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Peer Review in a 97% Consensus Science

Posted on: May 6, 2018

 

JIM JONES HAD 97% CONSENSUS IN JONESTOWN: 1978

 

TCRE: TRANSIENT CLIMATE RESPONSE TO CUMULATIVE EMISSIONS

 

[LIST OF POSTS ON THIS SITE]

 

[RELATED POST ON TCRE]

 

  1. In 2009, Damon Matthews et al submitted a paper to the journal Nature with an amazing discovery that could potentially rescue climate science from the climate sensitivity uncertainty problem. He found a strong correlation between temperature (=cumulative warming) and cumulative emissions. It was quickly named the CCR (Climate Carbon Response) and later the TCRE (Transient Climate Response to Cumulative Emissions) and soon used to forecast the so called carbon budgets for a 2C and 1.5C warming targets.
  2. The TCRE became a sensation. In accepting the (Matthews, 2009) paper for publication the editor of Nature gushed in an editorial comment that: “To date, efforts to describe and predict the climate response to human CO2 emissions have focused on climate sensitivity: the equilibrium temperature change associated with a doubling of CO2. But recent research has suggested that this ‘Charney’ sensitivity, so named after the meteorologist Jule Charney who first adopted this approach in 1979, may be an incomplete representation of the full Earth system response, as it ignores changes in the carbon cycle, aerosols, land use and land cover.”
  3. He continued: “Matthews et al. propose a new measure, the carbon-climate response, or CCR. Using a combination of a simplified climate model, a range of simulations from a recent model inter-comparison, and historical constraints, they find that independent of the timing of emissions or the atmospheric concentration of CO2 emitting a trillion tonnes of carbon will cause 1.0 – 2.1 C of global warming, a CCR value that is consistent with model predictions for the twenty-first century.”
  4. In a 2017 paper Reto Knutti also gushed about Matthews’ proportionality writing that the TCRE metric should replace the ECS as the primary tool for relating warming to human caused emissions. The Knutti paper was not only published but received with great fanfare by the climate science community.
  5. As of this writing in 2018, the TCRE correlation serves as the key relationship that ties warming to emissions and thereby to human cause. The Matthews paper has engendered scores of more papers on TCRE and Carbon Budgets all of them enthusiastically published in the journals.
  6. But the inner circle of climate scientists, in their enthusiasm for a savior in the quest for human cause, failed to critically evaluate the Matthews “proportionality”. If they had they might have found that the proportionality between temperature and cumulative emissions that serves as the foundation of TCRE rests on a spurious correlation as shown in a related post [LINK] .
  7. The mathematical argument for the spuriousness of correlations between cumulative values may be found here: SSRN1  SSRN2  SSRN3 . The spuriousness is demonstrated in the videos below where we can see that the cumulative values of random emissions and random warming generate just the kind of correlation shown in the Matthews paper and all subsequent papers on this subject. Yet this proportionality continues to be used in climate science as the only link between human fossil fuel emissions and global warming.
  8. The two videos together show that the correlation found by Matthews is the creation of a fortuitous sign convention in the data in which emissions are always positive and, during a time of global warming, the warming values tend to be mostly positive. In other words, what the Matthews correlation tells us is that the temperature data do indeed show a warming trend; and nothing more.
  9. And yet, in their rush and eagerness to find strong empirical connection between emissions and warming that can serve to underscore the call to emission reduction, climate science and their peer review process overlooked basic statistical considerations. And nine years later, we find that scores of papers on the spurious TCRE correlation have been published in peer reviewed journals and also that the IPCC has adopted the TCRE in its carbon budget for a target warming of 1.5C “since pre-industrial times”.
  10. The usual assumption by consumers of such information among the general public and among policy makers is that peer review is a seal of truth that justifies the appeal to authority fallacy. This glaring incident should serve as a cautionary tale that neither the scientific credentials of the authors nor the peer review process of journals offers a guarantee of truth particularly so when the scientists in question are also activists who are passionately involved in an advocacy that is closely related to the subject matter of their research.
  11. An additional factor that should be considered is that a scientific community that admits to complete consensus and group-think on all matters in consideration is unlikely to provide critical peer review to their fellow researchers. Although the climate science community prides itself on a 97% consensus, such consensus is likely to degrade and not enhance objective scientific inquiry and critical and effective peer review in their journals.

