
This qualifier is made in the very first paragraph of the Results and Discussion section. Your guru is not only ignorant of calibration and resolution, he can’t read, either. Or, more likely, didn’t read the paper he criticized.
And just to add, you’ve not read it either. No surprise, as you’d not understand it. And yet you presume criticize.
7. “bias is mistaken for noise,‘
Wrong. Systematic simulation error is not noise.
8. the resulting explosion of uncertainty is mistaken for insight.”
Wrong. Uncertainty propagated time-wise presented as progressive loss of knowledge. Which it is.
9. “You should hang your head in shame.”
And so you should, libte.
Presenting other’s work as your own.
Blindly relaying the incompetence standard of midline consensus climatologists – who invariably demonstrate a lack of training in physical error analysis.
Repackaging a specious attack, criticizing what you don’t understand, can’t understand, and have made no effort to understand. The very model of an intellectual fraud.
I’ve seen it all before. I’ve successfully dealt with every criticism. Falsified, they resurrect like vampires at the invocation of yet another hostile naif.
That’s you, libte. A scientific naif, a blind copier, a pretender of critiques, a betrayer of intellect, an iterator of the inane.
Comment by Pat Frank — January 25, 2026 @ 9:05 am
@24 – I have the respect of my peers, David. A novel state for you, apparently.
I have several times visited the UK. I’ve even had British friends. Never a problem keeping up. Of course, their wit was intelligent, unlike the base cynicism you evidence here.
Francis Thomas, the crazy cat woman Unknown to me. Previously never mentioned by you. Suppose you post a link to the “very fulsome review” that pleases you so.
Francis is more typically male. Frances is the female rendition. Just thought you’d like to know.
Also, for you to put in your knowledge basket, is that scientific work does not target a demographic. Nor does any scholarly work.
By invoking a demographic target as though expected, you reveal your exclusive bent for politics. Not a surprise, really. You’ve provided nothing but political snark here.
Comment by Pat Frank — January 25, 2026 @ 9:27 am
@25, my comment in #22 about flexibility from polar bear pushups was in reference to you, David.
I was congratulating you on your facile participation in libte’s inanity.
Comment by Pat Frank — January 25, 2026 @ 9:30 am
@Pat, no idea which guru you are talking about, you strange, strange man.
The repeated cry of “Wrong” is impressive in its confidence, if not its substance. One is reminded less of physical error analysis and more of a flatulent monk shouting catechisms in an echo chamber, mistaking reverberation for refutation.
Let’s name the problem plainly, because dancing around it clearly isn’t helping:
There is a huge categorical error at the heart of what you are doing.
You take a linear fit to model output and treat it as evidence that linear time-wise uncertainty propagation applies to the system. That leap is invalid. A linear approximation to behavior over a finite interval does not make the underlying system linear, nor does it license linear error accumulation. This is not a subtle point — it is Error Analysis 101.
You insist projections are a “linear extrapolation of fractional forcing,” then protest that you never claimed the models are linear systems — all while applying linear propagation of uncertainty, which requires linearity, independence of errors, and the absence of stabilizing constraints. You deny linearity in prose while assuming it in the algebra. That contradiction is the engine of your result.
Your repeated incantation that “uncertainty is not error” only deepens the confusion. Quite right — epistemic uncertainty is not physical error. Which is precisely why it cannot be propagated in time as if it were a fresh stochastic perturbation injected into the energy budget each year. Ignorance does not radiate watts. Calibration uncertainty does not perform a random walk through the climate system. Yet your calculation treats it as if it does, allowing uncertainty to grow without bound while the modeled climate remains energetically stable.
Relabeling bias as “calibration uncertainty” does no work for you. A stationary systematic uncertainty produces a bounded spread, not an ever-expanding explosion. If cloud uncertainty behaved as you assume, GCMs would drift catastrophically within decades. They do not. Reality falsifies your propagation scheme.
Your dismissal of model skill as “tuned to a trend, tracks the trend” is sneering, not analysis. Models reproduce volcanic responses, ocean heat uptake, vertical temperature structure, and scenario divergence — none of which follow from curve fitting. Calling it extrapolation does not make it so.
You retreat to saying this is about “model behavior, not climate physics.” Fine. Then demonstrate that the behavior satisfies the conditions for linear error propagation. Show superposition. Show independence. Show the absence of energy-balance closure. You do none of this. Instead, you assert that “epistemic uncertainty grows without bound” as if repetition could transubstantiate assertion into derivation.
