30 July 2021
I get emails from the EPA Office of Public Engagement. They came regularly, though not since I submitted testimony to them on June 21.
The short of it is that on April 26, I received an email from the EPA with the subject line, “EPA Reconsiders Previous Administration’s Withdrawal of California’s Waiver to Enforce Greenhouse Gas Standards for Cars and Light Trucks“
California has applied for a waiver from the EPA’s SAFE-1 vehicle rule, which regulates so-called GHG emissions of cars and light trucks. These are the vehicles used by families and small business owners, primarily.
California wants to apply stricter emission standards than the EPA warrants — no surprise there — and so has asked for a waiver from the SAFE-1 Rule.
The EPA’s April 26 email noted the opportunity to remotely testify at public hearings about the waiver during June 2-June 6. So, I availed myself of it. Each speaker got three minutes. But written testimony was also accepted at the EPA Docket web portal.
My June 2nd three minutes included self-introduction and quick mention of 21 years attention to climate science, that climate models are unreliable, and the IPCC doesn’t know what it’s talking about. The EPA CO2 endangerment finding has no scientific basis, so the SAFE-1 rule is pointless.
If the SAFE-1 rule is pointless, well, then, so is a waiver from it. A rather condensed 3-minute message.
The panel noted that written testimony was accepted at their Docket web portal.
So, I uploaded the more detailed written testimony to the EPA on June 4. It presented the unreliability of the current CMIP6 climate models and reminded the EPA of their own stated commitment to make evidence-based decisions using only the best available science. Right.
The unskilled CMIP6 climate models undergird the soon-to-be-portentously-cried IPCC 6AR.
A PDF of the full testimony is available to anyone in California who wishes to send it to their state representative; or to the California Air Resources Board; or to Mr. Larry Elder’s campaign; or to any lawyer engaged in a class-action suit to recover injuries caused by false-precision-based climate legislation.
Here’s the testimony.
Written Comments on the US EPA SAFE 1 Adjudication Proposal
With Necessary Reference to the Science Underlying the CO2 Endangerment Finding
Docket ID No. EPA-HQ-OAR-2021-0257
Patrick Frank, Ph.D.
Oral testimony presented to the Environmental Protection Agency
2021 June 2
The 31 March 2020 EPA SAFE Vehicles Rule finds its justification in the 7 December 2009 EPA CO2 Endangerment Finding.
General circulation climate models (GCMs) provide the sole foundation for both the 2009 Endangerment Finding and the SAFE Vehicle Rule because GCMs are the sole source for equating danger to CO2 emissions.
Until recently, the physical accuracy and reliability of GCM outputs had never been evaluated.
Propagation of Error and the Reliability of Global Air Temperature Projections,  published on 6 September 2019 following expert peer-review, presents the first critical evaluation of the physical accuracy and reliability of advanced GCMs, with direct bearing on the notion that CO2 emissions are dangerous.
- cloud fraction simulation error indicates a GCM lower limit of resolution that is about 800 times too coarse to detect a thermal signal, if any, from CO2 emissions.the uncertainty in centennial-scale GCM projections of air temperature is ±(12-17) C.
- GCMs are unable to detect, to attribute, or to project the effect, if any, of CO2 emissions upon global air temperature.
- They have no predictive value.
The unavoidable conclusions are that the SAFE Vehicle Rule serves no ameliorative purpose because the EPA CO2 endangerment finding is without any scientific merit.
As the SAFE Vehicle Rule serves no evident purpose, a SAFE waiver extended to California is senseless. The EPA is self-committed to adjudicate the California waiver accordingly.
Full Written Testimony
The EPA Office of Public Engagement Release of 10 February 2021 was, “EPA Takes Action to Protect Scientific Integrity.” Therein, Acting Science Advisor Dr. Jennifer Orme-Zavaleta noted that, “Science is the backbone of EPA.” Dr. Orme-Zavaleta further committed the EPA to, “making evidence-based decisions and developing policies and programs that are guided by the best available scientific data.“
The testimony herein is presented with the confidence that the EPA will fulfill its commitment to scientific integrity and to guidance by the best science.
The EPA SAFE Vehicles Rule was activated on 31 March 2020. The SAFE protocol establishes fuel economy standards to service an imperative calling for a decrease in automotive tailpipe emissions of carbon dioxide (CO2). The present EPA concern is adjudicating the reintroduction of a waiver of SAFE allowing California to enforce its own greenhouse gas pollution standards for cars and trucks.
