The Greenhouse Effect
I'm frequently asked to supply lists of studies supporting the scientific conclusions that we've understood for decades. Sometimes they challenge scientific conclusions that have stood the test of time for centuries. I thought it would be good collect my standard responses in one place. Links in the text descriptions following titles point to my posts that discuss the studies further.
Links to Sections:
I. CO2 Causes Warming
Scientists have understood that increasing CO2 causes global warming since the 19th century, but over the last decade or so, scientists have documented empirical evidence for causation from CO2 and GMST data,[1] observations at the surface, [2] observations at the top of the atmosphere,[3][4] and quantum mechanics.[5] Excepts for these studies follow the citations.
From CO2 & Temperature Data:
[1] Stips, A., Macias, D., Coughlan, C. et al. On the causal structure between CO2 and global temperature. Sci Rep 6, 21691 (2016). https://www.nature.com/articles/srep21691"Using the IF concept we were able to confirm the inherent one-way causality between human activities and global warming, as during the last 150 years the increasing anthropogenic radiative forcing is driving the increasing global temperature, a result that cannot be inferred from traditional time delayed correlation or ordinary least square regression analysis. Natural forcing (solar forcing and volcanic activities) contributes only marginally to the global temperature dynamics during the last 150 years. Human influence, especially via CO2 radiative forcing, has been detected to be significant since about the 1960s. This provides an independent statistical confirmation of the results from process based modelling studies. Investigation of the temperature simulations from the CMIP5 ensemble is largely in agreement with the conclusion drawn from the observational data. However on very long time scales (800,000 years) the IF is only significant in the direction from air temperature to CO2. This supports the idea that the feedback of GHGs to temperature changes seems to be much slower than the fast response of temperature to changes in GHGs."From Surface Measurements:
[2] Feldman DR, Collins WD, Gero PJ, Torn MS, Mlawer EJ, Shippert TR. Observational determination of surface radiative forcing by CO2 from 2000 to 2010. Nature. 2015;519 (7543):339‐343. doi:10.1038/nature14240.
https://escholarship.org/content/qt3428v1r6/qt3428v1r6_noSplash_b5903aebfe105b4071103e11197138f8.pdf
The time series both showstatistically significant trends of 0.2 W m−2 per decade (with respectiveuncertainties of ±0.06 W m−2 per decade and ±0.07 W m−2 per decade) and haveseasonal ranges of 0.1–0.2 W m−2. This is approximately ten per cent of thetrend in downwelling longwave radiation5,6,7. These results confirm theoreticalpredictions of the atmospheric greenhouse effect due to anthropogenicemissions, and provide empirical evidence of how rising CO2 levels, mediatedby temporal variations due to photosynthesis and respiration, are affecting thesurface energy balance.From Satellite Measurements:
[3] Kramer, R. J., He, H., Soden, B. J., Oreopoulos, L., Myhre, G., Forster, P. M., & Smith, C. J. (2021). Observational evidence of increasing global radiative forcing. Geophysical Research Letters, 48, e2020GL091585. https://doi.org/10.1029/2020GL091585
Changes in atmospheric composition, such as increasing greenhouse gases, cause an initial radiative imbalance to the climate system, quantified as the instantaneous radiative forcing. This fundamental metric has not been directly observed globally and previous estimates have come from models. In part, this is because current space-based instruments cannot distinguish the instantaneous radiative forcing from the climate’s radiative response. We apply radiative kernels to satellite observations to disentangle these components and find all-sky instantaneous radiative forcing has increased 0.53 ± 0.11 W/m2 from 2003 to 2018, accounting for positive trends in the total planetary radiative imbalance. This increase has been due to a combination of rising concentrations of well-mixed greenhouse gases and recent reductions in aerosol emissions. These results highlight distinct fingerprints of anthropogenic activity in Earth’s changing energy budget, which we find observations can detect within 4 years.
[4] Teixeira, J., Wilson, R. C., and Thrastarson, H. Th.: Direct observational evidence from space of the effect of CO2 increase on longwave spectral radiances: the unique role of high-spectral-resolution measurements, Atmos. Chem. Phys., 24, 6375–6383, https://doi.org/10.5194/acp-24-6375-2024, 2024.
NASA presentation here.
This new methodology can undoubtedly be refined and its uncertainties better characterized and understood to establish its accuracy and precision more clearly. But as far as the authors are aware, this study represents the first attempt to establish a more precise experimental confirmation from space of the direct effects of CO2 on longwave spectral radiances. The results (solely based on observations) confirm that the effects of the recent atmospheric CO2 increase on longwave spectral radiances follow theoretical estimates. As such, these results confirm a critical foundation of the science of global warming.From Quantum Mechanics:
[5] Wordsworth, R., Seeley, J. T., & Shine, K. P. (2024). Fermi Resonance and the Quantum Mechanical Basis of Global Warming. The Planetary Science Journal, 5(3), 67. DOI: 10.3847/PSJ/ad226d. https://iopscience.iop.org/article/10.3847/PSJ/ad226d/pdf
We have shown using mostly first-principles reasoning how the radiative forcing of CO2 emerges from the quantum mechanical properties of the CO2 molecule. This result has implications for our understanding of both contemporary global warming and the long-term evolution of Earth’s climate. There are, of course, many things that our analysis misses out. Many spectroscopic details, including anharmonic interactions, line mixing, and additional weak bands have been neglected, as have overlap with other gaseous absorbers and the radiative effects of clouds. In common with many other 1D calculations, atmospheric vertical temperature structure has been treated crudely, and 3D dynamics is neglected entirely. Given all this, it is remarkable that our analysis and others like it still allows a reasonably accurate estimate of clear-sky radiative forcing and climate sensitivity. This outcome provides further evidence, if such evidence were needed, of the rock-solid foundation of the physics of global warming and climate change.
