Sensitivity
In addition to those I cite below, here is a list of more than 160 peer-reviewed papers showing less sensitivity to CO2 doubling than the IPCC claims. Remember that “sensitivity” is the theoretical instantaneous atmospheric response of the lapse rate to a rapid doubling of CO2. It’s calculated (not measured) in degrees C. It does not take into account other systems or feedbacks.
Number of papers: 14
Net-Zero Averted Temperature Increase — Arxiv Atmospheric and Ocean Physics, 2024; Happer, Van Wijngaarden, and Lindzen
“Using feedback-free estimates of the warming by increased atmospheric carbon dioxide (CO2) and observed rates of increase, we estimate that if the United States (U.S.) eliminated net CO2 emissions by the year 2050, this would avert a warming of 0.0084 C (0.015 F), which is below our ability to accurately measure. If the entire world forced net zero CO2 emissions by the year 2050, a warming of only 0.070 C (0.13 F) would be averted. If one assumes that the warming is a factor of 4 larger because of positive feedbacks, as asserted by the Intergovernmental Panel on Climate Change (IPCC), the warming averted by a net zero U.S. policy would still be very small, 0.034 C (0.061 F). For worldwide net zero emissions by 2050 and the 4-times larger IPCC climate sensitivity, the averted warming would be 0.28 C (0.50 F).”
Objectively combining climate sensitivity evidence — Climate dynamics, 2022; Nic Lewis
Recent assessments of climate sensitivity per doubling of atmospheric CO2 concentration have combined likelihoods derived from multiple lines of evidence. These assessments were very influential in the Intergovernmental Panel on Climate Change Sixth Assessment Report (AR6) assessment of equilibrium climate sensitivity, the likely range lower limit of which was raised to 2.5 °C (from 1.5 °C previously). This study evaluates the methodology of and results from a particularly influential assessment of climate sensitivity that combined multiple lines of evidence, Sherwood et al. (Rev Geophys 58(4):e2019RG000678, 2020). That assessment used a subjective Bayesian statistical method, with an investigator-selected prior distribution. This study estimates climate sensitivity using an Objective Bayesian method with computed, mathematical priors, since subjective Bayesian methods may produce uncertainty ranges that poorly match confidence intervals. … The resulting estimates of long-term climate sensitivity are much lower and better constrained (median 2.16 °C, 17–83% range 1.75–2.7 °C, 5–95% range 1.55–3.2 °C) than in Sherwood et al. and in AR6 (central value 3 °C, very likely range 2.0–5.0 °C). This sensitivity to the assumptions employed implies that climate sensitivity remains difficult to ascertain, and that values between 1.5 °C and 2 °C are quite plausible.
Effective climate sensitivity distributions from a 1D model of global ocean and land temperature trends, 1970–2021 — Theoretical and Applied Climatology, 2023; Spencer & Christy
The authors attempt to answer the question, What effective climate sensitivity is consistent with the observed rates of land and deep-ocean warming over the last 50 + years? The observed rate of surface warming during that time is less than produced by 80% of 36 CMIP6 climate models, and the CMIP6 models still have documented problems with energy conservation and produce future warming rates that vary by a factor of three. To address this question, a 1D time-dependent model of global monthly average temperature departures from energy equilibrium was forced with the newer SSP245 and older RCP6 radiative forcing scenarios. They calculate that global average EffCS is 1.86 deg. C. for the SSP245 ERF scenario, and 2.49 deg. C for the RCP6 scenario, which is slightly warmer than Lewis’s estimate (above).
Climate Sensitivity to an Increase in the Carbon Dioxide Concentration in the Atmosphere Decreases with an Increase in the Water Vapor Concentration upon Warming — Geomagnetism and Aeronomy, 2021; H. I. Abdussamatov
This author claims to show that feedbacks of rising CO2 are actually negative, rather than positive as alarmists claim.
Natural climate variability, part 1: Observations versus the modeled predictions — International Journal of Heat and Technology, 2017; Scafetta et al
The authors compare models to reality and find that the models consistently overpredict past temperatures and can only reliably predict 1980 to 1999, which was a strong, el-Nino-driven period that the models got right in the same way that a broken clock is right twice a day.
