Reporting the fraudulent practices behind global warming science

by Christopher Monckton of Brenchley
June 3, 2019

The prison gate is about to slam thunderously shut on the global warming fraudsters. It is time to report their profitable but murderous deception to the public investigating and prosecuting authorities.

To prove a fraud, though, is harder than to prove a murder. One has to demonstrate – beyond reasonable doubt – not one but two criminal intents.

The first is the intent to deceive by way of a false and dishonest representation. A representation is false if it is untrue or misleading and the person making it knows that it is, or may be, untrue or misleading. A representation is dishonest if what was done would be regarded as dishonest by the reasonable man on the Clapham omnibus, and if the perpetrator must have realized that the reasonable man would regard the deception as dishonest.

The second is the intent to cause a gain or loss in money or money’s worth by means of the deception – an intent either to gain by fraudulently getting what one does not have or by fraudulently keeping what one already has, or both, or an intent to cause a loss by depriving the victims of what they already possess, or by preventing them from gaining what they would otherwise have gotten, or both.

I recently visited a country house somewhere in Scotland to consult an eminent lawyer with close ties to the police. I described to him certain specific matters that appeared, prima facie, to be frauds. I told him exactly how the fraudulent claim of “97% consensus” had been fabricated. He got the point at once.

I went on to tell him how certain parties have wilfully and, as we see it, fraudulently thwarted our attempts to get one of the leading learned journals of climatology to publish our paper demonstrating that a single, elementary, catastrophic error of physics is the sole cause of the absurdly overblown predictions of warmer weather on the basis of which scientifically-illiterate governments have been panicked by downright evil lobby groups and profiteers of doom into causing untold death, disease, educational disadvantage, industrial destruction and financial ruin worldwide.

His eyes widened as the story unfolded. I said that, when we had submitted our paper to a journal, its editor had at first replied that he could not find anyone competent to review the paper. When we had persisted, the editor had spent six months garnering precisely two reviews. The first reviewer said he disagreed with the mathematics on a page that did not exist: whatever paper the reviewer was commenting upon, we were able to prove it was not the paper we had submitted to the journal.

The second reviewer had actually read the submitted paper, but he had commented that, because he had found the paper’s conclusion that global warming was not a problem uncongenial, he had not read the equations that justified the conclusion.

We pointed out that, since neither of the reviewers had actually reviewed our paper, the editor had received no indication that there was anything wrong with it, wherefore he should publish it without any further delay. He refused, saying that he would only publish the paper if the reviewers said it should be published. He added that he had telephoned a third party, who had told him not to publish the paper. We asked for that review in writing, so that we could comment on it and respond to any specific scientific points it made, but were refused.

The journal’s management then got in touch to invite us to submit further papers in future and to say they hoped we were happy with the review process. I wrote back to say that, unless we were given the opportunity to appeal against the editor’s decision, we proposed to report him as a participant in what Professor Mörner has justifiably described as “the biggest fraud in human history”.

Thereupon, the editor agreed to send out the paper for review again. For our part, we offered to expand the argument considerably, so as to forestall the usual attempts by politically and financially motivated academics to weasel out of allowing the paper to be published.

But when we submitted the much-extended paper, the editor did not reply. When we wrote a reminder email, again he did not reply.

We wrote to the IPCC, not once but twice, to activate the error-reporting protocol that the IPCC had been obliged to adopt after a series of acutely embarrassing errors, such as the laughable notion that all the ice in the Himalayas would melt by 2050. The IPCC, however, had failed even to acknowledge our report, let alone to activate the mandatory protocol that the Inter-Academy Council had obliged it to put in place.

The eminent lawyer’s eyebrows lifted. He pondered for a few moments, and then gave us the following advice:

First, he said, we should write to the Serious Fraud Office, with a copy to my local Chief Constable and a further copy to him, putting the authorities on notice that a fraud was suspected, providing the evidence of the “97% consensus” fraud (some of the perpetrators were in Britain) and providing the evidence of how we had been mistreated by the journal. At this stage, we should not request an investigation, but we should outline the widespread death, disease, damage and destruction caused by the suspected fraud.

Next, he advised us to submit our paper, in the normal way, to a second journal, this time within the jurisdiction of the British investigating authorities. We should keep meticulous records of the correspondence between us and the journal. If that second journal failed either to publish our paper or to provide a legitimate and robust scientific refutation of our argument, then we should copy that correspondence to the Serious Fraud Office and to the Chief Constable, again not requesting an investigation but merely putting them on notice that the fraud appeared to be continuing, and appeared to involve more than one journal.