What actually grows without bound here is not uncertainty, but the confidence with which a basic category error is defended. A linear fit to output is mistaken for linear dynamics; stationary uncertainty is mistaken for accumulating noise; and the resulting mathematical artifact is presented as deep insight — all while insults are hurled from the safety of a self-sealed cloister.
If you have a derivation showing that GCM calibration uncertainty propagates unboundedly in time without violating energetic stability, present it. Until then, chanting “Wrong” — no matter how vigorously, or how many polar bear push-ups accompany it — does not make the math work.
Comment by [email protected] — January 25, 2026 @ 11:47 am
And just because i feel generous with my time this fine afternoon.
There is a huge categorical error at the heart of what you are doing. You repeatedly infer properties of a dynamical system from a curve fit to its output, and then apply linear time-wise uncertainty propagation as if that leap were mathematically licensed. It isn’t. Everything below follows from that mistake.
1. “Projections are a linear extrapolation of the fractional change in forcing.”
You are describing a fit, not a system. That a straight line approximates model output over a finite interval tells us nothing about whether linear error propagation applies. Cars cruising at constant speed also produce linear distance–time plots; this does not make the drivetrain linear. You are confusing emulation with dynamics — the foundational category error.
2. “Appears nowhere in my work.”
It appears the moment you propagate uncertainty linearly in time. Linear propagation assumes linearity, independence, and no stabilizing constraints. You deny linearity rhetorically while assuming it algebraically. That contradiction is not resolved by saying “I never used the word.”
3. “Calibration uncertainty (not bias) in longwave cloud forcing.”
Renaming does not rescue you. A stationary calibration uncertainty — bias by any other name — produces a bounded spread, not an ever-growing explosion. Treating it as a fresh independent perturbation each timestep is exactly the error you deny making, and exactly the one your math requires.
4. “Epistemic uncertainty grows without bound.”
This is where the flatulent monk really starts chanting.
Epistemic uncertainty is not physical error and does not accumulate in time like noise. Ignorance does not radiatively force the planet. Yet your calculation treats uncertainty as if it injected watts every year, while models remain energetically stable. You cannot have unbounded epistemic growth in a bounded physical system without violating energy balance. The contradiction is yours, not mine.
5. “Tuned to a trend, tracks the trend.”
This is not analysis; it’s sneer-as-argument. Models reproduce volcanic responses, ocean heat uptake, vertical temperature structure, and scenario divergence — none of which follow from a simple curve fit. Hand-waving this away does not make it disappear.
6. “It’s about model behavior, not climate physics.”
Fine. Then show that the behavior satisfies the conditions required for linear error propagation. Show superposition. Show independence of timestep errors. Show absence of restoring forces and energy-balance closure. You do none of this. Instead, you assert conclusions and accuse critics of illiteracy — a poor substitute for derivation.
7. “Systematic simulation error is not noise.”
Correct — which is precisely why it does not accumulate as noise. And yet your result depends on treating it exactly that way. You say one thing in English and do the opposite in mathematics.
8. “Progressive loss of knowledge.”
Loss of knowledge is not a physical process. It does not drive temperatures. Presenting epistemic decay as if it were a climate mechanism is the core confusion of the paper, and no amount of repetition will turn that confusion into insight.
9. Personal insults, plagiarism fantasies, and vampire metaphors.
Noted. They do not repair the algebra.
Comment by [email protected] — January 25, 2026 @ 11:50 am
@27 Yup, definitely tender.
Fell into my trap fella! You know exactly which Frances I’m talking about.
As for my peers, you (and everyone else here) know nothing about me. Must drive you nuts. So you grasp at straws.
Comment by David Mercer — January 25, 2026 @ 1:26 pm
@29 “You take a linear fit to model output and treat it as evidence that linear time-wise uncertainty propagation applies to the system.”
Wrong, right from the start. The emulations are calculated using the Meinhausen standard scenario forcings. They’re not fits.
“You are describing a fit, not a system.
Wrong. The emulation demonstrates that CMIP5 air temperature projections are linear extrapolations of the fractional change in forcing. The projections are mere sums.
Linear sums are subject to linear propagation of uncertainty. That’s standard in science.
protest that you never claimed the models are linear systems”
I’ve never claimed the models are linear systems. I’ve shown their temperature projections are linear in fractional forcing. Not the same thing at all. Output is not model. The category error is yours.
“independence of errors, ”
Uncertainty is not error. You’ve made yet another category error.
“the absence of stabilizing constraints.
You’re confusing uncertainty with error again. Epistemic uncertainty bounds are not metric of model divergence.
Quite right — epistemic uncertainty is not physical error.”
