Tag: hypothesis

Muddling the Judiciary’s Understanding of Science

While an educational manual for federal judges was improved when a biased representation of climate change was removed, a remaining chapter on the fundamentals of science would poison the judiciary with quackery.

From CO2 COATITION

by Sharon Camp

While an educational manual for federal judges was improved when a biased representation of climate change was removed, a remaining chapter on the fundamentals of science would poison the judiciary with quackery.

The “How Science Works” chapter of the “Reference Manual on Scientific Evidence” allows for an overreliance on the unproven assumptions of computer models and an acceptance of “consensus” as proof even when contradicted by empirical evidence.

This violates tenets of the hundreds-year-old Scientific Method that require data obtained through experimentation or observation of the physical world as the means of supporting scientific conclusions. The undue regard for models and consensus is emblematic of climate alarmists whose claims fail scrupulous examination and whose views are shared by at least one of the chapter’s authors.

In defining the concepts of hypothesis, theory and scientific law, the writers exclude the elements of testing, observation and experimentation. Neither is it acknowledged that all three can be disproven, even though the ability to demonstrate the falseness of a conclusion has long been recognized as the path to advancing scientific knowledge.

Along these lines, the chapter even says that science cannot “disprove hypotheses,” although science has done so many times. A famous example is geocentricism that was supplanted in the 1500s by the heliocentric theory of Copernicus. Others include phrenology, eugenics, spontaneous generation and miasma theory of disease. All were embraced by much of the scientific community of their time – a consensus – until proven false. German scientist Alfred Wegener was dead for 30 years – and rejected by a consensus of his peers – before his theory of plate tectonics gained support in the last half of the 20th century.

The authors may misunderstand the Scientific Method. Or perhaps they believe that computer models relying on unproven assumptions that fail to explain or predict outcomes should be accepted over the extensive experimentation and observation required by the Scientific Method.

The chapter also misses the mark with this statement: “In the context of testing hypotheses, the term prediction refers to a logical consequence of a hypothesis, not necessarily what will happen in the future.” On the contrary, a prediction is all about what will happen in the future. Either objects of different weights dropped from the same height in a vacuum hit the ground at the same time or don’t. (They do.) A hypothesis also can be tested by determining whether it can explain something that has happened in the past.

Are the authors saying that a hypothesis paired with a model is sufficient confirmation, even when they fail to predict the future or explain the past? Or perhaps they believe that computer models predicting the climate 50-100 years in the future are more accurate than weather models that are reliable less than a week in advance — and sometimes failing that.

Apparently, there is no need to fret about such failures because the authors say: “The fact that there is room for improvement in the process of science does not necessitate distrust of hypotheses that have gained widespread acceptance in the scientific community and about which consensus has been achieved.” This is a justification for using consensus as a defense against evidence that challenges a popular narrative – a common ploy of climate alarmists.

In places, the chapter is self-contradictory. For example, the writers seem to embrace key elements of the Scientific Method when they say that a testable hypothesis must ultimately predict a set of observations that could or could not be made. This suggests a less cavalier relationship with traditional science than exhibited elsewhere, such as when key features of hypotheses and theories are omitted from their definitions. Unfortunately, the contradiction conveys a desire “to have it both ways” more than a commitment to rigorous scientific inquiry.

Ultimately, the chapter’s confusions and inordinate 62-page length muddy a reader’s understanding of the Scientific Method. More problematic, the writers introduce wrongheaded practices like the overuse of models and consensus in settling important questions. Such departures from the empirical tradition of Isaac Newton and Marie Curie make for superficial and specious investigations of reality known as pseudoscience.

Having received objections from state attorneys general and others, U.S. District Judge Robin Rosenberg excised the offending chapter on climate change from the reference manual. This is a remedy that needs to be applied by the National Academies of Sciences, Engineering and Medicine, which still includes the chapter on its website.

In the meantime, as head of the Federal Judicial Center, the manual’s publisher, Judge Rosenberg should do the same with “How Science Works.” The judiciary and the public it serves deserve nothing less.

Originally published in The Blaze on March 3, 2026.

Sharon Camp, senior education advisor for the CO2 Coalition, Fairfax, Virginia, has a Ph.D. in analytical chemistry, Georgia Institute of Technology, and has worked for the U.S. Environmental Protection Agency and as an advanced placement science teacher.