 

[RELATED POST ON TCRE]

 

[LIST OF POSTS ON THIS SITE]

 

 

RANDOM NUMBERS WITH SIGN CONSTRAINT

 

RANDOM NUMBERS WITHOUT SIGN CONSTRAINT

 

 

TCRE BIBLIOGRAPHY

  1. 2009: Matthews, H. Damon, et al. “The proportionality of global warming to cumulative carbon emissions.” Nature 459.7248 (2009): 829.  ABSTRACT: The global temperature response to increasing atmospheric CO2 is often quantified by metrics such as equilibrium climate sensitivity and transient climate response1. These approaches, however, do not account for carbon cycle feedbacks and therefore do not fully represent the net response of the Earth system to anthropogenic CO2 emissions. Climate–carbon modelling experiments have shown that: (1) the warming per unit CO2 emitted does not depend on the background CO2 concentration2; (2) the total allowable emissions for climate stabilization do not depend on the timing of those emissions3,4,5; and (3) the temperature response to a pulse of CO2 is approximately constant on timescales of decades to centuries3,6,7,8. Here we generalize these results and show that the carbon–climate response (CCR), defined as the ratio of temperature change to cumulative carbon emissions, is approximately independent of both the atmospheric CO2 concentration and its rate of change on these timescales. From observational constraints, we estimate CCR to be in the range 1.0–2.1 °C per trillion tonnes of carbon (Tt C) emitted (5th to 95th percentiles), consistent with twenty-first-century CCR values simulated by climate–carbon models. Uncertainty in land-use CO2 emissions and aerosol forcing, however, means that higher observationally constrained values cannot be excluded. The CCR, when evaluated from climate–carbon models under idealized conditions, represents a simple yet robust metric for comparing models, which aggregates both climate feedbacks and carbon cycle feedbacks. CCR is also likely to be a useful concept for climate change mitigation and policy; by combining the uncertainties associated with climate sensitivity, carbon sinks and climate–carbon feedbacks into a single quantity, the CCR allows CO2-induced global mean temperature change to be inferred directly from cumulative carbon emissions.
  2. 2013: Gillett, Nathan P., et al. “Constraining the ratio of global warming to cumulative CO2 emissions using CMIP5 simulations.” Journal of Climate 26.18 (2013): 6844-6858. The ratio of warming to cumulative emissions of carbon dioxide has been shown to be approximately independent of time and emissions scenarios and directly relates emissions to temperature. It is therefore a potentially important tool for climate mitigation policy. The transient climate response to cumulative carbon emissions (TCRE), defined as the ratio of global-mean warming to cumulative emissions at CO2doubling in a 1% yr−1 CO2 increase experiment, ranges from 0.8 to 2.4 K EgC−1 in 15 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5)—a somewhat broader range than that found in a previous generation of carbon–climate models. Using newly available simulations and a new observational temperature dataset to 2010, TCRE is estimated from observations by dividing an observationally constrained estimate of CO2-attributable warming by an estimate of cumulative carbon emissions to date, yielding an observationally constrained 5%–95% range of 0.7–2.0 K EgC−1.
  3. 2014: Allen, Myles R., and Thomas F. Stocker. “Impact of delay in reducing carbon dioxide emissions.” Nature Climate Change4.1 (2014): 23. Recent downward revisions in the climate response to rising CO2 levels, and opportunities for reducing non-CO2 climate warming, have both been cited as evidence that the case for reducing CO2 emissions is less urgent than previously thought. Evaluating the impact of delay is complicated by the fact that CO2 emissions accumulate over time, so what happens after they peak is as relevant for long-term warming as the size and timing of the peak itself. Previous discussions have focused on how the rate of reduction required to meet any given temperature target rises asymptotically the later the emissions peak. Here we focus on a complementary question: how fast is peak CO2-induced warming increasing while mitigation is delayed, assuming no increase in rates of reduction after the emissions peak? We show that this peak-committed warming is increasing at the same rate as cumulative CO2 emissions, about 2% per year, much faster than observed warming, independent of the climate response.