And yet you repeatedly treat it as though it were error.
“Which is precisely why it cannot be propagated in time as if it were a fresh stochastic perturbation injected into the energy budget each year.”
Wrong. The propagation is per iterative step. And you’re treating uncertainty as though physical error (“stochastic perturbation“) yet again.
“Ignorance does not radiate watts. ”
Epistemic uncertainty is about the state of knowledge, not the state of the model. With each iterative step, ignorance grows of the phase-space relation of simulated climate state and physical state of the future climate. It’s all explained in my paper and even further in the SI. Perhaps you should read them.
“allowing uncertainty to grow without bound while the modeled climate remains energetically stable.”
Wrong. You’re confusing uncertainty with error, yet again.
“A stationary systematic uncertainty..”
Good job assuming your conclusion. Model cloud error is not stationary. It’s funny – you here confused uncertainty with error, an inversion of your usual mistake.
“Relabeling bias as “calibration uncertainty” does no work for you.”
Inversion of fact. You are relabeling calibration uncertainty as a bias, which it is not.
“Models reproduce volcanic … blah, blah…”
Your list didn’t include the air temperature projections – which are the subject of my paper, and this discussion. That absence testifies to disingenuity, or perhaps to ignorance.
“Calling it extrapolation does not make it so.”
Demonstrating it as extrapolation does make it so. And demonstrations they are.
“Then demonstrate that the behavior satisfies the conditions for linear error propagation.”
The paper and SI include 58 such demonstrations.
“you assert that “epistemic uncertainty grows without bound” as if repetition could transubstantiate assertion into derivation.”
No. I stated that as though you understood epistemic uncertainty. You don’t, as amply demonstrated by your repeated mistaken attribution to error.
“ A linear fit to output is mistaken for linear dynamics; ”
Wrong and wrong. A successful linear emulation demonstrates linear output.
“stationary uncertainty is mistaken for accumulating noise”
Wrong, wrong, and wrong. Error not uncertainty. Simulation error is not stationary. Systematic error is not noise.
Simulation error => calibration uncertainty => iterative decline in knowledge.
“… and the resulting mathematical artifact is presented as deep insight”
Propagation of uncertainty through an iterative calculation is standard; not artifactual.
“— all while insults are hurled from the safety of a self-sealed cloister.”
Ironic coming from you, libte, given as you are to insulting diminutives, and given that you have previously admitted to being a medical shut-in.
“without violating energetic stability, ”
You’re treating epistemic uncertainty as physical error – model divergence – yet again.
You’ve failed to grasp the basics of the analysis, libte. Or whoever it is that has written that for you.
Noting your invariably mistaken thinking is not to chant wrong, libte. It is merely to summarize the itemized poverty of your responses.
Comment by Pat Frank — January 25, 2026 @ 1:35 pm
@30 – just a repetition of your #29. Fully answered in my #32.
A heuristic to clarify epistemic uncertainty: ignorance = 1/knowledge. As knowledge => zero, ignorance => infinity.
Comment by Pat Frank — January 25, 2026 @ 1:40 pm
@31 “Fell into my trap fella!”
How convenient for you.
“You know exactly which Frances I’m talking about.”
I’ve no idea at all, honestly.
“you (and everyone else here) know nothing about me.”
A benefit, surely. I do know of you that you favor Muslim rape gangs over British girls.
“Must drive you nuts.”
Haven’t a care about your selfhood.
“ So you grasp at straws.”
Observing that you produce monobrow snipery where critical thought is appropriate is no mere straw.
Comment by Pat Frank — January 25, 2026 @ 1:48 pm
@Pat,
Thank you — this finally clarifies the mistake beyond any doubt.
You now state explicitly:
“The projections are mere sums. Linear sums are subject to linear propagation of uncertainty.”
This sentence is the categorical error, fully exposed.
A sum of outputs is not a license to propagate uncertainty linearly in time unless the underlying mapping from uncertainty to output is linear, independent, and unconstrained. You keep insisting “output is not model,” while simultaneously treating the output as if it were generated by a linear, memoryless process. You cannot amputate the model and keep its algebra.
Your emulation showing that temperature output is linear in fractional forcing does not establish that uncertainty in cloud forcing maps linearly, independently, or additively through iterative timesteps. It establishes only that a straight line can approximate the mean trajectory. That is curve emulation, not system identification. This distinction is elementary, and repeating “demonstration” does not make it disappear.
The decisive point — which you continue to dodge — is this:
Epistemic uncertainty is not a state variable.