II. CO2 Sensitivity
2.1. ECS: 2xCO2 Causes ~3 C Warming
The most thorough evaluation of equilibrium climate sensitivity (ECS) arrived at a likely range of 2.6°C to 4.1°C.[1] A meta-analysis from 2017 shows that the value of 3°C is also a central estimate in the peer-reviewed literature, agreeing with the values estimated by the IPCC. This is reinforced by estimates of cloud feedbacks that make low estimates for ECS less likely.[3] A recent analysis, however, found that the models that do the best job of predicting global warming and changes in EEI trends are on the higher end of this estimate, especially when looking at models with strong trends of increasing absorbed solar radiation and a strong temperature response to forcings.
The 66% range is 2.6–3.9 K for our Baseline calculation and remains within 2.3–4.5 K under the robustness tests; corresponding 5–95% ranges are 2.3–4.7 K, bounded by 2.0–5.7 K (although such high-confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent and because of greater confidence in understanding feedback processes and in combining evidence.
[2] Knutti, R., Rugenstein, M. & Hegerl, G. Beyond equilibrium climate sensitivity. Nature Geosci 10, 727–736 (2017). https://doi.org/10.1038/ngeo3017
When the individual PDFs of GCMs and palaeoclimate are, just for illustration (Fig. 5b), inflated in their lower and upper bounds to account for potential structural problems, state-dependent feedbacks and dependency across the linesof evidence, and in addition the mismatch between the historically inferred and future sensitivity4,59,60 is accounted for by extending the historical PDF upward (see Methods), the combined evidence from the three PDFs would still yield a rather narrow range, con-straining ECS to 2 °C to 4 °C with a most likely value near 3 °C.[3] Paulo Ceppi, Peer Nowack. Observational evidence that cloud feedback amplifies global warming. Proceedings of the National Academy of Sciences Jul 2021, 118 (30) e2026290118; DOI: 10.1073/pnas.2026290118 https://www.pnas.org/content/118/30/e2026290118
We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 0.35 Wm−2K−1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.
The trends in net EEl and surface warming trend over the first two decades of this century provide little constraint on climate sensitivity. However, we present robust findings for trends in LW and SW EEI. These trends, and their relationship to climate sensitivity, are more physically based than the net EEI trend. ... All models, given as the 99.999% level of the distribution, with an ECS of 2.93 K or below, are outside the CERES range.
2.2. ESS: 2xCO2 Causes ~6 C Warming
ECS only accounts for rapid feedbacks. On longer time scales, slower feedbacks like reductions in glacial ice and the poleward movement of boreal forests continue to add warming on millennial time scales. Generally speaking, Earth System Sensitivity (ESS) is estimated to be about 2x ECS, with some studies arriving at ~1.5x ECS.
Equation (4) gives the global mean temperature change expected for a stabilized future climate at 400 ppmv (about half the radiative forcing of a CO2 doubling from pre-industrial), with equilibrated ice sheets and vegetation. In this case, the ratio ESS/CS = 1.45, meaning that the Earth system sensitivity is about 45% greater than the equivalent Charney sensitivity.
A comparison of the new temperature reconstruction with radiative forcing from greenhouse gases estimates an Earth system sensitivity of 9 degrees Celsius (range 7 to 13 degrees Celsius, 95 per cent credible interval) change in global average surface temperature per doubling of atmospheric carbon dioxide over millennium timescales. This result suggests that stabilization at today’s greenhouse gas levels may already commit Earth to an eventual total warming of 5 degrees Celsius (range 3 to 7 degrees Celsius, 95 per cent credible interval) over the next few millennia as ice sheets, vegetation and atmospheric dust continue to respond to global warming.