The imperative to decrease CO2 emissions rests upon the 7 December 2009 EPA CO2 endangerment finding. Therefore, the EPA SAFE Vehicles Rule, and waivers pertaining thereto, are driven entirely by the EPA CO2 endangerment finding.
This testimony evaluates whether the SAFE Vehicle Rule is based upon the best science. That evaluation will in turn determine whether the waiver for California has valid standing.
The full peer-reviewed scientific case supporting this testimony is available as an open access publication , and is included herein as an Addendum.
The entire case for a future catastrophe in air temperatures driven by CO2 emissions, rests upon the projections derived from general circulation climate models (GCMs). However, climate models through the CMIP5 generation have no predictive value (cf. below).  The prospect of a future extreme of air temperatures therefore has no scientific standing.
Explanatory Figure 1 presents evidence that a simple linear equation can successfully emulate the air temperature projections of the most advanced CMIP6 generation of climate models.
Figure 1: CMIP6 GCM air temperature projections can be fully replicated using a simple linear equation. Left panels: (blue points), the air temperature projections of the CMIP6 AWI-CM-1-1 GCM of the Alfred Wegener Institute, for four different shared socioeconomic pathway (SSP) forcing scenarios; (red lines), successful emulations of the projections using the “Climate Model Emulator” (cf. above, right)), using the identical SSP forcings.
Figure 1 shows that the same linear equation that successfully emulated the air temperature projections of CMIP5 and all prior generations of GCMs,  will faithfully emulate the air temperature projections of the current CMIP6 climate models. This work will be submitted for publication. 
Explanatory Figure 2 below conveys the CMIP6 error in simulated global cloud fraction.[1, 3, 4] Clouds control the amount of sun-derived thermal energy that resides in the troposphere (the atmosphere laying between the surface and the stratosphere).
Comparison of simulated cloud fraction against observed cloud fraction calibrates the accuracy of climate model output. Figure 2, left, shows that neither CMIP5 nor CMIP6 climate models are able to correctly simulate the global cloud cover fraction.
Simulation error in cloud cover produces an error in the simulated thermal energy flux (the heat content) of the troposphere. The thermal energy flux of the troposphere determines air temperature. (, cf. Figure 7.1)
Evaluation of 45 CMIP6 GCMs indicated an annual average error in simulated tropospheric thermal energy flux of ±2.9 W/m2.  By way of comparison, the annual average of thermal flux energy (forcing) that CO2 emissions contribute to the troposphere since 1979 is 0.035 W/m2.
Figure 2: (left), the CMIP6 error in simulated cloud cover, and; (right) the consequent error in tropospheric thermal energy flux.
The level of GCM simulation error defines their power to resolve detail. The relative sizes of GCM resolution of thermal energy flux and CO2 forcing is (±2.9 W/m2)/(0.035 W/m2) = 82.9.
That is, the smallest detail of tropospheric thermal energy flux (heat content) that can be resolved in a GCM simulation is 83 times larger than CO2 forcing. More simply, if a CMIP6 model were a lens, the effect of CO2 forcing would be 83 times too small to notice.
Typically, resolution power must be ten times signal intensity in order to obtain a reliable determination. In this metric, CMIP6 climate models must improve by 830-fold in order to reliably detect a forcing signal from CO2 emissions, if any.
Explanatory Figure 3 demonstrates the impact of CMIP6 error in simulated tropospheric thermal energy flux, on the reliability of CMIP6 air temperature projections. One notes here that the 23 June 1988 presentation before the Senate Committee on Energy and Natural Resources included no uncertainty bars. 
Uncertainty in a linear summation such as the projected air temperature of an advanced GCM, is the addition in quadrature of the error in each member of the sum.[1, 7, 8]
The uncertainty in the sum total is the magnitude of each entry propagated forward combined in quadrature. The result is an increasingly large envelope of uncertainty. 
From Figure 3, the uncertainty in the CMIP6 projected air temperature for the four shared socioeconomic pathways is, ±16.7 C (±30.1 F, ssp126), ±16 C (±28.8 F, ssp245), ±15.7 C (±28.3 F, ssp370), and ±12.1 C (±21.8 F, ssp585), after a centennial simulation.
These very large uncertainty envelopes reflect the 83-fold disparity between the error in simulated cloud fraction and the tiny perturbation from CO2 emissions.
The uncertainty after 100 years of projection exceeds any possible physical change in temperature. However, these large plus/minus uncertainties do not imply that the future climate may be, e.g., 30 F warmer or cooler than now.
The plus/minus uncertainty statistics do not at all indicate temperature. They indicate the region where complete ignorance reigns. This absolutely central point must be understood.