It does not evolve under the model’s equations.
It does not accumulate through timesteps unless you explicitly assume independence and lack of constraint.
When you say:
“With each iterative step, ignorance grows of the phase-space relation…”
you have quietly left physics altogether. You are no longer propagating anything through the model; you are asserting that our ignorance grows because time passes. That may be a philosophical claim about knowledge, but it is not a mathematical justification for √t uncertainty growth in projected temperature.
Your “heuristic” — ignorance = 1/knowledge, therefore ignorance → ∞ — is not physics, not error analysis, and not even statistics. It is rhetoric dressed up as algebra. By this logic, all forecasts in all sciences become meaningless by construction, regardless of skill, constraints, or validation. That is not insight; it is nihilism with symbols.
You repeatedly accuse others of “treating uncertainty as error,” yet your entire result depends on treating epistemic uncertainty as if it behaved like accumulating stochastic error, while simultaneously insisting it is not error. That contradiction is never resolved — only restated, more loudly, with insults appended.
And this is why the energetic stability point matters, no matter how often you wave it away:
If your propagated uncertainty had any physical meaning, it would manifest as divergence, drift, or loss of constraint. It does not. The system remains bounded because the uncertainty you are propagating is not a dynamical quantity. You are inflating ignorance, not temperatures.
At bottom, this is simple:
A linear-looking output does not imply linear dynamics.
A linear sum does not justify linear time-wise uncertainty propagation.
Epistemic uncertainty is not a mechanism.
Loss of knowledge is not a climate process.
What does grow without bound here is the insistence that repeating these confusions constitutes a refutation. At this point, the argument resembles a flatulent monk in an echo chamber, chanting “Wrong” while mistaking the reverberation for validation.
Unless you can show — explicitly — that uncertainty in cloud forcing propagates through the model as an independent, additive quantity without invoking the very linear-system assumptions you deny, there is nothing left to discuss.
You have asserted. You have insulted. You have not derived.
That is not error analysis. It is theater.
Comment by [email protected] — January 25, 2026 @ 6:27 pm
“Thank you — this finally clarifies the mistake beyond any doubt.
You will be shown indulging in bluster and living in a meritless fantasy.
You quoting me: “The projections are mere sums. Linear sums are subject to linear propagation of uncertainty.”
“This sentence is the categorical error, fully exposed.
A sum of outputs is not a license to propagate uncertainty linearly in time…”
Uncertainty is propagated as root-sum-square (RSS) through a sum. Air temperature projections are a linear sum. Uncertainty is propagated as the RSS. Your reference to time is an irrelevant methodological non-sequitur.
“… while simultaneously treating the output as if it were generated by a linear, memoryless process”
No. Demonstrating that model output is successfully emulated as linearly dependent on the fractional increase in forcing. A sum is not memoryless.
“does not establish that uncertainty in cloud forcing maps linearly, independently, or additively through iterative timesteps.”
On the contrary, it does so. The output is linear, the uncertainty conditions every iterative result, a projection is the iterative sum of results, the uncertainty in a sum of results is the RSS of the entering uncertainties.. And thats Q.E.D. no matter your protests.
“It establishes only that a straight line can approximate the mean trajectory.”
No. It establishes that an equation linear in fractional forcing can successfully emulate the specific air temperature projection of any given CMIP5 model. Not a straight line,. Not the mean.
“That is curve emulation, not system identification”
Wrong again. That is model output emulation. System identification, whatever that is, is irrelevant.
“Epistemic uncertainty is not a state variable.
It does not evolve under the model’s equations.
It does not accumulate through timesteps unless you explicitly assume independence and lack of constraint.”
Epistemic uncertainty is an ignorance metric conditioning a state variable.
It varies with model reliability.
It accumulates with the iterative steps.
It has no physical constraint.
“you have quietly left physics altogether.”
Phase space is the home ground of physics.
“You are no longer propagating anything through the model;..”
I never propagated anything through a (climate) model. You’ve drifted off into critical Never-Neverland
“you are asserting that our ignorance grows because time passes.”
No. I demonstrate that ignorance grows with the number of iterative steps. That’s not philosophy. It’s ultra basic reliability analysis,
“Your “heuristic” — … is nihilism with symbols.”
No. It is assertional modesty in the face of ignorance. Something you apparently do not inhere. Future climate states are unknowable. Error-ridden models do not produce reliable forecasts.
“yet your entire result depends on treating epistemic uncertainty as if it behaved like accumulating stochastic error,”
Wrong. My result depends on treating the uncertainty in a sum as the RSS of the uncertainty in each entering variable.