[3] The Cenozoic CO2 Proxy Integration Project (CenCO2PIP) Consortium, Toward a Cenozoic history of atmospheric CO2. Science 382,eadi5177(2023). DOI:10.1126/science.adi5177. Accepted version online at: https://oro.open.ac.uk/94676/1/Accepted_manuscript_combinepdf.pdf
The Cenozoic compilation confirms a strong link between CO2 and GMST across timescales from 500 kyr to tens of Myr, with ESS[CO2] generally within the range of 5-8°C – patterns consistent with most prior work, and considerably higher than the present-day ECS of ~3°C. Both temperature reconstructions imply relatively high ESS[CO2] values during the last 10 Myr of the Cenozoic, when global ice volumes were highest. This agrees with expectations of an amplified ESS[CO2] due to the ice-albedo feedback. However, even during times with little-to-no ice (Paleocene to early Eocene), we find elevated values of ESS[CO2] (approaching or exceeding 5°C per CO2 doubling).[4] Emily J. Judd et al., A 485-million-year history of Earth’s surface temperature. Science 385,eadk3705 (2024).DOI:10.1126/science.adk3705
PhanDA provides a statistically robust estimate of GMST through the Phanerozoic. We find that Earth’s temperature has varied more dynamically than previously thought and that greenhouse climates were very warm. CO2 is the dominant driver of Phanerozoic climate, emphasizing the importance of this greenhouse gas in shaping Earth history. The consistency of apparent Earth system sensitivity (∼8°C) is surprising and deserves further investigation. More broadly, PhanDA provides critical context for the evolution of life on Earth, as well as present and future climate changes.
III. Answering Contrarian Misinformation
about the Greenhouse Effect
3.1. Studies Showing GMST Lags CO2 in Paleoclimate and in the Instrumental Record
Scientific evidence has been clear that, while warming in Antarctica is triggered by orbital forcings, CO2 increases at about the same time[2] as a feedback, and global warming follows this increase in CO2.[1] The lead-lag issue is also resolved with causative analysis.[3] There is evidence that natural cycles like ENSO affect variability in the rates at which CO2 increases, but the the overall increase in CO2 since 1850 comes from human activity. We know that CO2 leads GMST.[4][1] Shakun, J.D., Clark, P.U., He, F., Marcott, S.A., Mix, A.C., Liu, Z., Otto-Bliesner, B., Schmittner, A., and Bard, E.: Global warming preceded by increasing carbon dioxide concentrations during the last deglaciation, Nature, 484, 49–54, https://doi.org/10.1038/nature10915, 2012.
https://www.researchgate.net/publication/223987444_Global_Warming_Preceded_by_Increasing_Carbon_Dioxide_Concentrations_during_the_Last_Deglaciation
The covariation of carbon dioxide (CO2) concentration and temperature in Antarctic ice-core records suggests a close link between CO2 and climate during the Pleistocene ice ages. The role and relative importance of CO2 in producing these climate changes remains unclear, however, in part because the ice-core deuterium record reflects local rather than global temperature. Here we construct a record of global surface temperature from 80 proxy records and show that temperature is correlated with and generally lags CO2 during the last (that is, the most recent) deglaciation.[2] Parrenin, F. et al. “Synchronous Change of Atmospheric CO2 and Antarctic Temperature During the Last Deglacial Warming.” Science 339, 1060 (2013). DOI: 10.1126/science.1226368
https://pdfs.semanticscholar.org/d61d/0fbcb5828af1d434d1bd0282ed36e0f00d2a.pdf
Here we propose a revised relative age scale for the concentration of atmospheric CO2 and
Antarctic temperature for the last deglacial warming, using data from five Antarctic ice cores. We infer the phasing between CO2 concentration and Antarctic temperature at four times when their trends change abruptly. We find no significant asynchrony between them, indicating that Antarctic temperature did not begin to rise hundreds of years before the concentration of atmospheric CO2, as has been suggested by earlier studies.
[3] Stips, A., Macias, D., Coughlan, C. et al. On the causal structure between CO2 and global temperature. Sci Rep 6, 21691 (2016). https://www.nature.com/articles/srep21691
Further we apply this technique to analyse paleoclimatological air temperature (PAT)40 and CO2/CH4 data from the EPICA Dome C ice cores41,42 from the last 800,000 years. Both time series are interpolated on the same time steps of 1000 years using the AICC201243,44 chronology. As already known the two data set are highly correlated with a correlation coefficient of 0.842 ± 0. By calculating the IF in nat per unit time from the 1000 year interpolated PAT time series to CO2 concentration we get 0.123 ± 0.060 nat/ut and −0.054 ± 0.040 nat/ut in the reverse direction. Therefore we have on these long time scales a significant IF only from the temperature data to the CO2, but not in the other direction, exactly opposite to that seen in the data from the last 156 years. This result proves robust against using different ice age/gas age chronologies (SI, Tables SI-5 and SI-6 comparing EDC3 and AICC2012 chronology) and against using the recent corrected CO2 data from Bereiter45 (SI, Table SI-7). The time step chosen for interpolation influences neither the strong correlation (always around 0.88 for the EDC3 chronology) nor the significant causation (SI, Table SI-8). This supports the hypothesis that on geological time scales air temperature changes are causing the subsequent changes in CO2 concentration. This was already hypothesized by46, who claimed that CO2 lagged Antarctic deglacial warming by 800 ± 200 years, during a specific deglaciation event (Termination III ~ 240,000 years ago). Recently Parrenin et al.47, did not find any significant asynchrony in the timing between atmospheric CO2 and Antarctic temperature changes during the last deglaciation event (Termination TI). If we apply causality analysis only to data from event TI (22000–10000 years), we do get a bidirectional significant flow of 0.120 ± 0.074 nat/ut from PAT to CO2 and 0.484 ± 0.168 nat/ut from CO2 to PAT pointing to a synchronous behaviour or even