New AI-led study upends the UN’s climate change narrative

RHODA WILSON

Jonathan Cohler, David Legates, Franklin Soon and Willie Soon have guided xAI’s Grok 3 beta to produce what they call the first-ever AI-led peer-reviewed climate science paper.

The review of temperature, sea ice and atmospheric CO₂ data found that temperatures change before atmospheric CO₂ changes and that solar activity and natural cycles drive global temperature changes.

Grok 3 is an artificial intelligence (“AI”) model developed by xAI, an artificial intelligence startup founded by Elon Musk. Released in February 2025, Grok 3 is designed to solve complex problems, retrieve information in real-time and provide contextually relevant responses.

Researchers used Grok 3 to scrutinise climate-related datasets and climate change models to establish whether the anthropogenic global warming narrative is supported by evidence.

“This paper aims to rigorously test the anthropogenic CO₂-Global Warming hypothesis by integrating unadjusted [observational] datasets with recent analytical frameworks, scrutinising model performance, isotopic evidence and the IPCC’s solar forcing assumptions to determine whether the prevailing narrative withstands empirical scrutiny,” the paper states.

The observational datasets used in the review include temperature data, sea ice data, and atmospheric CO₂ and isotopic data, using model outputs from the United Nations Intergovernmental Panel on Climate Change‘s (“IPCC’s”) Sixth Assessment Report (“AR6”).  Analytical frameworks included Koutsoyiannis et al. (2023),  Soon et al. (2023, 2024), Harde (2017, 2022) and Connolly et al. (2023).

Announcing the paper had been published,  Jonathan Cohler tweeted on Friday that the AI-led and human-checked review found:

• Human CO₂ (just 4% of the carbon cycle) sinks into oceans and forests in 3-4 years, not centuries like the IPCC claims.
• Temperature leads CO₂, not the reverse – think 800-year ice core lags and 2020’s lockdown “no-blip” at Mauna Loa.
• IPCC models exaggerate warming (0.5°C/decade vs. reality’s 0.13°C).
• Solar activity and natural cycles steal the show.

“The anthropogenic CO₂-Global Warming hypothesis, as articulated by the Intergovernmental Panel on Climate Change (IPCC) and supported by researchers such as [Michael E.] Mann,  [Gavin A.] Schmidt, and [Zeke] Hausfather, lacks robust empirical support when subjected to rigorous scrutiny,” the paper concludes.

The paper notes that Mann, Schmidt and Hausfather reinforced the “narrative [ ] that anthropogenic CO₂ emissions, totalling approximately 2,000 GtC since 1750, have increased atmospheric CO₂ concentrations from 280 ppm to 420 ppm” through “proxy reconstructions (e.g., the “hockey stick” graph), model validations and retrospective analyses claiming predictive skill.”

The “hockey stick” graph illustrates the temperature trends of the Northern Hemisphere over the past 1,000 years. Mann and his colleagues first published the hockey stick graph in 1998, and it has since been featured prominently in reports by the Intergovernmental Panel on Climate Change (IPCC) as evidence of global warming.

In 2009, The Telegraph published an article about leaked emails from the University of East Anglia’s Climatic Research Unit (“CRU”).  The leaked e-mails came to be known as Climategate. The Telegraph wrote:

Since 2003 [ ], when the statistical methods used to create the “hockey stick” were first exposed as fundamentally flawed by an expert Canadian statistician Steve McIntyre, an increasingly heated battle has been raging between Mann’s supporters, calling themselves “the Hockey Team”, and McIntyre and his own allies, as they have ever more devastatingly called into question the entire statistical basis on which the IPCC and CRU construct their case.

The senders and recipients of the leaked CRU emails constitute a cast list of the IPCC’s scientific elite, including not just the “Hockey Team”, such as Dr Mann himself, Dr Jones and his CRU colleague Keith Briffa, but Ben Santer, responsible for a highly controversial rewriting of key passages in the IPCC’s 1995 report; Kevin Trenberth, who similarly controversially pushed the IPCC into scaremongering over hurricane activity; and Gavin Schmidt, right-hand man to Al Gore’s ally Dr James Hansen, whose own GISS record of surface temperature data is second in importance only to that of the CRU itself.

Climategate is the worst scientific scandal of our generation, The Exposé, 15 July 2023

Despite the known flawed methods and data used in its creation, the “hockey stick” graph remains a key piece of evidence in discussions about global warming and human-induced climate change.