  4. 2014: Herrington, T., and K. Zickfeld. “Path independence of climate and carbon cycle response over a broad range of cumulative carbon emissions.” Earth System Dynamics 5.2 (2014): 409-422. Recent studies have identified an approximately proportional relationship between global warming and cumulative carbon emissions, yet the robustness of this relationship has not been tested over a broad range of cumulative emissions and emission rates. This study explores the path dependence of the climate and carbon cycle response using an Earth system model of intermediate complexity forced with 24 idealized emissions scenarios across five cumulative emission groups (1275–5275 Gt C) with varying rates of emission. We find the century-scale climate and carbon cycle response after cessation of emissions to be approximately independent of emission pathway for all cumulative emission levels considered. The ratio of global mean temperature change to cumulative emissions – referred to as the transient climate response to cumulative carbon emissions (TCRE) – is found to be constant for cumulative emissions lower than ∼1500 Gt C but to decline with higher cumulative emissions. The TCRE is also found to decrease with increasing emission rate. The response of Arctic sea ice is found to be approximately proportional to cumulative emissions, while the response of the Atlantic Meridional Overturning Circulation does not scale linearly with cumulative emissions, as its peak response is strongly dependent on emission rate. Ocean carbon uptake weakens with increasing cumulative emissions, while land carbon uptake displays non-monotonic behavior, increasing up to a cumulative emission threshold of ∼2000 Gt C and then declining.
  5. 2014: Krasting, J. P., et al. “Trajectory sensitivity of the transient climate response to cumulative carbon emissions.” Geophysical Research Letters 41.7 (2014): 2520-2527. The robustness of Transient Climate Response to cumulative Emissions (TCRE) is tested using an Earth System Model (Geophysical Fluid Dynamics Laboratory‐ESM2G) forced with seven different constant rates of carbon emissions (2 GtC/yr to 25 GtC/yr), including low emission rates that have been largely unexplored in previous studies. We find the range of TCRE resulting from varying emission pathways to be 0.76 to 1.04°C/TtC. This range, however, is small compared to the uncertainty resulting from varying model physics across the Fifth Coupled Model Intercomparison Project ensemble. TCRE has a complex relationship with emission rates; TCRE is largest for both low (2 GtC/yr) and high (25 GtC/yr) emissions and smallest for present‐day emissions (5–10 GtC/yr). Unforced climate variability hinders precise estimates of TCRE for periods shorter than 50 years for emission rates near or smaller than present day values. Even if carbon emissions would stop, the prior emissions pathways will affect the future climate responses.
  6. 2015″ Goodwin, Philip, Richard G. Williams, and Andy Ridgwell. “Sensitivity of climate to cumulative carbon emissions due to compensation of ocean heat and carbon uptake.” Nature Geoscience 8.1 (2015): 29. Climate model experiments reveal that transient global warming is nearly proportional to cumulative carbon emissions on multi-decadal to centennial timescales1,2,3,4,5. However, it is not quantitatively understood how this near-linear dependence between warming and cumulative carbon emissions arises in transient climate simulations6,7. Here, we present a theoretically derived equation of the dependence of global warming on cumulative carbon emissions over time. For an atmosphere–ocean system, our analysis identifies a surface warming response to cumulative carbon emissions of 1.5 ± 0.7 K for every 1,000 Pg of carbon emitted. This surface warming response is reduced by typically 10–20% by the end of the century and beyond. The climate response remains nearly constant on multi-decadal to centennial timescales as a result of partially opposing effects of oceanic uptake of heat and carbon8. The resulting warming then becomes proportional to cumulative carbon emissions after many centuries, as noted earlier9. When we incorporate estimates of terrestrial carbon uptake10, the surface warming response is reduced to 1.1 ± 0.5 K for every 1,000 Pg of carbon emitted, but this modification is unlikely to significantly affect how the climate response changes over time. We suggest that our theoretical framework may be used to diagnose the global warming response in climate models and mechanistically understand the differences between their projections.