a leading CO2 signal (see Table SI-9). Using the old EDC3 chronology would have given a very different result, with CO2 changes clearly causing PAT changes (Table SI-10). Because of the inherent nonlinear dynamics of the climate system, changes in correlation during single events could even be expected35. The causality analysis indicates that for the full 800,000 years time series PAT is indeed leading CO2 because of the significant IF from PAT to CO2. This is in principal agreement with the conclusion from Nes et al.48 that has been derived using convergent cross mapping. However, when interpolating to time steps longer than 3000 years the IF decreases (Table SI-8). Because of this it is not possible to specify a time lag of maximal IF in contrast to the 6000 year time lag found by Nes et al.48. Data from another strong greenhouse gas, namely methane CH4, are also available from EPICA Dome C covering the same time period as the CO2 data49. Again, as for CO2, we find a strong significant correlation between PAT and CH4 of 0.777. The IF from PAT to CH4 for the interpolated time series (1000 years time step) equals 0.393 ± 0.051 nat/ut and 0.007 ± 0.025 nat/ut in the reverse direction. Therefore the causal drive of temperature on the CH4 dynamics is even stronger than for CO2. This supports the expectation that on paleoclimatological time scales changing temperature could be held responsible for following changes in greenhouse gas (CO2/CH4) concentrations.[4] W. Wang, P. Ciais, R.R. Nemani, J.G. Canadell, S. Piao, S. Sitch, M.A. White, H. Hashimoto, C. Milesi, & R.B. Myneni, Variations in atmospheric CO2 growth rates coupled with tropical temperature, Proc. Natl. Acad. Sci. U.S.A. 110 (32) 13061-13066, https://doi.org/10.1073/pnas.1219683110 (2013).
3.2. Studies Showing all the Increase in CO2 above Preindustrial Levels come from Human Activity
There are at least five lines of independent evidence demonstrating that humans are responsible for virtually all the increase in atmospheric CO2 above preindustrial levels. In many ways, the issue is fully decided by evidence we about human carbon emissions since 1750. Estimates of our carbon emissions from fossil fuels and industry (FFI) and land use change (LUC) show that humans have added 720 GtC to the atmosphere, which is more carbon than was in the atmosphere in 1750 (~600 GtC or ~280 ppm). But atmospheric CO2 has only increased by 50% (~300 GtC or ~140 ppm). So human emissions have actually been large enough not only to be responsible for 100% of the increase in atmospheric CO2 but also to add ~420 GtC to the land and ocean sinks. I made a chart that summarizes this below (data from the 2024 Global Carbon Budget and CO2 concentrations from Mauna Loa and ice core data).
https://essd.copernicus.org/articles/17/965/2025/essd-17-965-2025.html
Total anthropogenic emissions (fossil and LULUCF, including the cement carbonation sink) were 11.1 GtC yr−1 (40.6 GtCO2 yr−1) in 2023, with a slightly higher preliminary estimate of 11.4 GtC yr−1 (41.6 GtCO2 yr−1) for 2024. Total anthropogenic emissions have been stable over the last decade (zero growth rate over the 2014–2023 period) and much slower than over the previous decade (2004–2013), with an average growth rate of 2.0 % yr−1.
[2] Rebecca Lindsay. Climate Change: Atmospheric Carbon Dioxide. https://www.climate.gov/news-features/understanding-climate/climate-change-atmospheric-carbon-dioxide
[3] Akira Tomizuka. Why Is Atmospheric Carbon Dioxide Concentration Higher in the Northern Hemisphere. Environmental Science 26.4 (2013): 374-387. www.jstage.jst.go.jp/article/sesj/26/4/26_374/_pdf
[4] Iris Crawford and Andrew Babbin. How will future warming and CO2 emissions affect oxygen concentrations? Ask MIT Climate. https://climate.mit.edu/ask-mit/how-will-future-warming-and-co2-emissions-affect-oxygen-concentrations
[3] Akira Tomizuka. Why Is Atmospheric Carbon Dioxide Concentration Higher in the Northern Hemisphere. Environmental Science 26.4 (2013): 374-387. www.jstage.jst.go.jp/article/sesj/26/4/26_374/_pdf
[4] Iris Crawford and Andrew Babbin. How will future warming and CO2 emissions affect oxygen concentrations? Ask MIT Climate. https://climate.mit.edu/ask-mit/how-will-future-warming-and-co2-emissions-affect-oxygen-concentrations
[5] Graven, H., Keeling, R. F., & Rogelj, J. (2020). Changes to carbon isotopes in atmospheric CO2 over the industrial era and into the future. Global Biogeochemical Cycles, 34, e2019GB006170. https://doi.org/10.1029/2019GB006170
Atmospheric observations of δ13CO2 have been used to investigate carbon fluxes and the functioning of plants, and they are used for comparison with δ13C in other materials such as tree rings. Atmospheric observations of Δ14CO2 have been used to quantify the rate of air-sea gas exchange and ocean circulation, and the rate of net primary production and the turnover time of carbon in plant material and soils. Atmospheric observations of Δ14CO2 are also used for comparison with Δ14C in other materials in many fields such as archaeology, forensics, and physiology. Another major application is the assessment of regional emissions of CO2 from fossil fuel combustion using Δ14CO2 observations and models. In the future, δ13CO2 and Δ14CO2 will continue to change. The sign and magnitude of the changes are mainly determined by global fossil fuel emissions.[6] Watson, A.J., Schuster, U., Shutler, J.D. et al. Revised estimates of ocean-atmosphere CO2 flux are consistent with ocean carbon inventory. Nat Commun 11, 4422 (2020). https://doi.org/10.1038/s41467-020-18203-3
Time-resolved estimates of global ocean-atmosphere CO2 flux provide an important constraint on the global carbon budget. However, previous estimates of this flux, derived from surface ocean CO2 concentrations, have not corrected the data for temperature gradients between the surface and sampling at a few meters depth, or for the effect of the cool ocean surface skin. Here we calculate a time history of ocean-atmosphere CO2 fluxes from 1992 to 2018, corrected for these effects. These increase the calculated net flux into the oceans by 0.8–0.9 PgC yr−1, at times doubling uncorrected values.