What’s New!

The CO2 Coalition has released its new episode of the Climate Debrief Podcast featuring Ron Stein. Watch the full video here!

Scientific Report or Legal Brief? The Hunga Tonga Assessment and the Anatomy of Narrative Closure

When the Hunga Tonga–Hunga Haʻapai volcano erupted in January 2022, it immediately posed a problem—not merely scientific, but institutional. The eruption was the most explosive in the satellite era, injected an unprecedented quantity of water vapor into the stratosphere, and did so with a chemical signature unlike the canonical climate-cooling eruptions of the late twentieth century.

A massive volcanic eruption at Hunga Tonga–Hunga Haʻapai, with thick ash and steam clouds billowing into the atmosphere.

From Watts Up With That?

By Charles Rotter

When the Hunga Tonga–Hunga Haʻapai volcano erupted in January 2022, it immediately posed a problem—not merely scientific, but institutional. The eruption was the most explosive in the satellite era, injected an unprecedented quantity of water vapor into the stratosphere, and did so with a chemical signature unlike the canonical climate-cooling eruptions of the late twentieth century. It was followed, inconveniently, by a pronounced surge in global surface temperatures. The timing alone guaranteed scrutiny. What mattered was how that scrutiny would be framed.

Cover of the Atmospheric Impacts Report 2025 on the Hunga volcanic eruption, featuring multiple satellite images of the volcano's eruption and ash cloud.
https://juser.fz-juelich.de/record/1049154/files/Hunga_APARC_Report_full.pdf

The resulting assessment report is vast, meticulous, and technically competent. It documents the eruption and its atmospheric aftermath in extraordinary detail, particularly in its observational chapters. Satellite measurements are cross-validated, transport pathways mapped, and instrumental uncertainties repeatedly acknowledged. The early sections read as careful empirical science, and much of the observational synthesis is genuinely valuable.

But the report is not merely descriptive. From its opening highlights onward, it signals a specific destination.

“The record-high global surface temperatures in 2023/2024 were not due to the Hunga eruption.”

That sentence appears in the Highlights section, not buried in the discussion, and not framed as provisional. It is one of the few categorical statements in the entire summary. Its placement matters. In a scientific inquiry, conclusions typically emerge from analysis. In this document, the conclusion precedes it.

The report then devotes hundreds of pages to ensuring that this statement remains unthreatened.

To be clear, the authors do not deny that Hunga was extraordinary. On the contrary, they emphasize repeatedly that the eruption was unique in the observational record.

“The stratospheric hydration caused by the eruption was unprecedented in magnitude, altitude, and duration in the satellite record.”

That admission alone makes the subsequent dismissal of surface relevance nontrivial. Water vapor is not an exotic or speculative climate agent; it is the dominant greenhouse gas. An unprecedented perturbation at climatically sensitive altitudes is, at minimum, a legitimate explanatory candidate.

The report quantifies that perturbation carefully.

“Hunga injected an exceptional amount of water into the stratosphere, causing a ~10% (~150 Tg) increase in the global stratospheric water vapour burden.”

This is not a rounding error. Yet from this point forward, the analytical burden shifts. The question ceases to be what such an injection might plausibly do and becomes how its effects can be shown to dissipate, fragment, or sink below detectability.

Radiative forcing estimates are produced. The report arrives at a net top-of-atmosphere forcing of roughly −0.4 W/m² over the first two years, dominated by short-lived aerosol effects and partially offset by water vapor. From this, a small surface temperature response is inferred, followed immediately by a critical concession.

“As a consequence of the negative TOA RF, the Hunga eruption is estimated to have decreased global surface air temperature by about 0.05 K during 2022–2023; due to larger interannual variability, this temperature change cannot be observed.”

This sentence does more work than the report seems to recognize. An effect that cannot be observed, cannot be separated from noise, and cannot be detected empirically is not a finding; it is a boundary. It defines what must be ignored.

The report repeatedly emphasizes this indistinguishability.

“Surface climate impacts of the eruption… are relatively small and not distinguishable from the background internal variability of the Earth system.”

Internal variability thus becomes a one-way gate. It is sufficient to dismiss Hunga’s influence, but it is not subjected to the same analytical pressure as an explanatory mechanism in its own right. Variability explains by default; Hunga must explain beyond reasonable doubt.