Then, he said, assuming that no genuine fault had been found with our scientific argument, we should submit the paper to a third journal, again in the normal way, keeping a careful track of the correspondence. If the third journal did not handle the paper scientifically, we should write to the police again, this time to request investigation and prosecution of the connected frauds of the authors of the “97% consensus” claim, of the journal that had published that claim and had failed to publish a correction when requested, of the board of management of that journal, of the three journals that had refused to handle our paper scientifically, and of the IPCC secretariat that had fraudulently failed to activate its error-reporting protocol.

By that time, he said, the police would begin to be curious. They would check out certain easily-verifiable points, such as the fact that the list of almost 12,000 papers allegedly reviewed by the perpetrators of the “97% consensus” deception showed that the authors had themselves marked only 0.5% of the papers as explicitly stating their support for the “consensus” position as they had defined it. Once the police realized that we were telling the truth, they would begin to investigate, and he would support them in doing so.

So that is what we are going to do. And this is where you come in. There follows a condensed version (warning: it’s not for wimps) of our scientific argument to the effect that climatologists had forgotten, at a vital point in their “how-much-warming” calculations, to take due account of the fact that the Sun is shining. Is our argument sound? Is it definitive? Or is it erroneous or in some respects deficient? And should we follow the eminent lawyer’s advice? I shall read your comments with interest.

An error in defining temperature feedback explains overstatements of global warming

Abstract: Climatology borrows feedback method from control theory^1-6, but errs by defining feedback as responsive only to perturbations of the input signal, emission temperature. If so, impossibly, the feedback fraction due to warming from noncondensing greenhouse gases would exceed that due to emission temperature by 1-2 orders of magnitude. Then feedback response would be up to 90% of Charney sensitivity (equilibrium sensitivity to doubled CO2 after feedback has acted)⁷ and of the uncertainty therein⁸. In reality, feedback also responds to the entire reference signal^9,10. In climate, that signal (the signal before feedback acts) is reference temperature, the sum of all natural as well as anthropogenic perturbations and, above all, of emission temperature. It is here demonstrated that the system-gain factor, the ratio not only (as now) of equilibrium to reference sensitivities but also of entire temperatures, is insensitive even to large uncertainties therein: in 1850 and 2011 it was 1.1. Though models⁷ project 3.35 [2.1, 4.7] K Charney sensitivity, the revised value – the product of the system-gain factor 1.1 and the 1.05 K reference sensitivity⁷ to doubled CO₂ – falls on 1.15 [1.10, 1.25] K, confirming evidence¹¹ that feedback barely alters temperature and that, even without mitigation, net-harmful warming is unlikely. Mitigation entails a heavy net global welfare loss disproportionately afflicting 1.3 billion people to whom access to electricity is denied.

Projected midrange global warming outstrips observation threefold (Fig. 1) due to an erroneous definition of temperature feedback in climatology. All transport across the climate-system boundary is radiative; and, in the Stefan-Boltzmann equation, flux density at an emitting surface is a function of absolute temperature, which is accordingly the proper metric for sensitivity studies. Yet climatology defines feedback response as the difference not between entire reference and equilibrium temperatures (respectively before and after feedback has acted) but between sensitivities, concluding that feedback response comprises up to 90%⁷ of equilibrium sensitivity, and of the uncertainty that arises therein⁸ chiefly because feedbacks are unquantifiable by measurement and act at resolutions below models’ (GCMs’) grid-scale. Reference sensitivity⁷ to doubled CO₂ is only ^{1, p. 676, cf. 12}: but in GCMs the large imagined feedback response and its large attendant uncertainty elevates Charney sensitivity (equilibrium sensitivity to doubled CO₂) to 3.35 [2.1, 4.7] K ⁷. IPCC, whose [1.5, 4.5] K interval^1,13 is as in 1979¹⁴, mentions “feedback” more than 1000 times¹.

Figure 1. | Projections^1,7 of global warming from 1850-2011 (inner scale), in response to doubled CO₂ (middle scale) and the sum of these two (outer scale) greatly exceeds warming consistent with the 0.75 K observed from 1850-2011 (green needle). Midrange Charney sensitivity⁷ 3.35 K (red needle) implies 2.4 K equilibrium warming by 2011, thrice observation. The revised interval derived herein is consistent with observation.