3.3. Studies Demonstrating that Solar Variability Does Not Explain Global Warming
There is a steady trickle of papers, mostly published in pay-to-play journals, that argue that the changes in Solar activity, or total solar irradiance (TS), is responsible for current warming. A good number of them are written by Willie Soon (and his friends at Ceres) or Zharkova. None of these papers are convincing, all are full of errors, and some have been retracted.
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[1] Benestad R. E. 2006 Solar Activity and Earth's Climate (Chichester: Springer/Praxis)
[2] Benestad, R. E. (2015). The debate about solar activity and climate change. Eathʼs Climate Response to a Changing Sun (Les Elis: EDP Sci.).
https://www.degruyter.com/document/doi/10.1051/978-2-7598-1849-5.c008/pdf?licenseType=open-access
[3] Benestad, R. E., and G. A. Schmidt (2009), Solar trends and global warming, J. Geophys. Res., 114, D14101, doi:10.1029/2008JD011639.
[4] Rasmus Benestad, "How large were the past changes in the sun?"
https://www.realclimate.org/index.php/archives/author/rasmus/
[5] Mark T. Richardson and Rasmus E. Benestad 2022 Res. Astron. Astrophys. 22 125008
https://iopscience.iop.org/article/10.1088/1674-4527/ac981c
[6] Kopp. "Historical Total Solar Irradiance Reconstruction, Time Series." https://lasp.colorado.edu/lisird/data/historical_tsi/
[7] Lean, J. L. (2018). Estimating solar irradiance since 850 CE. Earth and Space Science, 5, 133– 149. https://doi.org/10.1002/2017EA000357
[2] Benestad, R. E. (2015). The debate about solar activity and climate change. Eathʼs Climate Response to a Changing Sun (Les Elis: EDP Sci.).
https://www.degruyter.com/document/doi/10.1051/978-2-7598-1849-5.c008/pdf?licenseType=open-access
[3] Benestad, R. E., and G. A. Schmidt (2009), Solar trends and global warming, J. Geophys. Res., 114, D14101, doi:10.1029/2008JD011639.
[4] Rasmus Benestad, "How large were the past changes in the sun?"
https://www.realclimate.org/index.php/archives/author/rasmus/
[5] Mark T. Richardson and Rasmus E. Benestad 2022 Res. Astron. Astrophys. 22 125008
https://iopscience.iop.org/article/10.1088/1674-4527/ac981c
[6] Kopp. "Historical Total Solar Irradiance Reconstruction, Time Series." https://lasp.colorado.edu/lisird/data/historical_tsi/
[7] Lean, J. L. (2018). Estimating solar irradiance since 850 CE. Earth and Space Science, 5, 133– 149. https://doi.org/10.1002/2017EA000357
3.4. Studies Demonstrating that Cosmic Rays Do Not Explain Global Warming
There are some attempts at blaming the Sun via the seeding of clouds from cosmic rays. This was a serious hypothesis, and so it was taken seriously and extensively investigated. But there simply no evidence that this is having a significant impact on global temperatures.