Natural climate variability, part 2: Interpretation of the post 2000 temperature standstill — International Journal of Heat and Technology, 2017; Scafetta et al
Since 2000, the global surface temperature really hasn’t changed, defying the models. The exception is the 2016 el Nino event, unrelated to CO2. The authors show that the IPCC models are wrong, and that a natural prediction based on 200 years of gradual warming is much more accurate.
CMIP6 GCM ensemble members versus global surface temperatures — Climate Dynamics, 2022; Nicola Scafetta
From the abstract: “These results suggest that the actual ECS may be relatively low, i.e. lower than 3 ∘C or even less than 2 ∘C if the 1980–2021 global surface temperature records contain spurious warming, as some alternative studies have already suggested. Therefore, the projected global climate warming over the next few decades could be moderate and probably not particularly alarming.”
The Impact of Recent Forcing and Ocean Heat Uptake Data on Estimates of Climate Sensitivity — Journal of Climate, 2018; Lewis & Curry
This important analysis by Lewis and Curry shows that the IPCC’s calculation for sensitivity to increased CO2 is unrealistically high. I show the same in my piece on CO2 saturation.
A Case Against Precipitous Climate Action — Energy and Environment. 2011, Richard Lindzen
Lindzen explains that the earth’s temperature varies naturally and that we measure the atmosphere so poorly that anyone can cherrypick data to suit any argument. This does not mean that humans are causing the climate to change.
On the observational determination of climate sensitivity and its implications — Asia-Pacific Atmospheric Journal of Sciences, 2011; Lindzen & Choi
The authors revisit previous papers and arguments, incorporating CERES data, refining their analysis, and still find that many climate feedbacks are negative. “… we show that simple regression methods used by several existing papers generally exaggerate positive feedbacks and even show positive feedbacks when actual feedbacks are negative.”
Testing the CMIP6 GCM Simulations versus Surface Temperature Records from 1980–1990 to 2011–2021: High ECS Is Not Supported — Climate, 2021; Nicola Scafetta
The author tests the real-world performance of 38 CMIP6 models used by the IPCC against three actual data sets of temperature over 1980–2021 and finds that the higher the climate sensitivity built into the models, the worse they perform. The author concludes, “This result suggests that climate change and its natural variability remain poorly modeled by the CMIP6 GCMs.” He also proposes that even the IPCC’s lower bound for sensitivity is too high [ed note: the IPCC reduced their lower bound sensitivity number in the subsequent AR6 report. It is still too high.]
The Impact of CO2, H2O and Other “Greenhouse Gases” on Equilibrium Earth Temperatures — International Journal of Atmospheric and Oceanic Sciences, 2021; Coe et al.
The authors show a less complex method of accounting for the greenhouse effect than the IPCC, concluding: “H2O is responsible for 29.4K of the 33K warming, with CO2 contributing 3.3K and CH4 and N2O combined just 0.3K. Climate sensitivity to future increases in CO2 concentration is calculated to be 0.50K, including the positive feedback effects of H2O, while climate sensitivities to CH4 and N2O are almost undetectable at 0.06K and 0.08K respectively. This result strongly suggests that increasing levels of CO2 will not lead to significant changes in earth temperature and that increases in CH4 and N2O will have very little discernible impact.”
The application of machine learning for evaluating anthropogenic versus natural climate change — GeoResJ, 2017; Abbott & Marohasy
Their machine-learning model skillfully hindcasts temperatures, suggesting CO2 sensitivity on the very low end of 0.6 degrees C.
On the importance of the natural components in climate change study: Temperature rise in the study of climate change — Physics & Astronomy International Journal, 2021; Akasofu & Tanaka
“The combined rise of temperature by the two natural components between 1975 and 2000 (which is considered to be due to CO2 by the IPCC) is 0.47°C; it is comparable with the observed rise of 0.5°C during the same period. Thus, the contribution of the greenhouse gases for the same period is estimated to be at most 0.1°C, not 0.5°C.I.”