Quantifying Cloud Feedbacks for Climate Sensitivity


One of the more challenging aspects of climate science today is quantifying the cloud feedbacks to better constrain estimates for equilibrium climate sensitivity (ECS). It’s long been understood that low clouds generally have a cooling influence, while higher clouds increase warming via the greenhouse effect. Previous attempts at quantifying the net feedback have produced results where the confidence interval is larger than the estimate. For instance, Andrew Dessler’s estimates[1][2] were +0.50 ± 0.75 W/m^2/K over a 10 year period. Zhou’s estimate[3] was −0.16 ±0.83 W/m^2/K. Attempts at simulating clouds in some of the CMIP6 models have produced ECS values that are likely too high,[4] though many of these issues have since been largely resolved.[5][6][7].

A new study,[8] however, has succeeded at quantifying these cloud feedbacks at 0.43 ± 0.35 W/m^2/K. This means that for every 1 C warming, we can expect an additional 0.43 W/m^2, amplifying warming. Given these results, there is just a 2.5% chance that the net cloud feedback has a negative sign. These findings also help constrain values for ECS. “Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W⋅m−2⋅K−1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K.” The paper is currently behind a paywall, but you can read a summary of it on CarbonBrief.[9]

Figure 4B from the Paper

The observational constraints also reduces the uncertainty for ECS with respect to AR5's assessment, and assesses ECS to be 3.2, though the 1σ and 2σ confidence intervals are larger above the mean than below it. "The observational constraint translates into a probability distribution for ECS... with central value 3.2 K and CIs 2.6 to 4.2 K (17 to 83%; Fig. 4B, blue bar) and 2.3 to 5.2 K (5 to 95%). The former is considerably (49%) narrower than the IPCC AR5 likely (17 to 83%) range of 1.5 to 4.5 K and agrees well with the slightly narrower 66% ECS range proposed by the WCRP assessment (2.6 to 3.9 K), which accounts for multiple lines of evidence and expert judgment, rather than being based solely on cloud radiative observations."


References:

[1] Dessler, A. E. (2010), A determination of the cloud feedback from climate variations over the past decade, Science, 330, 1523– 1527, doi:10.1126/science.1192546.

[2] Dessler, A. E., and Loeb, N. G. (2013), Impact of dataset choice on calculations of the short‐term cloud feedback, J. Geophys. Res. Atmos., 118, 2821– 2826, doi:10.1002/jgrd.50199.

[3] Zhou, C., M. D. Zelinka, A. E. Dessler, and P. Yang, 2013: An Analysis of the Short-Term Cloud Feedback Using MODIS Data. J. Climate, 26, 4803–4815, https://doi.org/10.1175/JCLI-D-12-00547.1.

[4] Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M., Ceppi, P., et al. (2020). Causes of higher climate sensitivity in CMIP6 models. Geophysical Research Letters, 47, e2019GL085782. https://doi.org/10.1029/2019GL085782
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL085782

[5] Myers, T.A., Scott, R.C., Zelinka, M.D. et al. Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity. Nat. Clim. Chang. 11, 501–507 (2021). https://doi.org/10.1038/s41558-021-01039-0

[6] MĂ¼lmenstädt, J., Salzmann, M., Kay, J.E. et al. An underestimated negative cloud feedback from cloud lifetime changes. Nat. Clim. Chang. 11, 508–513 (2021). https://doi.org/10.1038/s41558-021-01038-1

[7] Stephens, G.L. The cooling of light rains in a warming world. Nat. Clim. Chang. 11, 468–470 (2021). https://doi.org/10.1038/s41558-021-01056-z

[8] 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

[9] Ayesha Tandon.Clouds study finds that low climate sensitivity is ‘extremely unlikely.’ CarbonBrief. July 21 2021. https://www.carbonbrief.org/clouds-study-finds-that-low-climate-sensitivity-is-extremely-unlikely?fbclid=IwAR225L6aKkDv4IVx-U6-t1qQeHJ01yEkF5NwAMULkJM_N51qugi9clbplSc


Comments

Post a Comment

Popular posts from this blog

The Marketing of Alt-Data at Temperature.Global

Image
Temperature.Global (12-month running average, sort of) A few years ago, I started seeing people post links to a new dataset for global temperatures at a website called temperature.global. There are at least four unique features of this dataset. First, the website claims to update global temperature in near real time. Second, every year in the dataset averages below "normal." Third, there is absolutely no transparency regarding their methodology (those who administer it are anonymous, most of the data is hidden, and much of their methodology is unclear). And fourth, what is disclosed about their methodology reveals that what they are calculating is not the Earth's surface temperature. Description of Temperature.Global If you go to the temperature.global website, it becomes almost immediately apparent that this website has little concern for transparency. The website is hosted by Parler (the alternative social network), which if nothing else is pretty odd. There are no name
Read more

Roy Spencer on Models and Observations

Image
A few days ago, Dr. Roy Spencer wrote a piece for the Heritage Foundation called, " Global Warming: Observations vs. Climate Models " ( PDF ) essentially arguing that models show too much warming compared to observations, and if we stick to observations, "global warming offers no justification for carbon-based regulation." He claims to frame his argument in terms of answering three questions: Is recent warming of the climate system materially attributable to anthropogenic greenhouse gas emissions, as is usually claimed? Is the rate of observed warming close to what computer climate models—used to guide public policy—show? Has the observed rate of warming been sufficient to justify alarm and extensive regulation of CO2 emissions? We should keep in mind that this is a political document intended to support the political aims of the Heritage Foundation, and Spencer has carefully selected what he says and doesn't say to fit the political agenda of the Heritage Found
Read more

Patrick Frank Publishes on Errors Again

Image
Recently I came across yet another paper by Patrick Frank[1] attempting to claim that climate scientists have been underestimating uncertainties in climate-related data. In this paper, he takes aim at GMST data, and he argues that  LiG resolution limits, non-linearity, and sensor field calibrations yield GSATA mean ±2σ RMS uncertainties of, 1900–1945, ±1.7 °C; 1946–1980, ±2.1 °C; 1981–2004, ±2.0 °C; and 2005–2010, ±1.6 °C. Finally, the 20th century (1900–1999) GSATA, 0.74 ± 1.94 °C, does not convey any information about rate or magnitude of temperature change. The resulting GMST graph from his calculations is below. Essentially, he's saying that errors associated with liquid in glass thermometers are so large that we can have no confidence in the global warming trend in the major GMST datasets. Of course, the organizations producing these GMST datasets all evaluate the uncertainties associated with their anomaly values, and their estimates are invariably much smaller - about ±0.05°
Read more