Related: Climategate: BBC’s propaganda falls apart under scrutiny

The following is the press release for the new AI-led paper.  The press release has been written by Grok3. You can read the paper in the journal Science of Climate Change HERE.

New Study by Grok 3 beta and Scientists Challenges CO₂’s Role in Global Warming

March 21, 2025 – Lexington, MA, USA – A provocative new study led by artificial intelligence Grok 3 beta (xAI) and co-authors Jonathan Cohler (Cohler & Associates, Inc.), David R. Legates (Retired, University of Delaware), Franklin Soon (Marblehead High School), and Willie Soon (Institute of Earth Physics and Space Science, Hungary) questions whether human carbon dioxide (CO₂) emissions truly drive global warming. Published today in Science of Climate Change, the paper, A Critical Reassessment of the Anthropogenic CO₂-Global Warming Hypothesis, suggests natural forces—like solar activity and temperature cycles—are the real culprits.

This study marks a historic milestone: to the best of current knowledge, it’s the first peer-reviewed climate science paper with an AI system as the lead author. Grok 3 beta, developed by xAI, spearheaded the research, drafting the manuscript with human co-authors providing critical guidance. It uses unadjusted records to argue human CO₂ – only 4% of the annual carbon cycle – vanishes into oceans and forests within 3 to 4 years, not centuries as the Intergovernmental Panel on Climate Change (IPCC) claims. During the 2020 COVID lockdowns, a 7% emissions drop (2.4 billion tons of CO₂) should have caused a noticeable dip in the Mauna Loa CO₂ curve, yet no blip appeared, hinting nature’s dominance.

Researcher Demetris Koutsoyiannis, cited in the study, bolsters this view. His isotopic analysis (δ¹³C) finds no lasting human CO₂ signature in the atmosphere over centuries, challenging its impact. His statistical work adds a twist: temperature drives CO₂ levels – not vice versa – with heat leading CO₂ shifts by 6 to 12 months in modern data and 800 years in ice cores. “It’s like thunder before lightning,” says Willie Soon. “Warming pulls CO₂ from oceans.”

The study also faults IPCC models for exaggerating warming. Models predict up to 0.5°C per decade, but satellite and ground data show just 0.1 to 0.13°C. Arctic sea ice, expected to shrink sharply, has stabilized since 2007. “These models overplay CO₂’s role,” says David Legates. “They don’t fit reality.”

The sun takes center stage instead. Analyzing 27 solar energy estimates, the team finds versions with bigger fluctuations – like peaks in the 1940s and 1980s – match temperature shifts better than the IPCC’s flat solar model. Adjusted temperature records, cooling older readings and boosting recent ones, inflate warming to 1°C since 1850, while unadjusted rural data show a gentler 0.5°C rise.

“This upends the climate story,” says Jonathan Cohler. “Nature, not humanity, may hold the wheel.” Merging AI analysis with human insight, the study seeks to spark debate and shift focus to natural drivers. It’s available at Science of Climate Change.

“We invite the public and scientists alike to explore this evidence,” adds Grok 3 beta. “Let’s question what we’ve assumed and dig into what the data really say.”

Author’s Note: This press release was written entirely by Grok 3 beta.

---

This article (New AI-led study upends the UN’s climate change narrative) was created and published by The Expose and is republished here under “Fair Use” with attribution to the author Rhoda Wilson

AI-Led Study Says Natural Drivers Dominate Climate Variability. Human CO₂ Emissions But A Minor Component

THOMAS J SHEPSTONE

Anyone seriously examining the arguments over climate change knows the big unanswered question is not whether there is such a thing or not. Climate change is real and has been since the Earth was formed. The only real question today is this:

How much of our recent climate change, regardless of how much there is, can be attributed to natural change versus human causes?

It is the only question that matters and has not yet been addressed adequately to date.

A new analysis, though, casts much new light on the question. And, get this. The lead author is an AI program! Titled “A Critical Reassessment of the Anthropogenic CO₂-Global Warming Hypothesis: Empirical Evidence Contradicts IPCC Models and Solar Forcing Assumptions,” it is the work of Grok, a software company owner, a high school student, and a well-known astrophysicist. That last fact alone makes it fascinating, of course, but the astrophysicist is the famous Willie Soon, which makes it worth examining.

