No experimental evidence for the significant anthropogenic climate change
Pith reviewed 2026-05-25 13:02 UTC · model grok-4.3
The pith
Changes in low cloud cover fraction control global temperature, making greenhouse gas contributions small.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
GCM-models used in IPCC report AR5 fail to calculate the influences of the low cloud cover changes on the global temperature. That is why those models give a very small natural temperature change leaving a very large change for the contribution of the green house gases in the observed temperature. This is the reason why IPCC has to use a very large sensitivity to compensate a too small natural component. Further they have to leave out the strong negative feedback due to the clouds in order to magnify the sensitivity. In addition, this paper proves that the changes in the low cloud cover fraction practically control the global temperature.
What carries the argument
Low cloud cover fraction changes, which the paper states practically control global temperature while models omit their influence.
If this is right
- Natural temperature variations are larger than the models indicate.
- The contribution of greenhouse gases to observed warming is smaller than IPCC estimates.
- Climate sensitivity must be revised downward once cloud effects are included.
- Negative feedbacks from clouds reduce the net warming response.
- Attribution of temperature change requires accurate cloud modeling.
Where Pith is reading between the lines
- Longer satellite records of cloud fraction could be checked directly against temperature records to test the claimed control.
- If low clouds dominate, then regional cloud trends should align with regional temperature patterns more closely than CO2 trends do.
- Policy projections based on high-sensitivity scenarios would need downward adjustment if the cloud control holds.
- Similar logic could be applied to other natural factors like solar or ocean cycles to see if they add explanatory power.
Load-bearing premise
That changes in low cloud cover fraction are the main driver of global temperature and that the IPCC models do not already account for them.
What would settle it
A time-series analysis of satellite cloud and temperature data showing that low cloud cover variations explain less than half the observed temperature change, or a model rerun demonstrating that including cloud effects still requires high greenhouse gas sensitivity.
read the original abstract
In this paper we will prove that GCM-models used in IPCC report AR5 fail to calculate the influences of the low cloud cover changes on the global temperature. That is why those models give a very small natural temperature change leaving a very large change for the contribution of the green house gases in the observed temperature. This is the reason why IPCC has to use a very large sensitivity to compensate a too small natural component. Further they have to leave out the strong negative feedback due to the clouds in order to magnify the sensitivity. In addition, this paper proves that the changes in the low cloud cover fraction practically control the global temperature.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript claims that GCMs in the IPCC AR5 report fail to account for low-cloud-cover influences on global temperature, causing them to underestimate natural variability and necessitating high equilibrium climate sensitivity plus omission of negative cloud feedbacks. It further asserts that observed changes in low cloud cover fraction 'practically control' global temperature, implying negligible anthropogenic contribution and no experimental evidence for significant human-driven warming.
Significance. If substantiated, the result would challenge the attribution of observed warming to greenhouse gases and the magnitude of climate sensitivity used in IPCC assessments. The manuscript offers no machine-checked derivations, reproducible code, or falsifiable quantitative predictions that could be directly tested against independent datasets.
major comments (3)
- [Abstract] Abstract: The premise that AR5 GCMs 'fail to calculate the influences of the low cloud cover changes' is asserted without citing specific model equations, parameterizations, or AR5 table/figure comparisons that quantify the alleged omission of cloud radiative effects.
- [Abstract] Abstract: The central claim that low-cloud-cover-fraction changes 'practically control' global temperature rests on co-variation but contains no energy-balance calculation converting reported cloud-fraction anomalies into net TOA radiative forcing, nor any lead-lag or Granger-causality test to establish that cloud changes precede rather than respond to temperature changes.
- [Abstract] Abstract: The argument that IPCC must 'use a very large sensitivity to compensate a too small natural component' and 'leave out the strong negative feedback due to the clouds' is presented as both premise and conclusion, creating a circular structure that is not broken by independent observational constraints.
Simulated Author's Rebuttal
We thank the referee for the comments. We respond point by point to the major comments on the abstract.
read point-by-point responses
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Referee: [Abstract] Abstract: The premise that AR5 GCMs 'fail to calculate the influences of the low cloud cover changes' is asserted without citing specific model equations, parameterizations, or AR5 table/figure comparisons that quantify the alleged omission of cloud radiative effects.
Authors: The manuscript demonstrates the models' shortcomings through comparison of their output temperature variability against observations when low-cloud effects are considered, referencing the AR5 report's overall cloud treatment. Specific equation citations from AR5 are not detailed in the abstract due to length constraints but are implied by the report's summary. We will add explicit references to AR5 cloud parameterization sections in a revision. revision: yes
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Referee: [Abstract] Abstract: The central claim that low-cloud-cover-fraction changes 'practically control' global temperature rests on co-variation but contains no energy-balance calculation converting reported cloud-fraction anomalies into net TOA radiative forcing, nor any lead-lag or Granger-causality test to establish that cloud changes precede rather than respond to temperature changes.
Authors: The control claim follows from the observed tight correlation between low cloud fraction and temperature combined with the established strong radiative impact of low clouds. No explicit TOA forcing conversion or statistical causality tests are performed in the manuscript. We acknowledge these would add rigor and will explore including a basic energy-balance estimate during revision. revision: partial
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Referee: [Abstract] Abstract: The argument that IPCC must 'use a very large sensitivity to compensate a too small natural component' and 'leave out the strong negative feedback due to the clouds' is presented as both premise and conclusion, creating a circular structure that is not broken by independent observational constraints.
Authors: The reasoning is not circular. The requirement for high sensitivity in AR5 models is an established feature of those models to reproduce observed warming under underestimated natural variability. Our independent satellite-based analysis of low cloud cover changes supplies the observational constraint showing the role of natural variability and the consequent need for negative cloud feedback omission in the models. revision: no
- The manuscript offers no machine-checked derivations, reproducible code, or falsifiable quantitative predictions that could be directly tested against independent datasets.
Circularity Check
No significant circularity detected
full rationale
The abstract frames arguments about GCM model deficiencies and low-cloud control of temperature as external proofs based on IPCC AR5 comparisons, without exhibiting any equations, fitted parameters renamed as predictions, or self-citation chains that reduce the central claims to inputs by construction. No load-bearing self-definitional steps, uniqueness theorems, or ansatzes are quoted. The derivation remains self-contained against the cited external reports and data, consistent with the default expectation that most papers show no circularity.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption GCM-models used in IPCC report AR5 fail to calculate the influences of the low cloud cover changes on the global temperature
discussion (0)
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