Since we have been periodically posting updates (e.g. 2009, 2010, 2011, 2012, 2015, 2016 etc.) of model output comparisons to observations across a range of variables, we have now set up this page as a permanent placeholder for the most up-to-date comparisons. We include surface temperature projections from 1981, 1988, CMIP3, CMIP5, and CMIP6, and MSU satellite products from CMIP5, and we will update this on an annual basis, or as new observational products become available. For each comparison, we note the last update date, and where the comparison was first discussed.
Global mean surface temperature anomalies
Hansen et al (1981)
Hansen et al (1988)
Original discussion (2007), Last discussion (2018). Scenarios from Hansen et al. (1988). Observations are the GISTEMP LOTI annual figures. Trends from 1984: GISTEMP: 0.20ºC/dec, Scenarios A, B, C: 0.34, 0.28, 0.15ºC/dec respectively (all 95% CI ~±0.02 or 0.03). Last updated: 16 Jan 2023.
CMIP3 (circa 2004)
Last discussion (2015). Model spread is the 95% envelope of global mean surface temperature anomalies from all individual CMIP3 simulations (using the SRES A1B projection post-2000). Observations are the standard quasi-global estimates of anomalies with no adjustment for spatial coverage or the use of SST instead of SAT over the open ocean. Last updated: 16 Jan 2023.
CMIP5 (circa 2011)
Last discussion (2015). Model spread is the 95% envelope of true global mean surface temperature anomalies from all CMIP5 historical simulations (using the RCP4.5 projection post-2005). Forcing adjustment is updated from Schmidt et al. (2014). Observations are the standard quasi-global estimates of anomalies with no adjustment for spatial coverage or the use of SST instead of SAT over the open ocean. Last updated: 16 Jan 2023.
As above, but using the blended SST/SAT product from the CMIP5 models produced by Cowtan et al (2015) instead of the pure SAT field. Note that this makes about a 0.05ºC difference in 2022 (compared to a 0.1ºC difference estimated from the forcings adjustment above). Last updated: 17 Jan 2023.
CMIP6 (circa 2021)
The latest phase of CMIP has been ongoing since around 2019, and now has sufficient models to provide a basis for projections going forward. These models used observed boundary conditions (GHG levels, deforestation, solar, volcanoes etc.) up to 2014, and projections based on the Shared Socioeconomic Pathways (SSPs) from 2015 onwards. The same caveat with respect to the comparison to the blended SAT/SST observations stands as with CMIP5, but this is a relatively small effect (i.e. it’s expected to be around 0.05ºC in 2022). Note however, that some CMIP6 models have climate sensitivities outside both the CMIP5 range and the range constrained by observations. Thus in these figures, we plot the full mean (1 ensemble member per model) and the mean of a subset of the models that have a transient climate response (TCR) within the likely constrained range [1.4,2.2]ºC as assessed by IPCC AR6 (Hausfather et al., 2022).
Model spread is the 95% envelope of surface air temperature anomalies using 37 model simulations from the historical runs and SSP2-4.5. TCR values used in the screen are Hausfather et al. (2022). Last updated: 20 Jan 2023.
Satellite-derived atmospheric temperatures
TMT (global and tropical means) (timeseries and trends)
Original discussion (Jan 2017). Mid-troposphere satellite products from UAH, RSS, NOAA STAR (v3, v4.1 and v5) and UW (Po-Chedley et al, tropical values only). Model values use synthetic MSU/AMSU-TMT weightings, spread is 95% envelope of simulations. Last updated: 2 Feb 2023.
If you have suggestions for additional comparisons, stylistic changes, clarifications etc., please leave a comment on the latest open thread. You can use these figures anywhere (with citation and link back to RealClimate).
- Z. Hausfather, H.F. Drake, T. Abbott, and G.A. Schmidt, "Evaluating the Performance of Past Climate Model Projections", Geophysical Research Letters, vol. 47, 2020. http://dx.doi.org/10.1029/2019GL085378
- J. Hansen, D. Johnson, A. Lacis, S. Lebedeff, P. Lee, D. Rind, and G. Russell, "Climate Impact of Increasing Atmospheric Carbon Dioxide", Science, vol. 213, pp. 957-966, 1981. http://dx.doi.org/10.1126/science.213.4511.957
- J. Hansen, I. Fung, A. Lacis, D. Rind, S. Lebedeff, R. Ruedy, G. Russell, and P. Stone, "Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model", Journal of Geophysical Research, vol. 93, pp. 9341, 1988. http://dx.doi.org/10.1029/JD093iD08p09341
- G.A. Schmidt, D.T. Shindell, and K. Tsigaridis, "Reconciling warming trends", Nature Geoscience, vol. 7, pp. 158-160, 2014. http://dx.doi.org/10.1038/ngeo2105
- K. Cowtan, Z. Hausfather, E. Hawkins, P. Jacobs, M.E. Mann, S.K. Miller, B.A. Steinman, M.B. Stolpe, and R.G. Way, "Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures", Geophysical Research Letters, vol. 42, pp. 6526-6534, 2015. http://dx.doi.org/10.1002/2015GL064888
- Z. Hausfather, K. Marvel, G.A. Schmidt, J.W. Nielsen-Gammon, and M. Zelinka, "Climate simulations: recognize the ‘hot model’ problem", Nature, vol. 605, pp. 26-29, 2022. http://dx.doi.org/10.1038/d41586-022-01192-2