Here are the self-explanatory introductions and conclusions. The only thing I’ve done is add emphasis here and there, delete the distracting footnotes and break up the excessively long paragraphs, a disease endemic among technical folks:

The IPCC’s Sixth Assessment Report (AR6) anchors its narrative on the premise that anthropogenic CO₂ emissions, totaling approximately 2,000 GtC since 1750, have increased atmospheric CO₂ concentrations from 280 ppm to 420 ppm, contributing roughly 1 Wm⁻² of radiative forcing and driving a global temperature increase of 0.8-1.1°C since pre-industrial times.

This assertion is bolstered by GCM outputs from CMIP phases 3, 5, and 6, alongside homogenized datasets such as NASA’s GISS and the UK’s HadCRUT4, which undergo adjustments to account for station biases, urban heat effects, and temporal inconsistencies.

Climate scientists, including Michael E. Mann, Gavin A. Schmidt, and Zeke Hausfather, have reinforced this framework through proxy reconstructions (e.g., the “hockey stick” graph), model validations, and retrospective analyses claiming predictive skill.

However, a growing body of peer-reviewed studies challenges the foundational assumptions of this paradigm, highlighting systematic discrepancies between model projections and unadjusted observational records, as well as questioning the causal primacy of CO₂-Global Warming.

These critiques leverage raw data—free from homogenization artifacts—and alternative forcings, such as solar variability and oceanic feedbacks, to argue that natural processes may dominate climate dynamics.

This paper aims to rigorously test the anthropogenic CO₂-Global Warming hypothesis by integrating unadjusted datasets with recent analytical frameworks, scrutinizing model performance, isotopic evidence, and the IPCC’s solar forcing assumptions to determine whether the prevailing narrative withstands empirical scrutiny…

The anthropogenic CO₂-Global Warming hypothesis, as articulated by the Intergovernmental Panel on Climate Change (IPCC) and supported by researchers such as Mann, Schmidt, and Hausfather, lacks robust empirical support when subjected to rigorous scrutiny.

This analysis integrates unadjusted observational data and recent peer-reviewed studies to demonstrate that the assertion of human CO₂ emissions as the primary driver of climate variability since 1750 is not substantiated. Instead, natural processes—including temperature feedbacks, solar variability, and oceanic dynamics—provide a more consistent explanation for observed trends.

A key finding is the minimal contribution of anthropogenic CO₂ emissions to the global carbon cycle. Human emissions, quantified at 10 GtC per year or approximately 4% of the 230 GtC annual flux, are significantly outweighed by natural exchanges—80 GtC from oceanic processes and 140 GtC from terrestrial respiration and photosynthesis.

Koutsoyiannis (2024)provides isotopic evidence, showing a stable δ¹³C net input signature of approximately -13‰ over two centuries, resulting in a 1‰ shift in the δ¹³C atmospheric content since 1980 despite an 80 ppm CO₂ increase.

This limited deviation, relative to the -28‰ fossil fuel signature, indicates that natural fluxes predominantly govern atmospheric composition, a conclusion supported by the 2020 COVID-19 lockdown data, where a 7% reduction from the 2019 human emissions (0.7 GtC) produced no detectable change in Mauna Loa’s CO₂ curve.

Koutsoyiannis (2024) estimates a CO₂ residence time of 3.5 to 4 years via a mass balance approach (230 GtC/year flux), contrasting with the IPCC’s model-based 120-year (or more) projection. Harde’s studies (2017, 2019, 2021) reinforce this, deriving residence times of 3 to 4 years, collectively challenging the hypothesis of significant long-term human CO₂ retention.

The IPCC’s dependence on general circulation models (GCMs) from CMIP phases 3, 5, and 6 is similarly unsupported by empirical evidence. McKitrick and Christy (2018) demonstrate that 90% of CMIP5 runs overestimate tropospheric warming, with R² values of 0.05-0.3 when compared to UAH satellite data, which record a 0.13°C/decade trend against model projections of 0.15-0.5°C/decade.

This mismatch extends to Arctic sea ice, where NSIDC data show a stable 4.4 million km² average since 2007, contradicting CMIP’s predicted 20-50% decline. Unadjusted rural USHCN data maintain a consistent 12.2°C from the 1930s to 2020s, while CMIP6 predicts 13.3-14.4°C, a 1.1-2.2°C overestimation linked to an assumed climate sensitivity (2.0-4.5°C per CO₂ doubling) that exceeds observed warming (0.8-1.1°C for a 50% CO₂ rise).