[1] Agee, E. M., K. Kiefer, and E. Cornett, 2012: Relationship of Lower-Troposphere Cloud Cover and Cosmic Rays: An Updated Perspective. J. Climate, 25, 1057–1060, https://doi.org/10.1175/JCLI-D-11-00169.1.
https://www.pik-potsdam.de/en/news/latest-news/archive-news/2004-2005/pm_Shaviv_Veizer_e.html
[3] Rasmus E Benestad 2013 Environ. Res. Lett. 8 035049. DOI 10.1088/1748-9326/8/3/035049. https://iopscience.iop.org/article/10.1088/1748-9326/8/3/035049
[5] Erlykin, A.D., Sloan, T. & Wolfendale, A.W. A review of the relevance of the ‘CLOUD’ results and other recent observations to the possible effect of cosmic rays on the terrestrial climate. Meteorol Atmos Phys 121, 137–142 (2013). https://doi.org/10.1007/s00703-013-0260-x
[4] Eimear M. Dunne et al. ,Global atmospheric particle formation from CERN CLOUD measurements. Science354,1119-1124(2016). DOI:10.1126/science.aaf2649
[7] Laken, Benjamin A., Enric PallĂ©, JaÅ¡a ÄŒalogović and Eimear M. Dunne. A cosmic ray-climate link and cloud observations. J. Space Weather Space Clim., 2 (2012) A18. DOI: https://doi.org/10.1051/swsc/2012018
[8] Pierce, J. R., and P. J. Adams (2009), Can cosmic rays affect cloud condensation nuclei by altering new particle formation rates? Geophys. Res. Lett., 36, L09820, doi:10.1029/2009GL037946.
doi: 10.1130/1052-5173(2004)014<4:CAAPDO>2.0.CO;2.
https://www.geosociety.org/gsatoday/archive/14/3/pdf/i1052-5173-14-3-4.pdf
[11] Sloan, T and Wolfendale, A W. "Cosmic Rays and Global Warming." AIP Conference Proceedings, vol. 972, no. 1, Jan. 2008. https://doi.org/10.1063/1.2870330
[12] T. Sloan, A.W. Wolfendale, Cosmic rays and climate change over the past 1000 million years, New Astronomy, Volume 25, 2013, Pages 45-49, ISSN 1384-1076, https://doi.org/10.1016/j.newast.2013.03.008.
3.5 Studies Investigating the Tropospheric Hotspot
You sometimes see people saying that the since a tropospheric "hotspot" is not detected by satellite data, a major prediction of climate science regarding a fingerprint of greenhouse gas warming has not materialized. But as I've discussed in another post, much of the issue here has to do with uncertainties with satellite measurements, and the hotspot has been detected.
https://www.researchgate.net/publication/228630146_Warming_maximum_in_the_tropical_upper_troposphere_deduced_from_thermal_winds
[2] Steven C Sherwood and Nidhi Nishant (2015) Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data (IUKv2). Environ. Res. Lett. 10 054007.
https://iopscience.iop.org/article/10.1088/1748-9326/10/5/054007/meta
3.6 Reliability of Ice Core CO2
[1] Oeschger, Hans. (1995) Letters to the Editor. "Z. JAWOROWSKI: Ancient Atmosphere - Validity of Ice Records ESPR 1 (3): 161–171 (1994)." ESPR-Environ. Sci. & Pollut. Res. 2 (1): 60-61.
https://web.archive.org/web/20070927024724/http://www.scientificjournals.com/sj/espr/Pdf/aId/7394
[2] Alley RB. Reliability of ice-core science: historical insights. Journal of Glaciology. 2010;56(200):1095-1103. doi:10.3189/002214311796406130
https://www.cambridge.org/core/journals/journal-of-glaciology/article/reliability-of-icecore-science-historical-insights/92910C4F70F7D55B05484DADD5C45236
[3] Meijer, Harro A.J. Comment on 180 Years of Atmospheric CO2 Gas Analysis by Chemical Methods. Energy & Environment Vol. 18(2), 2007.
https://journals.sagepub.com/doi/10.1260/0958-305X.18.5.635
[4] Keeling, Ralph F. Comment on 180 Years of Atmospheric CO2 Gas Analysis by Chemical Methods. Energy & Environment Vol. 18(2), 2007.
[5] Steig. Sources of uncertainty in ice core data: A contribution to the Workshop on Reducing and Representing Uncertainties in High-Resolution Proxy Data. International Centre for Theoretical Physics, Trieste, Italy, June 9 - 11, 2008.
https://www.ncei.noaa.gov/pub/data/paleo/icecore/ice-cores.pdf
[6] Ahn J, Headly M, Wahlen M, Brook EJ, Mayewski PA, Taylor KC. CO2 diffusion in polar ice: observations from naturally formed CO2 spikes in the Siple Dome (Antarctica) ice core. Journal of Glaciology. 2008;54(187):685-695. doi:10.3189/002214308786570764
https://www.cambridge.org/core/journals/journal-of-glaciology/article/co2-diffusion-in-polar-ice-observations-from-naturally-formed-co2-spikes-in-the-siple-dome-antarctica-ice-core/8C8638D9EC90AEA53B90B3DE70E594C0
https://www.cambridge.org/core/journals/journal-of-glaciology/article/reliability-of-icecore-science-historical-insights/92910C4F70F7D55B05484DADD5C45236
[3] Meijer, Harro A.J. Comment on 180 Years of Atmospheric CO2 Gas Analysis by Chemical Methods. Energy & Environment Vol. 18(2), 2007.
https://journals.sagepub.com/doi/10.1260/0958-305X.18.5.635
[4] Keeling, Ralph F. Comment on 180 Years of Atmospheric CO2 Gas Analysis by Chemical Methods. Energy & Environment Vol. 18(2), 2007.