This asymmetry is reinforced through modeling. The report leans heavily on global chemistry–climate models, repeatedly stressing their importance.

“Models are critical tools to elucidate the detailed chemical, radiative, and dynamical impacts on the Earth system from volcanic events, especially in the context of interannual variability.”

Yet these same models are acknowledged to diverge in key respects.

“Models differ in their simulations of Hunga aerosol microphysical properties, indicating that simulating aerosol microphysics remains a challenge for model development.”

Differences in aerosol growth rates, sedimentation, cross-equatorial transport, and decay times are treated as technical hurdles rather than epistemic warnings. Model spread does not weaken conclusions; it merely motivates more modeling.

When transport-driven ozone anomalies are discussed, the report concedes limits to causal attribution.

“The extent to which transport anomalies were causally connected to the eruption is not clear.”

This admission is quietly devastating. It acknowledges that large observed anomalies coincided with Hunga but cannot be cleanly attributed to it. Rather than opening the possibility that attribution itself may be structurally weak, the report uses this ambiguity to cordon off surface relevance altogether.

The same pattern recurs in the discussion of circulation effects.

“In the NH, observed stratospheric meteorological conditions following the Hunga eruption were within the range of interannual variability, and model simulations show no consistent circulation response.”

No consistent response becomes synonymous with no meaningful effect. The possibility that the climate system simply lacks the resolution to isolate short-term forcings of this type is never seriously entertained.

Perhaps the most revealing sentence in the entire document appears not in the science chapters but in the forward-looking institutional context.

“Models are critical tools to elucidate the detailed chemical, radiative, and dynamical impacts on the Earth system from volcanic events, especially in the context of interannual variability.”

This is less a methodological statement than a declaration of dependence. Where observations fail to resolve attribution cleanly, models are invoked to close the question.

The report also makes clear that its remit extends beyond pure inquiry.

“This report has aligned closely with… upcoming international assessments.”

That alignment explains much. An open-ended conclusion—that a large, natural, poorly constrained event may have contributed meaningfully to recent warming—would complicate attribution frameworks that depend on trend continuity. Ambiguity was not an acceptable endpoint.

Instead, the hypothesis is exhausted. Not falsified, but procedurally neutralized. Every plausible pathway is examined, attenuated, and shown to fall below detectability thresholds. Uncertainty is acknowledged, but always in ways that weaken the Hunga hypothesis more than its alternatives.

The length of the report is not incidental. A short paper declaring Hunga irrelevant would have invited skepticism. Only a document of this scale—dense with data, models, intercomparisons, and caveats—could plausibly declare the case closed without appearing dismissive. The volume itself functions rhetorically, conveying finality through exhaustion.

None of this requires accusing the authors of misconduct. The report is careful, internally consistent, and often admirably cautious. But caution is not evenly distributed. Skepticism is applied asymmetrically. One explanation is forced to clear a high evidentiary bar; others pass unchallenged.

In that sense, the document reads less like an open scientific inquiry and more like a legal brief. Evidence is marshaled, counterarguments anticipated, uncertainties catalogued, and a verdict delivered early, then defended at length. The goal is not discovery, but closure.

The Hunga Tonga eruption presented an opportunity to examine the limits of short-term climate attribution and to confront how much natural variability remains unresolved. Instead, it became a case study in how institutions respond when nature threatens to intrude on a preferred narrative. The report succeeds on its own terms. Whether those terms serve science—or merely its administrative needs—is the question it never seriously asks.

IPCC Guilty of “Prosecutor’s Fallacy”

“Given the observed temperature increase, and the output from their computer simulations of the climate system, the IPCC rejected the idea that less than half the warming was man-made. They said there was less than a 5% chance that this was true.”

From Science Matters

By Ron Clutz

IPCC made an illogical argument in a previous report as explained in a new GWPF paper The Prosecutor’s Fallacy and the IPCC Report.  Excerpts in italics with my bolds and added images.

London, 13 September – A new paper from the Global Warming Policy Foundation reveals that the IPCC’s 2013 report contained a remarkable logical fallacy.

The author, Professor Norman Fenton, shows that the authors of the Summary for Policymakers claimed, with 95% certainty, that more than half of the warming observed since 1950 had been caused by man. But as Professor Fenton explains, their logic in reaching this conclusion was fatally flawed.