  7. 2016: Leduc, Martin, H. Damon Matthews, and Ramón de Elía. “Regional estimates of the transient climate response to cumulative CO 2 emissions.” Nature Climate Change 6.5 (2016): 474. The Transient Climate Response to cumulative carbon Emissions (TCRE) measures the response of global temperatures to cumulative CO2emissions1,2,3,4. Although the TCRE is a global quantity, climate impacts manifest predominantly in response to local climate changes. Here we quantify the link between CO2 emissions and regional temperature change, showing that regional temperatures also respond approximately linearly to cumulative CO2 emissions. Using an ensemble of twelve Earth system models, we present a novel application of pattern scaling5,6 to define the regional pattern of temperature change per emission of CO2. Ensemble mean regional TCRE values range from less than 1 °C per TtC for some ocean regions, to more than 5 °C per TtC in the Arctic, with a pattern of higher values over land and at high northern latitudes. We find also that high-latitude ocean regions deviate more strongly from linearity as compared to land and lower-latitude oceans. This suggests that ice-albedo and ocean circulation feedbacks are important contributors to the overall negative deviation from linearity of the global temperature response to high levels of cumulative emissions. The strong linearity of the regional climate response over most land regions provides a robust way to quantitatively link anthropogenic CO2 emissions to local-scale climate impacts.
  8. 2017: Millar, Richard J., et al. “Emission budgets and pathways consistent with limiting warming to 1.5 C.” Nature Geoscience10.10 (2017): 741. The Paris Agreement has opened debate on whether limiting warming to 1.5 °C is compatible with current emission pledges and warming of about 0.9 °C from the mid-nineteenth century to the present decade. We show that limiting cumulative post-2015 CO2 emissions to about 200 GtC would limit post-2015 warming to less than 0.6 °C in 66% of Earth system model members of the CMIP5 ensemble with no mitigation of other climate drivers. We combine a simple climate–carbon-cycle model with estimated ranges for key climate system properties from the IPCC Fifth Assessment Report. Assuming emissions peak and decline to below current levels by 2030, and continue thereafter on a much steeper decline, which would be historically unprecedented but consistent with a standard ambitious mitigation scenario (RCP2.6), results in a likely range of peak warming of 1.2–2.0 °C above the mid-nineteenth century. If CO2 emissions are continuously adjusted over time to limit 2100 warming to 1.5 °C, with ambitious non-CO2 mitigation, net future cumulative CO2 emissions are unlikely to prove less than 250 GtC and unlikely greater than 540 GtC. Hence, limiting warming to 1.5 °C is not yet a geophysical impossibility, but is likely to require delivery on strengthened pledges for 2030 followed by challengingly deep and rapid mitigation. Strengthening near-term emissions reductions would hedge against a high climate response or subsequent reduction rates proving economically, technically or politically unfeasible.
  9. 2017: MacDougall, Andrew H., Neil C. Swart, and Reto Knutti. “The uncertainty in the transient climate response to cumulative CO2 emissions arising from the uncertainty in physical climate parameters.” Journal of Climate 30.2 (2017): 813-827. An emergent property of most Earth system models is a near-linear relationship between cumulative emission of CO2 and change in global near-surface temperature. This relationship, which has been named the transient climate response to cumulative CO2 emissions (TCRE), implies a finite budget of fossil fuel carbon that can be burnt over all time consistent with a chosen temperature change target. Carbon budgets are inversely proportional to the value of TCRE and are therefore sensitive to the uncertainty in TCRE. Here the authors have used a perturbed physics approach with an Earth system model of intermediate complexity to assess the uncertainty in the TCRE that arises from uncertainty in the rate of transient temperature change and the effect of this uncertainty on carbon cycle feedbacks. The experiments are conducted using an idealized 1% yr−1 increase in CO2 concentration. Additionally, the authors have emulated the temperature output of 23 models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The experiment yields a mean value for TCRE of 1.72 K EgC−1 with a 5th to 95th percentile range of 0.88 to 2.52 K EgC−1. This range of uncertainty is consistent with the likely range from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (0.8 to 2.5 K EgC−1) but by construction underestimates the total uncertainty range of TCRE, as the authors’ experiments cannot account for the uncertainty from their models’ imperfect representation of the global carbon cycle. Transient temperature change uncertainty induces a 5th to 95th percentile range in the airborne fraction at the time of doubled atmospheric CO2 of 0.50 to 0.58. Overall the uncertainty in the value of TCRE remains considerable.