“while simultaneously insisting it is not error.”
Error = (observation minus simulation).
Uncertainty = (+/-)u (RSS or RMS, depending upon the analysis)
Uncertainty is not error. Uncertainty increases across a sum.
That contradiction is never resolved — only restated, more loudly, with insults appended.
There is no contradiction in my argument. RSS propagation of uncertainty in a sum is standard. .
I’ve not commented in all-caps. No loudness, ever, not even symbolic.
Insults?
Who wrote “You wimp.
Patrick, the silly goose.
you strange, strange man.
flatulent monk (thrice)”
As for what I wrote, “That’s you, libte. A scientific naif , a blind copier, a pretender of critiques, a betrayer of intellect, an iterator of the inane.” none is an ad hominem. All refer to states or behaviors. None refer to the person. Categorically at variance with yours.
“If your propagated uncertainty had any physical meaning, it would manifest as divergence, drift, or loss of constraint.”
Wrong, wrong, wrong. Utterly wrong. Epistemic uncertainty is not error. It has no physical magnitude. It is a reliability statistic. It has no impact on model output. It does not indicate model output or drift. It is not a perturbation or a divergence.
The system remains bounded…”
True. But the model output becomes physically meaningless when the uncertainty bound exceeds any possible physical state. As it does in an air temperature projection.
“A linear-looking output does not imply linear dynamics.”
A linear output implies a linear output. Demonstrated 58 times. Others than I have noted the same model behavior and have published on it. None have taken that result and gone on to propagate uncertainty, however.
“A linear sum does not justify linear time-wise uncertainty propagation.
Epistemic uncertainty is not a mechanism.
Loss of knowledge is not a climate process.”
A linear sum requires RSS uncertainty.
Epistemic uncertainty conditions physical reliability.
Loss of knowledge removes confidence in a result.
“the insistence that repeating these confusions constitutes a refutation”
Any standard book on uncertainty in the physical sciences will provide you an example of propagating uncertainty as RSS through a sum.
Your insistent denials of that standard method does not constitute a refutation.
“Unless you can show — explicitly — that uncertainty in cloud forcing propagates through the model as an independent, additive quantity…”
Uncertainty does not propagate through a model Error propagates through a model. Uncertainty conditions a result. You never get it right.
In terms of an air temperature projection the error can never be known, because there are no observed air temperatures from the future against which to evaluate the projection.
And the deployed physical theory is deficient.
“without invoking the very linear-system assumptions you deny,”
I made no assumption about linearity. I demonstrated a linearity of output. Which you deny.
“You have asserted. You have insulted. You have not derived.”
I have demonstrated. I have enumerated your repetitive mistakes. I have explained.
All the ad hominem insults in this thread source from you.
“That is not error analysis. It is theater.”
You’ve been analytically mistaken throughout, libte. Your final remark is of another of that kind.
Comment by Pat Frank — January 25, 2026 @ 8:18 pm
@Pat,
This is where the argument finally collapses, and no amount of repetition will prop it back up.
You keep asserting:
“Air temperature projections are a linear sum. Uncertainty is propagated as RSS. Q.E.D.”
That sounds orthodox, but it quietly assumes what you have never shown: that the uncertainties you are RSS-propagating are independent, additive, and unconditioned by system constraints. They are not.
RSS propagation applies when:
The mapping from inputs to outputs is linear in the uncertainties,
The uncertainties are independent random variables, and
The system does not re-constrain outcomes between steps.
None of those conditions are satisfied here.
You have demonstrated that mean temperature output can be emulated linearly in fractional forcing. Fine. That says nothing — nothing — about how uncertainty in cloud forcing maps through the system over time. You have inferred uncertainty behavior from mean behavior. That inference is invalid.
A projection being a sum of results does not imply that uncertainty accumulates as √N unless each contribution injects a fresh, independent uncertainty into the result. You never establish that. You merely assert it.
And this is the crux you keep sliding past:
Epistemic uncertainty is not an increment.
It is not drawn anew at each timestep.
It is not an additive random variable.
It does not “enter” a sum.
It is a bound on confidence, conditional on model structure and calibration. Treating it as a sequence of independent terms — which is exactly what RSS across timesteps does — is a category error, no matter how many textbooks you wave around that apply RSS to measurement noise.
Your own statements concede the point:
You say epistemic uncertainty is not physical error.
You say it has no physical magnitude.
You say it does not perturb the model.
Yet you propagate it exactly as if it were stochastic error injected at each step. You deny the assumption in prose and rely on it in algebra.