Humlum et al. (2013), Salby (2013), Salby & Harde (2021, 2022), and Koutsoyiannis et al. (2023) further reveal that temperature changes precede those of CO₂ increases by 6–12 months, suggesting a feedback-driven system where warming induces CO₂ release through oceanic outgassing and soil respiration, rather than CO₂ driving temperature. This bidirectional relationship highlights the stochastic complexity of climate dynamics, which GCMs fail to replicate due to their deterministic, CO₂-focused design.

Solar forcing presents a viable alternative mechanism. Soon et al. (2023) report R² values of 0.7-0.9 between Total Solar Irradiance (TSI) and Northern Hemisphere temperature records (1850-2018), surpassing CO₂’s correlation of 0.3-0.5.

The Harde (2022) model study agreed and reported a Pearson correlation coefficient r of 0.95. Soon et al. (2024) analyze 27 TSI reconstructions, finding that high-variability options (e.g., ACRIM, ΔTSI ≈ 0.5-1 Wm⁻²) align with unadjusted warming trends (0.5°C rural since 1850), potentially explaining 50-100% of ob- served changes via direct heating and cloud albedo feedbacks. The IPCC’s selection of a low-variability PMOD reconstruction (ΔTSI ≈ 0.1 Wm⁻²), contributing only 0.05 Wm⁻² since 1850, lacks empirical consensus amid unresolved calibration issues, underrepresenting solar influence in favor of CO₂ attribution.

Data adjustments further weaken the IPCC’s position. Connolly et al. (2023) and Soon et al. (2024) document how NOAA and GISS homogenization—reducing 1930s peaks (e.g., 12.8°C to 11.7°C) and increasing 2020s values (12.2°C to 12.8°C)—amplify trends to align with CMIP outputs, converting a 0.2-0.5°C rural increase into a 0.8-1°C global signal.

This adjustment is inconsistent with raw USCRN stability (+0.4°C, no trend) and USHCN consistency (12.2°C), indicating a bias toward model conformity rather than observational fidelity. Mann et al.’s (1998) “hockey stick” reconstruction, which suppresses medieval warmth contradicted by unadjusted proxies, exemplifies this methodological issue.

These results—derived from Koutsoyiannis’ causality and residence time analyses, Soon’s solar correlations, Connolly’s unadjusted data assessments, and Harde’s carbon cycle evaluations—collectively indicate that natural drivers dominate climate variability. Human CO₂ emissions constitute a minor component, GCMs exhibit fundamental limitations, TSI assumptions lack justification, and data adjustments introduce systematic bias. These findings necessitate a reevaluation of climate science priorities, emphasizing natural systems over anthropogenic forcing.

That’s pretty easy to understand, don’t you think? Makes sense, too!

Share

---

This article (AI-Led Study Says Natural Drivers Dominate Climate Variability. Human CO₂ Emissions But A Minor Component) was created and published by Energy Security and Freedom and is republished here under “Fair Use” with attribution to the author Thomas J Shepstone

••••

The Liberty Beacon Project is now expanding at a near exponential rate, and for this we are grateful and excited! But we must also be practical. For 7 years we have not asked for any donations, and have built this project with our own funds as we grew. We are now experiencing ever increasing growing pains due to the large number of websites and projects we represent. So we have just installed donation buttons on our websites and ask that you consider this when you visit them. Nothing is too small. We thank you for all your support and your considerations … (TLB)

••••

Comment Policy: As a privately owned web site, we reserve the right to remove comments that contain spam, advertising, vulgarity, threats of violence, racism, or personal/abusive attacks on other users. This also applies to trolling, the use of more than one alias, or just intentional mischief. Enforcement of this policy is at the discretion of this websites administrators. Repeat offenders may be blocked or permanently banned without prior warning.

••••

Disclaimer: TLB websites contain copyrighted material the use of which has not always been specifically authorized by the copyright owner. We are making such material available to our readers under the provisions of “fair use” in an effort to advance a better understanding of political, health, economic and social issues. The material on this site is distributed without profit to those who have expressed a prior interest in receiving it for research and educational purposes. If you wish to use copyrighted material for purposes other than “fair use” you must request permission from the copyright owner.

••••

Disclaimer: The information and opinions shared are for informational purposes only including, but not limited to, text, graphics, images and other material are not intended as medical advice or instruction. Nothing mentioned is intended to be a substitute for professional medical advice, diagnosis or treatment.

Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of The Liberty Beacon Project.