[5] Steig. Sources of uncertainty in ice core data: A contribution to the Workshop on Reducing and Representing Uncertainties in High-Resolution Proxy Data. International Centre for Theoretical Physics, Trieste, Italy, June 9 - 11, 2008.
https://www.ncei.noaa.gov/pub/data/paleo/icecore/ice-cores.pdf
[6] Ahn J, Headly M, Wahlen M, Brook EJ, Mayewski PA, Taylor KC. CO2 diffusion in polar ice: observations from naturally formed CO2 spikes in the Siple Dome (Antarctica) ice core. Journal of Glaciology. 2008;54(187):685-695. doi:10.3189/002214308786570764
https://www.cambridge.org/core/journals/journal-of-glaciology/article/co2-diffusion-in-polar-ice-observations-from-naturally-formed-co2-spikes-in-the-siple-dome-antarctica-ice-core/8C8638D9EC90AEA53B90B3DE70E594C0
3.7 The Iris Hypothesis
[1] Lin, B., B. A. Wielicki, L. H. Chambers, Y. Hu, and K. Xu, 2002: The Iris Hypothesis: A Negative or Positive Cloud Feedback?. J. Climate, 15, 3–7, https://doi.org/10.1175/1520-0442(2002)015<0003:TIHANO>2.0.CO;2.Using the Tropical Rainfall Measuring Mission (TRMM) satellite measurements over tropical oceans, this study evaluates the iris hypothesis recently proposed by Lindzen et al. that tropical upper-tropospheric anvils act as a strong negative feedback in the global climate system. The modeled radiative fluxes of Lindzen et al. are replaced by the Clouds and the Earth's Radiant Energy System (CERES) directly observed broadband radiation fields. The observations show that the clouds have much higher albedos and moderately larger longwave fluxes than those assumed by Lindzen et al. As a result, decreases in these clouds would cause a significant but weak positive feedback to the climate system, instead of providing a strong negative feedback.
[2] Paulo Ceppi, Peer Nowack. Observational evidence that cloud feedback amplifies global warming. Proceedings of the National Academy of Sciences Jul 2021, 118 (30) e2026290118; DOI: 10.1073/pnas.2026290118 https://www.pnas.org/content/118/30/e2026290118
We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 0.35 Wm−2K−1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.[3] Ito, M., & Masunaga, H. (2022). Process-level assessment of the iris effect over tropical oceans. Geophysical Research Letters, 49, e2022GL097997. https://doi.org/10.1029/2022GL097997
The iris hypothesis suggests a cloud feedback mechanism that a reduction in the tropical anvil cloud fraction (CF) in a warmer climate may act to mitigate the warming by enhanced outgoing longwave radiation. Two different physical processes, one involving precipitation efficiency and the other focusing on upper-tropospheric stability, have been argued in the literature to be responsible for the iris effect. In this study, A-Train observations and reanalysis data are analyzed to assess these two processes. Major findings are as follows: (a) the anvil CF changes evidently with upper-tropospheric stability as expected from the stability iris theory, (b) precipitation efficiency is unlikely to have control on the anvil CF but is related to mid- and low-level CFs, and (c) the day and nighttime cloud radiative effects are expected to largely cancel out when integrated over a diurnal cycle, suggesting a neutral cloud feedback.
[4] Lin Chambers and Bing Lin, "Test of the Iris Hypothesis Using Ceres SSF Data." https://ceres.larc.nasa.gov/documents/STM/2002-01/pdf/Lin%20ceres_rep_iris.pdf
3.8 Tree Ring Proxies and the Divergence Problem
[1] Taubes, G. (17 March 1995), "Is a Warmer Climate Wilting the Forests of the North?", Science, 267 (5204): 1595, Bibcode:1995Sci...267.1595T, doi:10.1126/science.267.5204.1595, PMID 17808119.
[2] Jacoby, G. C.; d'Arrigo, R. D. (June 1995), "Tree ring width and density evidence of climatic and potential forest change in Alaska", Global Biogeochemical Cycles, 9 (2): 227, Bibcode:1995GBioC...9..227J, doi:10.1029/95GB00321, The recent increase in temperatures combined with drier years may be changing the tree response to climate.
[3] Briffa, K.R.; Schweingruber, F.H.; Jones, P.D.; Osborn, T.J.; Harris, I.C.; Shiyatov, S.G.; Vaganov, E.A.; Grudd, H. (29 January 1998). "Trees tell of past climates: but are they speaking less clearly today?". Phil. Trans. R. Soc. Lond. B. 353 (1365): 65–73. doi:10.1098/rstb.1998.0191. PMC 1692171.