That is the contradiction.
If epistemic uncertainty truly “accumulates with iterative steps” purely because time passes, then all long-range forecasting in every science becomes meaningless by construction — economics, orbital mechanics, demography, epidemiology — regardless of validation or constraint. That is not error analysis; it is nihilism with notation.
And finally, the stability point does matter, no matter how often you insist it doesn’t. A quantity that grows without bound while the system remains bounded is not a property of the system. It is a property of the analyst’s bookkeeping.
You haven’t shown that uncertainty propagates.
You’ve shown that you are repeatedly counting the same ignorance as if it were new information loss each step.
That’s not derivation. That’s double-entry confusion.
At this point the disagreement isn’t about climate. It’s about whether epistemic limits are allowed to masquerade as dynamics.
They aren’t.
Comment by [email protected] — January 25, 2026 @ 10:30 pm
@38 “what you have never shown: that the uncertainties you are RSS-propagating are independent, additive, and unconditioned by system constraints. They are not.”
The uncertainty is constant. Not a plural. It is a RMS. It is singular. It is independent. It is not correlated. It conditions every single iterated step of a simulation.
These traits are characteristic of any calibration uncertainty. The uncertainty in a sum is RSS of the uncertainties of the entering elements. When every element has the identical uncertainty – as in this case – that uncertainty propagates as the root-sum-square through the sum. Uncorrelated. Independent.
“The mapping from inputs to outputs is linear in the uncertainties,”
Projections are linear sums. The elements include constant uncertainty.
“The uncertainties are independent random variables,”
There you go, yet again confusing uncertainty with error.
“The system does not re-constrain outcomes between steps.”
The uncertainty statistic is not part of the model system and is not subject to a physical constraint.
“None of those conditions are satisfied here”
Your first is satisfied. Your second and third are inapplicable misconstruals.
“You have demonstrated that mean temperature output can be emulated…”
Wrong. I have demonstrated that air temperature projections are successfully emulated. Not means. Each explicit projection. That’s twice you’ve misrepresented the case.
“about how uncertainty in cloud forcing maps through the system over time”
Irrelevant. The calibration uncertainty is not part of the system. It does not pass through the system. It never passes through the system. It has no impact on the system. It is independent of the system.
“You have inferred uncertainty behavior from mean behavior.”
Wrong. I have demonstrated that air temperature projections are linear in the fractional change in forcing. The demonstration is not restricted to a mean.
“A projection being a sum of results does not imply that uncertainty accumulates as √N unless each contribution injects a fresh, independent uncertainty into the result. You never establish that. You merely assert it.”
Several wrongs. 1. Systematic uncertainty does not vary as √N. 2. Systematic uncertainty is not random. 3. You’ve mistaken uncertainty for physical error, again. 4. The long wave cloud forcing (LWCF) uncertainty reflects deficient model physics. It therefore enters into and conditions every single simulation step. Incorrect states are propagated incorrectly. Every stepwise initial condition in an iterative simulation is wrong. Every step in a projection is simulated incorrectly.
The starting state is wrong; the simulation is wrong; the end state is wrong. But the errors of the simulated state are all unknowable. Uncertainty necessarily grows with the sequence of serially incorrect steps. The iterative logic is strict and obvious.
If one cannot reason through that obvious logic, one has no business offering a criticism.
The logic of propagation is discussed on pages 9-12, under the section Linear Models and Error Propagation and further in Sections 7.1.2-7.3 and Section 10 in the Supporting Information.
“”And this is the crux you keep sliding past:
Epistemic uncertainty is not an increment. It is not drawn anew at each timestep. It is not an additive random variable. It does not “enter” a sum.”
Epistemic uncertainty conditions the reliability of every model.
The model injects epistemic uncertainty into every simulation step.
Epistemic uncertainty is indeed not a random variable. Leaving me to wonder why it is you continue to mistake it as such.
Epistemic uncertainty is a (+/-) reliability metric of every stepwise temperature state summing into a projection. The RSS of the uncertainties of the projected temperatures yields the uncertainty of the sum.
It’s this easy: A(+/-)a + B(+/-)b = C(+/-)[√(a²+b²)]. Standard practice.
In an air temperature projection, Tᵨ±Uᵨ = t₁±u₁+t₂±u₂+ … +tn±un, where Tᵨ, the projection temperature, is the any-length sum of the series of iterative intermediate temperature states ’tᵢ’. The ±uᵢ are the calibration uncertainty in each intermediate tᵢ, and ±Uᵨ = the RSS of √[(±u₁)²+(±u₂)²+ … +(±un)²] is the epistemic uncertainty in the projection temperature. The epistemic uncertainty grows without bound. It is a statistic and not energetically constrained.