Control theory, developed for telephone circuits^9,10 but applicable to all feedback-moderated dynamical systems, defines feedback as responsive to the entire reference signal as well as to perturbations. However, climatology^1-6 considers only perturbations^{e.g. 1, p. 1450}:

Climate feedback: An interaction in which a perturbation in one climate quantity causes a change in a second, and the change in the second quantity ultimately leads to an additional change in the first. A negative feedback is one in which the initial perturbation is weakened by the changes it causes; a positive feedback is one in which the initial perturbation is enhanced … the climate quantity that is perturbed is the global mean surface temperature, which in turn causes changes in the global radiation budget. In either case, the initial perturbation can either be externally forced or arise as part of internal variability. [Authors’ emphases]

Due to this definitional error, projected Charney sensitivity has hitherto been imagined to exceed reference sensitivity up to tenfold^{7-8, 15-20}. A corrected definition follows (with climate-related terms in parentheses):

Feedback (in of surface equilibrium temperature ) induces a feedback response (, in Kelvin at time ) to the entire reference signal (reference temperature ), the sum of the input signal (emission temperature ) and all perturbations (natural and anthropogenic reference sensitivities ). The feedback loop (Fig. 2) modifies the output signal () by returning some fraction of it, the feedback fraction (), to the input/output node. The ratio of output to input signals is the system-gain factor (. Negative feedback attenuates output; positive feedback amplifies it.

Figure 2. | The feedback loop (a) simplifies to the system-gain schematic (b)

Given that and , , the sum of the infinite convergent geometric series under the convergence criterion . Visibly (Fig. 2), the feedback block modifies all of , not merely .

Sensitivities and absolute temperatures: Climatology obtains equilibrium sensitivities using (1), derived from the energy-balance equation via a Taylor-series expansion^4,21. In (1), is climatology’s system-gain factor, a forcing; a near-invariant sensitivity parameter^{22, p.354; 23, 24}. In (2), the corrected definition of feedback is used.

	.	(1)
		(2)

Though (1, 2) are both valid, (1) cannot constrain , because small uncertainties in , yield large uncertainty in ; but in (2), where , exceed , by two orders of magnitude, even large uncertainties in , entail small uncertainty in . The use of (2) remedies climatology’s restrictive definition, obviates quantification of individual feedbacks and diagnoses of equilibrium sensitivities using GCMs and, above all, facilitates reliable constraint of equilibrium sensitivities.

System gain: ; due to pre-industrial GHGs⁶ in 1850 was . In 1850, ; ²⁵. The Planck parameter . Net anthropogenic forcing^{1, fig. SPM.5} to 2011, so that .

In 2011, . Given radiative imbalance²⁶ by 2010, from 1850-2011 (of which was observed²⁵). Since , , as in 1850. Thus, proves stable over time: for instance, the uncertainty²⁵ in barely perturbs , so that, where the curve of the response function is linear .

That curve passes through two points . Since , the first point is . The second is the well-constrained in 1850. If is an exponential-growth curve, the exponent . For ⁷, . Then , and , near-identical to the linear case.

If were derived not from but from and current estimates of , temperature in 1850 would exceed observation and would barely exceed . For the midrange ⁷, GCMs’ system-gain factor implies that ; but then , so that in 1850 would have been , exceeding observation by , and, in any event, , close to the linear case.

If per impossibile the response curve bypassed , it must still visit in 1850. If the second point were (, current ), the ratio of the feedback fractions due to and due to becomes impossibly excessive: e.g., ; ; (Fig. 3). Yet the same feedbacks respond to sensitivities as to emission temperature, so that in (1) is near-invariant, implying .

Figure 3. | Ratio of the feedback fractions due to and due to , for on . Beyond the plausible regions, elevated feedback-fraction ratios and equilibrium sensitivities are impossible.

For a non-exponential-growth curve of that was near-linear, would barely exceed . For a significantly nonlinear or even stochastic non-exponential-growth curve, variability in the successive feedback fractions would at some point exceed that in an exponential-growth curve, contrary a fortiori to the near-invariance of . Therefore, regardless of the shape of , Charney sensitivities cannot much exceed .

Predicted and observed feedback have diverged (Fig. 4). Feedbacks other than water vapour self-cancel^{1, table 9.5}. By Clausius-Clapeyron, the atmosphere may carry 7% K^–1 more water vapour²⁷, but specific humidity is thus rising²⁸ only in the lower troposphere, where water vapour’s spectral lines are near-saturated: as humidity increases, only the far wings add to infrared absorption²⁹, which varies logarithmically +with humidity. Though GCMs predict 90% of water vapour feedback in the tropical mid-troposphere, specific humidity is falling there, so that predicted warming³⁰ at twice the surface rate is not seen^11,31. Thus, feedback response varies near-linearly with temperature, so that the water-vapour feedback is small.

Figure 4. | The tropical mid-troposphere hot spot (a) is not observed (b).