Figure 3: (left panels), the uncertainty envelopes around future air temperatures for four different shared socioeconomic pathway (SSP) forcing scenarios projected using the AWI-CM-1-1 CMIP6 GCM of the Alfred Wegener Institute (cf. Figure 1); (right panel), the emulation equation now including the ±2.9 W/m2 contribution of average annual CMIP6 tropospheric thermal energy flux error used to derive the uncertainty bounds.
The resolution of CMIP6 climate models is not up to the job of discerning or predicting the effect, if any, of CO2 emissions upon the climate. The large uncertainty envelopes indicate that future air temperatures are invisible to CMIP6 climate models.
Climate models cannot predict air temperatures 100 years out. Nor can they predict air temperatures one year out.
The strictly scientific interpretation of the uncertainty envelopes of Figure 3 is that the air temperature projections of CMIP6 climate models are physically meaningless. They impart no information whatever about future global air temperature.
Focus now returns to adjudication of the SAFE waiver for California.
The absence of any physical meaning in temperatures projected on the grounds of forcing from CO2 emissions means the SAFE Vehicle Rule is not grounded in science.
Indeed, the notion that vehicular CO2 emissions represent pollution at all is analytically vacated.
The unavoidable conclusions are that the SAFE Vehicle Rule serves no ameliorative purpose because the EPA CO2 endangerment finding has no scientific merit.
As the SAFE Vehicle Rule serves no evident purpose, the SAFE waiver extended to California is senseless and of no import.
The EPA has committed itself to adjudicate the California waiver accordingly.
In Added Note
The EPA Technical Support (TS) document of the endangerment finding is not a critical analysis. It is instead a catalogue recrudescing the IPCC Assessment Reports.
For example, the TS document ignores the known systematic temperature measurement errors of field meteorological stations. These errors completely obscure the rate and the magnitude of climate warming since 1900. [9, 10]
Further, The TS document uncritically accepts proxy air-temperature reconstructions despite that they have no distinct physical meaning. 
Critical analysis fully removes the notion that the EPA CO2 endangerment finding has any scientific standing. Neither, then, does the 2020 SAFE Vehicle Rule. A vitiation waiver for California is senseless.
 Frank, P., Propagation of Error and the Reliability of Global Air Temperature Projections. Frontiers in Earth Science: Atmospheric Sciences, 2019. 7(223) https://www.frontiersin.org/article/10.3389/feart.2019.00223.
 Frank, P., Are CMIP6 Air Temperature Projections Reliable? in preparation, 2021
 Vignesh, P.P., et al., Assessment of CMIP6 Cloud Fraction and Comparison with Satellite Observations. Earth and Space Science, 2020. 7(2): p. e2019EA000975 https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019EA000975.
 Wild, M., The global energy balance as represented in CMIP6 climate models. Climate Dynamics, 2020. 55(3): p. 553-577 https://doi.org/10.1007/s00382-020-05282-7.
 IPCC, Climate Change 2013: The Physical Science Basis. Contribution of Working Group 1 to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T.F. Stocker, et al., Editors. 2013, Cambridge University Press: Cambridge, United Kingdom and New York, NY, USA. p. 1535.
 Hansen, J. Statement of Dr. James Hansen, Director, NASA Goddard Institute for Space Studies. 1988 [Last accessed: 4 June 2021; Testimony before the US Senate Committee on Energy and Natural Resources: The Greenhouse Effect: Impacts on Current Global Temperature and Regional Heat Waves]. Available from: http://image.guardian.co.uk/sys-files/Environment/documents/2008/06/23/ClimateChangeHearing1988.pdf.
 Bevington, P.R. and D.K. Robinson, Data Reduction and Error Analysis for the Physical Sciences. 3rd ed. 2003, Boston: McGraw-Hill.
 Taylor, B.N. and C.E. Kuyatt., Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results. 1994, National Institute of Standards and Technology: Washington, DC. p. 20.
 Frank, P., Uncertainty in the Global Average Surface Air Temperature Index: A Representative Lower Limit. Energy & Environment, 2010. 21(8): p. 969-989 https://doi.org/10.1260/0958-305X.21.8.969
 Frank, P., Systematic Error in Climate Measurements: the global air temperature record, in The Role of Science in the Third Millennium, R. Ragaini ed, 2016, World Scientific: Singapore, pp. 337-351.
 Frank, P., Negligence, Non-Science, and Consensus Climatology. Energy & Environment, 2015. 26(3): p. 391-416 http://multi-science.atypon.com/doi/abs/10.1260/0958-305X.26.3.391.
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