If you can’t see that, and see how it strictly applies to a linear sum of projected air temperatures, then you’re beyond reach and we’ve nothing left to discuss.
“It is a bound on confidence, conditional on model structure and calibration. Treating it as a sequence of independent terms — which is exactly what RSS across timesteps does — is a category error,”
Your argument is self-contradictory. You concede that the uncertainty is conditional on model structure (i.e., on deficient physics), and then deny that a structural deficiency in the model itself does not condition every iterative step made using that very model.
“Your own statements concede the point:
You say epistemic uncertainty is not physical error. True
You say it has no physical magnitude. True
You say it does not perturb the model. True
Yet you propagate it exactly as if it were stochastic error injected at each step. You deny the assumption in prose and rely on it in algebra.” False.
I propagate it exactly as if it were a systematic uncertainty that conditions every single iterative step of the climate model, which is what it is and what it does. The model is itself conditioned by that calibration uncertainty. The uncertainty is an operational trait of the model. Every iterative step adds further uncertainty to the uncertainty of the prior state.
That is the contradiction.”
It’s not a contradiction. It is the correct way to propagate systematic uncertainty through a sum. It accounts for a calculational uncertainty that enters every step of a serial calculation.
“If epistemic uncertainty truly “accumulates with iterative steps” purely because time passes,…”
This makes at least 3 times you’ve forwarded that very same mistake. The uncertainty propagates with iterative step. Not with time.
“then all long-range forecasting…”
Forecasting is subject to propagated uncertainty. If model parameters are poorly constrained, the forecast rapidly becomes unreliable. Such is life, and such is one reason why science is so difficult.
None of your list is a physical science, by the way, except orbital mechanics. Even there, well-known that it is, chaos makes the orbits become unpredictable over long times. Even Newton understood that. And just to add, weather prediction would be impossible were not the models updated with fresh data every 2-4 hours. Given the difficulties, theres plenty of cavalier model use out there.
“A quantity that grows without bound while the system remains bounded is not a property of the system.”
It is a property of the result. And to be clear, the unbounded epistemic uncertainty does reflect a property of the system, namely the large and many deficiencies of the physical theory. In climate models, deficiencies are hidden by tuning.
“It is a property of the analyst’s bookkeeping.”
It is a reflection of complete ignorance concerning the phase-space relationship of the simulated future climate state relative to the physically correct future climate state.
“You haven’t shown that uncertainty propagates.
Rather, I have done. It’s in the paper and SI that you have not read. It is summarized in the equations provided above.
“You’ve shown that you are repeatedly counting the same ignorance as if it were new information loss each step.
I’ve shown that model uncertainty makes its contribution to every calculational step the physics-deficient model produces. It’s not a difficult concept.
“That’s not derivation. That’s double-entry confusion.”
Wrong. The uncertainty enters with the model iteration.
”At this point the disagreement isn’t about climate.
The disagreement has never been about climate. It’s been about conditioning model output.
“It’s about whether epistemic limits are allowed to masquerade as dynamics.”
A cardinal mistake. Even you should have realized that an uncertainty statistic invariably presented as conditioning model output can never be represented as model dynamics.
It seems impossible that you could have made such a gross misrepresentation. Maybe you became over-tired.
“They aren’t.”
True, and never described as such.
Your entire post here is merely a re-worded version of your prior attempts at criticism.
You can go on and throw your arguments into the ring again as you like, But there’s no profit to be made continuing a debate made sterile by an insistent lack of understanding. Your arguments have carried no analytical or critical force, though transmitting considerable passion.
So, post again as you like. I’ll not reply. You may have the last word(s).
The record of our debate is here for any to apprehend, for the foreseeable future. Anyone curious enough can go through it. The analytically competent will grasp the tale. The passionately committed (AGW believers) will never do.
So it’s always been. Cult members rarely leave the fold, no matter the overwhelming evidence against.
Comment by Pat Frank — January 26, 2026 @ 1:09 am
@Pat,
You asked for the last word. Here it is — point by point, no rhetoric required.
1. “The uncertainty is constant. Singular. Independent. Uncorrelated.”
This is your first fatal error, and everything downstream depends on it.
A constant calibration uncertainty is not an independent contribution at each step. Independence is a property of random variables, not labels. A single systematic uncertainty conditioning all states is perfectly correlated across timesteps, not independent.