Monte Carlo processes (Fig. 5) compared the revised 2 σ Charney-sensitivity interval 1.16 [1.09, 1.23] K with the current 3.35 [2.1, 4.7] K (inset); and, in an empirical campaign, authoritative estimates of anthropogenic forcing over ten periods all yielded 1.15 K.

Figure 5. | (a) Monte Carlo distribution of Charney sensitivities revised after defining feedback correctly (bin widths 0.005 K); (b) Scaled comparison of distributions of revised vs. current Charney sensitivities (bin widths 0.025 K).

No consensus: Only 0.3% of 11,944 climate papers from 1991-2011 found of post 1950-warming anthropogenic³². If some warming were natural, equilibrium sensitivities might be less than found here.

Discussion: The Stern climate-economics review³³ took a mid-range estimate of warming by 2100 as driving a welfare loss of – of global GDP (cf. –)¹. The 11 K upper bound³³ drove a 20%-of-GDP extinction-level loss assuming a pure rate-of-time discount rate, giving “roughly a chance of the planet not seeing out this century”³⁴. Adding per-capita consumption growth without climate change gave a mean social discount rate (cf. ³⁵), against a ^36-37 minimum market discount rate. Since the present result shows the probability of extinction is nil, submarket rates are unjustifiable. Even without allowing for the present result, at the mean discount rate a -of-GDP welfare loss³³ would become (or assuming no net welfare loss until preindustrial temperature is exceeded by ), while a -of-GDP loss³³ would become only ().

Conclusion: The World Bank cites global warming in refusing to fund coal, oil and gas projects in developing countries, where denying electricity to 1.3 billion people curtails IQ and shortens lifespans by ~20 years. Once temperature feedback is correctly defined, anthropogenic warming will be small, slow and net-beneficial. A policy rethink is advisable.

---

References

1. IPCC. Climate change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stocker, T.F., et al. (eds.), Cambridge University Press, Cambridge (2013).

2. Hansen, J. et al. Climate sensitivity: Analysis of feedback mechanisms. In: Climate Processes and Climate Sensitivity, AGU Geophysical Monograph 29, Maurice Ewing Vol. 5. Hansen J, Takahashi T (eds.). American Geophysical Union, 130–163 (1984).

3. Schlesinger, M.E. Feedback analysis of results from energy balance and radiative-convective models. In: The potential climatic effects of increasing carbon dioxide. MacCracken, M.C., Luther, F.M. (eds,). US Dept. of Energy, Washington DC, 280–319 (1985).

4. Roe, G. Feedbacks, timescales, and seeing red. Ann. Rev. Earth Planet. Sci. 37, 93–115 (2009).

5. Schmidt, G.A., Ruedy, R.A., Miller, R.L. & Lacis, A.A. Attribution of the present-day total greenhouse effect. J. Geophys. Res. (Atmos.) 115, D20106, https://doi.org/ 10.1029/2010JD014287 (2010).

6. Lacis, A.A., Schmidt, G.A., Rind, D., Ruedy, R.A. Atmospheric CO₂: principal control knob governing Earth’s temperature. Science 330, 356–359 (2010).

7. Andrews. T., Gregory, J.M., Webb, M.J. & Taylor, K.E. Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. Geophys. Res. Lett. 39, L09712, https://doi.org/10.1029/2012GL051607 (2012).

8. Vial, J., Dufresne, J.-L., Bony, S. On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Clim. Dyn. 41, 3339-3362, https://doi.org/10.1007/s00382-013-1725-9 (2013).

9. Black, H.S. Stabilized feedback amplifiers. Bell System Tech. J., New York (January 1934).

10. Bode, H.W. Network analysis and feedback amplifier design. Van Nostrand Reinhold, New York (1945).

11. Karl, T.R., Hassol, S.J., Miller, C.D., Murray, W.L. (Eds.). Temperature trends in the lower atmosphere: steps for understanding and reconciling differences. U.S. Climate Change Science Program Synthesis and Assessment Product 1.1, Washington DC, 164 pp, (2006).

12. Cess, R.D. et al. Uncertainties in carbon dioxide radiative forcing in atmospheric general-circulation models. Science 262 (5137), 1252-1255 (1993).

13. IPCC. Climate change – The IPCC Assessment (1990): Report prepared for the Intergovernmental Panel on Climate change by Working Group I. Houghton, J.T., Jenkins, G.J., Ephraums, J.J. (eds.). Cambridge University Press, Cambridge (1990).

14. Charney, J.G., et al. Carbon Dioxide and Climate: A Scientific Assessment. Report of an Ad-Hoc Study Group on Carbon Dioxide and Climate. Climate Research Board, Assembly of Mathematical and Physical Sciences, National Research Council, Woods Hole, Massachusetts (1979).