[4] Cook et al, “Extra-tropical Northern Hemisphere land temperature variability over the past 1000 years,” Quaternary Science Reviews 23 (2004) 2063–2074
https://www.ldeo.columbia.edu/res/fac/trl/downloads/Publications/%20cook2004.pdf
[5] D'Arrigo, Rosanne; Wilson, Rob; Liepert, Beate; Cherubini, Paolo (2008). "On the 'Divergence Problem' in Northern Forests: A review of the tree-ring evidence and possible causes" (PDF). Global and Planetary Change. Elsevier. 60 (3–4): 289–305. Bibcode:2008GPC....60..289D. doi:10.1016/j.gloplacha.2007.03.004. Archived from the original (PDF) on 2010-01-19.
[6] Folland, C. K., et al. (2001), Global temperature change and its uncertainties since 1861, Geophys. Res. Lett., 28, 2621–2624.
[7] Brohan, P., J. J. Kennedy, I. Harris, S. F. B. Tett, and P. D. Jones (2006), Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850, J. Geophys. Res., 111, D12106, doi:10.1029/2005JD006548.
[8] Wilson, R., D'Arrigo, R., Buckley, B., BĂ¼ntgen, U., Esper, J., Frank, D., Luckman, B., Payette, S., Vose, R., and Youngblut, D. (2007), A matter of divergence: Tracking recent warming at hemispheric scales using tree ring data, J. Geophys. Res., 112, D17103, doi:10.1029/2006JD008318.
[9] Trevor J. Porter, Michael F. J. Pisaric, Steven V. Kokelj & Thomas W. D. Edwards (2009) Climatic Signals in δ13C and δ18O of Tree-rings from White Spruce in the Mackenzie Delta Region, Northern Canada, Arctic, Antarctic, and Alpine Research, 41:4, 497-505, DOI: 10.1657/1938-4246-41.4.497
https://www.researchgate.net/publication/236271520_Climatic_Signals_in_dC_and_dO_of_Tree-rings_from_White_Spruce_in_the_Mackenzie_Delta_Region_Northern_Canada
[10] Rosanne D'Arrigo, Rob Wilson, Beate Liepert, Paolo Cherubini. On the ‘Divergence Problem’ in Northern Forests: A review of the tree-ring evidence and possible causes. Global and Planetary Change. Volume 60, Issues 3–4 (2008): Pages 289-305. https://doi.org/10.1016/j.gloplacha.2007.03.004.
https://www.sciencedirect.com/science/article/pii/S0921818107000495
[11] Brienen R.J.W.; Gloor E.; Zuidema P.A. (2012). "Detecting evidence for CO2 fertilization from tree ring studies: The potential role of sampling biases". Global Biogeochemical Cycles. 26: GB1025. Bibcode:2012GBioC..26B1025B. doi:10.1029/2011GB004143.
[12] Porter, T., Pisaric, M., Kokelj, S., & DeMontigny, P. (2013). A ring-width-based reconstruction of June–July minimum temperatures since AD 1245 from white spruce stands in the Mackenzie Delta region, northwestern Canada. Quaternary Research, 80(2), 167-179. doi:10.1016/j.yqres.2013.05.004
https://www.cambridge.org/core/journals/quaternary-research/article/abs/ringwidthbased-reconstruction-of-junejuly-minimum-temperatures-since-ad-1245-from-white-spruce-stands-in-the-mackenzie-delta-region-northwestern-canada/AC27937AA1172F81002B99594949CEC6
[13] Ulf BĂ¼ntgen, Alexander V. Kirdyanov, Paul J. Krusic, Vladimir V. Shishov, Jan Esper, Arctic aerosols and the ‘Divergence Problem’ in dendroclimatology, Dendrochronologia, Volume 67, 2021, 125837, ISSN 1125-7865, https://doi.org/10.1016/j.dendro.2021.125837.
[9] Trevor J. Porter, Michael F. J. Pisaric, Steven V. Kokelj & Thomas W. D. Edwards (2009) Climatic Signals in δ13C and δ18O of Tree-rings from White Spruce in the Mackenzie Delta Region, Northern Canada, Arctic, Antarctic, and Alpine Research, 41:4, 497-505, DOI: 10.1657/1938-4246-41.4.497
https://www.researchgate.net/publication/236271520_Climatic_Signals_in_dC_and_dO_of_Tree-rings_from_White_Spruce_in_the_Mackenzie_Delta_Region_Northern_Canada
[10] Rosanne D'Arrigo, Rob Wilson, Beate Liepert, Paolo Cherubini. On the ‘Divergence Problem’ in Northern Forests: A review of the tree-ring evidence and possible causes. Global and Planetary Change. Volume 60, Issues 3–4 (2008): Pages 289-305. https://doi.org/10.1016/j.gloplacha.2007.03.004.
https://www.sciencedirect.com/science/article/pii/S0921818107000495
https://www.cambridge.org/core/journals/quaternary-research/article/abs/ringwidthbased-reconstruction-of-junejuly-minimum-temperatures-since-ad-1245-from-white-spruce-stands-in-the-mackenzie-delta-region-northwestern-canada/AC27937AA1172F81002B99594949CEC6
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