If u1 equals u2 equals … equals un equals u because they arise from the same model deficiency, then:
Covariance between ui and uj equals u squared, for all i and j.
The correct propagation for a sum with perfect correlation is linear growth, not RSS:
Total uncertainty equals u1 plus u2 plus … plus un.
If each step has the same uncertainty magnitude u, this becomes:
Total uncertainty equals n times u.
You explicitly deny this by insisting on RSS, which assumes zero covariance. You never justify zero covariance — you merely assert it.
That is not uncertainty analysis. It is assumption laundering.
2. “Calibration uncertainty conditions every step, therefore RSS applies.”
No. This is exactly backwards.
If the same calibration uncertainty conditions every step, then it does not enter the sum multiple times. It conditions the mapping, not the outputs.
You are committing a textbook double-counting error: counting one epistemic deficiency once per timestep as if it were freshly sampled.
That is why your uncertainty “grows without bound” while the system remains stable — because you are repeatedly summing the same ignorance.
3. “A projection is a linear sum, therefore uncertainty RSS-propagates.”
False — and this is the core categorical error.
Uncertainty propagates through a sum only if each term contributes an independent uncertainty.
You never establish that u1, u2, u3, … un are independent.
You explicitly say they arise from the same deficient physics.
That makes them correlated, which invalidates RSS.
You cannot simultaneously argue:
– “This uncertainty reflects the same model deficiency everywhere,” and
– “Each timestep contributes an independent uncertainty.”
Those statements are mutually exclusive.
4. “Epistemic uncertainty accumulates with iterative steps.”
Only if new information is lost or new uncertainty is injected.
You introduce neither.
Iteration over a deterministic model with fixed parameters does not increase epistemic uncertainty. It merely maps the same uncertainty forward.
If iteration alone caused epistemic uncertainty to grow, then orbital ephemerides, numerical weather models with fixed parameters, CFD solvers, and population projections would all become meaningless purely by timestep count — which they demonstrably do not.
Your rule destroys all long-horizon modeling, not just climate.
That is not skepticism. That is nihilism.
5. “Systematic uncertainty propagates as RSS through a sum.”
Flatly wrong.
Systematic uncertainties do not propagate as root-sum-square unless decorrelated — which you never show and cannot show, because the uncertainty source is singular.
Every uncertainty text says this explicitly.
You cite “standard practice” but never quote a source that applies RSS to perfectly correlated epistemic uncertainty across serial states.
Because no such source exists.
6. Your equation in words
You are effectively asserting:
Projected temperature plus or minus total uncertainty equals
the sum over i of (temperature change at step i plus or minus uncertainty at step i),
with total uncertainty equal to the square root of (u1 squared plus u2 squared plus u3 squared plus … plus un squared).
That equation assumes what you deny:
– that each ui is a random variable,
– that the ui are uncorrelated, and
– that uncertainty “enters” the sum as an increment.
But epistemic uncertainty is not a stochastic draw, by your own repeated insistence.
You cannot use the algebra of random variables while denying randomness.
That contradiction is terminal.
7. “Uncertainty is not error; error propagates, uncertainty conditions.”
Correct — and fatal to your own case.
If uncertainty merely conditions the result, then it does not propagate through arithmetic. It bounds confidence in the outcome once, not once per timestep.
You do not propagate confidence bounds by summing them.
You report them.
8. “The model injects epistemic uncertainty into every step.”
No. The analyst injects it by repeatedly counting the same deficiency.
The model evolves states.
The uncertainty bounds the trustworthiness of those states.
Confusing those two is the entire failure mode here.
9. “Unbounded uncertainty reflects model deficiency.”
No — it reflects incorrect bookkeeping.
A bounded system with unbounded uncertainty is a red flag that the uncertainty is not a physical or informational quantity, but an artifact of propagation rules misapplied outside their domain.
Physics did not fail here. Statistics did.
10. Final clarification
Show — not assert — that epistemic uncertainty in cloud forcing produces independent uncertainty contributions at each timestep.
Not rhetoric.
Not repetition.
Not “standard practice.”
A derivation.
You cannot do this, because the uncertainty source is singular and structural. That makes it correlated by definition.
Bottom line –
A linear output is not a linear uncertainty map.
A sum of states is not a sum of ignorance.
Epistemic uncertainty is not an increment.
Root-sum-square does not apply to correlated, non-random quantities.
What grows without bound in your analysis is not uncertainty — it is the number of times the same uncertainty is counted.
That is not error analysis. That is double-entry ignorance accounting.
Comment by [email protected] — January 26, 2026 @ 7:06 am