15. Armour, K.C. Energy budget constraints on climate sensitivity in light of inconstant climate feedbacks. Nat. Clim. Change 7, 331-335, https://doi.org/10.1038/ NCLIMATE3278 (2017).

16. Friedrich, T., Timmermann, A., Tigchelaar, M. & Ganopolski, A. Nonlinear climate sensitivity and its implications for future greenhouse warming. Sci. Adv. 2 (11), https://doi.org/10.1126/sciadv.1501923 (2016).

17. Johansson, D.J.A., O’Neill, N.C., Tebaldi, C., Häggström, O. Equilibrium climate sensitivity in light of observations over the warming hiatus. Nat. Clim. Change 5, 449-453 (2015)

18. Murphy, D.M. et al. An observationally based energy balance for the Earth since 1950. J. Geophys. Res. 114, D17107, https://doi.org/10.1029/2009D012105 (2009).

19. Forest, C.E., Stone, P.H. & Sokolov, A.P. Estimated PDFs of climate system properties including natural and anthropogenic forcings. Geophys. Res. Lett. 33, L01705 (2006).

20. Andronova, N.G. & Schlesinger, M.E. Objective estimation of the probability density function for climate sensitivity. J. Geophys. Res. (Atmos). 106, 22605-22611 (2001).

21. Bony, S. et al. How well do we understand and evaluate climate change feedback processes? J. Clim. 19, 3445–3482, https://doi.org/10.1175/JCLI3819.1 (2006).

22. IPCC. Climate Change 2001: The scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Houghton, J.T. et al. (eds.). Cambridge University Press, Cambridge (2001).

23. Ramanathan, V., Cicerone, R.J., Singh, H.B. Kiehl, J.T. Trace gas trends and their potential role in climate change. JGR (Atmospheres) 7:90(D3), https://doi.org/10.1029/JD090iD03p-5547 (1985)

24. WMO. Atmospheric ozone: 1985 global ozone research and monitoring project, ch. 15, Geneva (1986).

25. Morice, C.P., Kennedy, J.J., Rayner, N., Jones, P.D. Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset. J. Geophys. Res. 117, D08101 (2012), http://www.metoffice.gov.uk/ hadobs/hadcrut4/data/current/time_series/HadCRUT.4.5.0.0.monthly_ns_avg.txt, accessed 10 September 2018.

26. Smith, D.M. et al. Earth’s energy imbalance since 1960 in observations and CMIP5 models. Geophys. Res. Lett. 42 (4), https://doi.org/10.1002/2014GL062669 (2015).

27. Wentz, F.J., Ricciardulli, L., Hilburn, K. & Mears, C. How much more rain will global warming bring? Science 317, 233–235 (2007).

28. Kalnay E. et al. The NCEP/NCAR Reanalysis 40-year Project. Bull. Amer. Meteor. Soc. 77, 437-471 (1996).

29. Harde, H. Radiation transfer calculations and assessment of global warming by CO₂. Int. J. Atmos. Sci., https://doi.org/10.1155/2017/9251034 (2017).

30. IPCC. Climate Change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon S. et al. (eds.). Cambridge University Press, Cambridge (2007).

31. McKitrick, R., Christy, J. A test of the tropical 200- to 300-hPa warming rate in climate models. Earth & Space Science, https://doi.org/10.1029/2018EA000401 (2018).

32. Legates, D.R., Soon, W.W.-H., Briggs, W.M., Monckton of Brenchley, C.W. Climate consensus and misinformation: a rejoinder to “Agnotology Scientific Consensus, and the Teaching and Learning of Climate Change”, Sci. Educ., doi:10.1007/s11191-013-9647-9 (2015).

33. Stern, N. The economics of climate change: the Stern review. Cambridge University Press, Cambridge (2006).

34. Dietz, S., Hope, C., Stern, N., Zenghelis, D. Reflections on the Stern Review (1): a robust case for strong action to reduce the risks of climate change. World Econ. 8(1), 121–168 (2007).

35. Garnaut, R. The Garnaut Climate Change Review: Final Report. Cambridge University Press, Port Melbourne, Australia, ISBN 9780521744447 (2008).

36. Murphy, J. Some Simple Economics of Climate Changes. Paper presented to the MPS General Meeting, Tokyo (2008 September 8).

37. Nordhaus, W.D. A question of balance: weighing the options on global warming policies. Yale University Press (2008).

38. Jouzel, J. et al. Orbital and millennial Antarctic climate variability over the past 800,000 years. Science 317, 793–796 (2007).

39. Monckton of Brenchley, C.W. The temperature feedback problem. Energy Envir. 26 (5), 829–840 (2015).