  10. 2017: Munshi, Jamal. “Limitations of the TCRE: Transient Climate Response to Cumulative Emissions.” (2017). Observed correlations between cumulative emissions and cumulative changes in climate variables form the basis of the Transient Climate Response to Cumulative Emissions (TCRE) function. The TCRE is used to make forecasts of future climate scenarios based on different emission pathways and thereby to derive their policy implications for climate action. Inaccuracies in these forecasts likely derive from a statistical weakness in the methodology used. The limitations of the TCRE are related to its reliance on correlations between cumulative values of time series data. Time series of cumulative values contain neither time scale nor degrees of freedom. Their correlations are spurious. No conclusions may be drawn from them.
  11. 2017: Knutti, Reto, Maria AA Rugenstein, and Gabriele C. Hegerl. “Beyond equilibrium climate sensitivity.” Nature Geoscience10.10 (2017): 727. Equilibrium climate sensitivity characterizes the Earth’s long-term global temperature response to increased atmospheric CO2concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the ‘likely’ range for climate sensitivity of 1.5 °C to 4.5 °C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 °C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.
  12. 2018: Millar, Richard J., and Pierre Friedlingstein. “The utility of the historical record for assessing the transient climate response to cumulative emissions.” Phil. Trans. R. Soc. A 376.2119 (2018): 20160449. The historical observational record offers a way to constrain the relationship between cumulative carbon dioxide emissions and global mean warming. We use a standard detection and attribution technique, along with observational uncertainties to estimate the all-forcing or ‘effective’ transient climate response to cumulative emissions (TCRE) from the observational record. Accounting for observational uncertainty and uncertainty in historical non-CO2 radiative forcing gives a best-estimate from the historical record of 1.84°C/TtC (1.43–2.37°C/TtC 5–95%uncertainty) for the effective TCRE and 1.31°C/TtC (0.88–2.60°C/TtC 5–95% uncertainty) for the CO2-only TCRE. While the best-estimate TCRE lies in the lower half of the IPCC likely range, the high upper bound is associated with the not-ruled-out possibility of a strongly negative aerosol forcing. Earth System Models have a higher effective TCRE range when compared like-for-like with the observations over the historical period, associated in part with a slight underestimate of diagnosed cumulative emissions relative to the observational best-estimate, a larger ensemble mean-simulated CO2-induced warming, and rapid post-2000 non-CO2 warming in some ensemble members.
  13. 2018: Matthews, H. Damon, et al. “Focus on cumulative emissions, global carbon budgets and the implications for climate mitigation targets.” Environmental Research Letters 13.1 (2018): 010201. The Environmental Research Letters focus issue on ‘Cumulative Emissions, Global Carbon Budgets and the Implications for Climate Mitigation Targets‘ was launched in 2015 to highlight the emerging science of the climate response to cumulative emissions, and how this can inform efforts to decrease emissions fast enough to avoid dangerous climate impacts. The 22 research articles published represent a fantastic snapshot of the state-or-the-art in this field, covering both the science and policy aspects of cumulative emissions and carbon budget research. In this Review and Synthesis, we summarize the findings published in this focus issue, outline some suggestions for ongoing research needs, and present our assessment of the implications of this research for ongoing efforts to meet the goals of the Paris climate agreement.

2 Responses to "Peer Review in a 97% Consensus Science"

[…] Related Post: PEER REVIEW IN CLIMATE SCIENCE: A CASE STUDY […]

[…] SCIENTIFIC CONSENSUS: The strong agreement among climate scientists is often presented as evidence that therefore climate science must be correct. This logic is flawed. Correctness of a scientific finding must rely on data and the scientific method and not on opinion polls. If anything, the 97% consensus statistic works against climate science because it is indicative of a field  of study that harbors a cult-like belief system and therefore incapable of objective scientific inquiry. A climate science peer review case study is presented in a related post that seems to indicate a cultist group-think culture in climate science. The case study is presented in a related post here: CLIMATE SCIENCE PEER REVIEW CASE STUDY. […]

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