“Given the observed temperature increase, and the output from their computer simulations of the climate system, the IPCC rejected the idea that less than half the warming was man-made. They said there was less than a 5% chance that this was true.”

“But they then turned this around and concluded that there was a 95% chance
that more than half of observed warming was man-made.”

This is an example of what is known as the Prosecutor’s Fallacy, in which the probability of a hypothesis given certain evidence, is mistakenly taken to be the same as the probability of the evidence given the hypothesis.

As Professor Fenton explains

“If an animal is a cat, there is a very high probability that it has four legs.
However, if an animal has four legs, we cannot conclude that it is a cat.
It’s a classic error, and is precisely what the IPCC has done.”

Professor Fenton’s paper is entitled The Prosecutor’s Fallacy and the IPCC Report.

What the number does and does not mean

Recall that the particular ‘climate change number’ that I was asked to explain was the number 95: specifically, relating to the assertion made in the IPCC 2013 Report of ‘at least 95% degree of certainty that more than half the recent warming is man-made’.  The ‘recent warming’ related to the period 1950–2010. So, the assertion is about the probability of humans causing most of this warming.

Before explaining the problem with this assertion, we need to make clear that (although superficially similar) it is very different to another more widely known assertion (still promoted by NASA) that ‘97% of climate scientists agree that humans are causing global warming and climate change’. That assertion was simply based on a flawed survey of authors of published papers and has been thoroughly debunked.

The 95% degree of certainty is a more serious claim.
But the  case made for it in the IPCC report is also flawed.

[Commment: In the short video above, Norman Fenton explains the fallacy IPCC committed.  Synopsis of example.  A man dies is a very rowdy gathering of young men.  A size 13 footprint is found on the body.  Fred is picked up by the police.  He admits to being there but not to killing anyone, despite wearing size 13 shoes.  Since statistics show that only 1% of young men have size 13 feet, the prosecutor claims a 99% chance Fred is guilty.  The crowd was reported to be on the order of 1000, so  there were likely 10 others with size 13 shoes.  So in fact there is only a 10% chance Fred is guilty.]

The flaw in the IPCC summary report

It turns out that the assertion that ‘at least 95% degree of certainty that more than half the recent warming is man-made’ is  based on the same fallacy. In my article about the programme, I highlighted this concern as follows:

The real probabilistic meaning of the 95% figure. In fact it comes from a classical hypothesis test in which observed data is used to test the credibility of the ‘null hypothesis’. The null hypothesis is the ‘opposite’ statement to the one believed to be true, i.e. ‘Less than half the warming in the last 60 years is man-made’. If, as in this case, there is only a 5% probability of observing the data if the null hypothesis is true, the statisticians equate this figure (called a p-value) to a 95% confidence that we can reject the null hypothesis.

But the probability here is a statement about the data given the hypothesis. It is not generally the same as the probability of the hypothesis given the data (in fact equating the two is often referred to as the ‘prosecutors fallacy’, since it is an error often made by lawyers when interpreting statistical evidence).

IPCC defined ‘extremely likely’ as at least 95% probability.  The basis for the claim is found in Chapter 10 of the detailed Technical Summary, which describes various climate change simulation models, which reject the null hypothesis (that more than half the warming was not man-made) at the 5% significance level. Specifically, in the simulation models, if you assumed that there was little man-made impact, then there was less than 5% chance of observing the warming that has been measured. In other words, the models do not support the null hypothesis of little man-made climate change. The problem is that, even if the models were accurate (and it is unlikely that they are) we cannot conclude that there is at least a 95% chance that more than half the warming was man-made, because doing so is the fallacy of the transposed conditional.

The illusion of confidence in the coin example comes from ignoring (the ‘prior probability’) of how rare the double-headed coins are. Similarly, in the case of climate change there is no allowance made for the prior probability of man-made climate change, i.e. how likely it is that humans rather than other factors such as solar activity cause most of the warming. After all, previous periods of warming certainly could not have been caused by increased greenhouse gases from humans, so it seems reasonable to assume – before we have considered any of the evidence – that the probability humans caused most of the recent increase in temperature to be very low. 

Only the assumptions of the simulation models are allowed,
and other explanations are absent.

In both of these circumstances, classical statistics can then be used to deceive you into presenting an illusion of confidence when it is not justified.

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