Observational constraints on the effective climate sensitivity from the historical period

Abstract

The observed warming in the atmosphere and ocean can be used to estimate the climate sensitivity linked to present-day feedbacks, which is referred to as the effective climate sensitivity (S hist ). However, such an estimate is affected by uncertainty in the radiative forcing, particularly aerosols, over the historical period. Here, we make use of detection and attribution techniques to derive the surface air temperature and ocean warming that can be attributed directly to greenhouse gas increases. These serve as inputs to a simple energy budget to infer the likelihood of S hist in response to observed greenhouse gases increases over two time periods (1862-2012 and 1955-2012). The benefit of using greenhouse gas attributable quantities is that they are not subject to uncertainties in the aerosol forcing (other than uncertainty in the attribution to greenhouse gas versus aerosol forcing not captured by the multi-model aerosol response pattern). The resulting effective climate sensitivity estimate, S hist , ranges from 1.3°C to 3.1°C (5%-95% range) over the full instrumental period (1862-2012) for our best estimate, and gets slightly wider when considering further uncertainties. This estimate increases to 1.7°C-4.6°C if using the shorter period . We also evaluate the climate model simulated surface air temperature and ocean heat content increase in response to greenhouse gas forcing over the same periods, and compare them with the observationally-constrained values. We find that that the ocean warming simulated in greenhouse gas only simulations in models considered here is consistent with that attributed to greenhouse gas increases from observations, while one model simulates more greenhouse gas-induced surface air warming than observed. However, other models with sensitivity outside our range show greenhouse gas warming that is consistent with that attributed in observations, emphasising that feedbacks during the historical period may differ from the feedbacks at CO 2 doubling and from those at true equilibrium.

Bayesian estimation of Earth’s climate sensitivity and transient climate response from observational warming and heat content datasets

“…Many studies have combined reconstructions of surface temperature and ocean heat uptake with estimates of radiative forcing to calculate the effective climate feedback during the historic period (e.g. Annan, 2015;Anan and Hargreaves, 2020;Bodman and Jones, 2016;Lewis and Curry, 2014;Skeie et al, 2018;Otto et al, 2013;Tokarska et al, 2020). However, climate feedback strengths evolve over time in complex climate models (e.g.…”

“…(2), have either calculated a single constant climate sensitivity (see Annan, 2015;Anan and Hargreaves, 2020;Bodman and Jones, 2016;Lewis and Curry, 2014;Sherwood et al, 2020;Skeie et al, 2018;Otto et al, 2013), or have evaluated ECS for specific historic periods (e.g. Tokarska et al, 2020), acknowledging that the value for the specific historical period may not apply for all timescales into the future.…”

Comparison of CMIP6 historical climate simulations and future projected warming to an empirical model of global climate

“…Upon our use of blended CMIP6 temperature output for these GCMs and calculation of AAWR for 1975-2014, we find that AAWR based on blended CMIP6 temperature is 3.5 % lower than AAWR found when using only TAS. Tokarska et al (2020b) estimate an effect of 0.013 • C per decade in the trend of CMIP6 temperature output upon the use of blended CMIP6 temperature instead of TAS, while Cowtan et al (2015) report a difference of 0.030 • C per decade between the trend in observations and modeled output. Since the difference between values of AAWR found using blended CMIP6 temperature output and TAS is so small and does not affect any of our conclusions, we use TAS output from the CMIP6 multi-model archive because this choice allows many more GCMs to be examined.…”

An Assessment of Earth's Climate Sensitivity Using Multiple Lines of Evidence

“…We address this question by first comparing the above results to an estimate based on the portion of the observed surface and ocean warming that has been attributed to increasing GHGs (Tokarska, Schurer, et al, 2020): ΔT ghg , ΔF ghg , and ΔN ghg . Attribution makes use of the time-space pattern of warming to disentangle the effects of other forcings, particularly aerosols, from those of GHGs and then applies the same energy budget (Equation 20) as above, but uses attributed warming and greenhouse-gas-only forcing changes.…”

“…Illustration of probability density functions from alternative, published approaches (as labeled). Tokarska, Schurer, et al (2020) rely on an energy budget approach using the observed warming and ocean heat uptake attributed to greenhouse warming and is most directly comparable to our main approach. The solid line relies on a flat prior in S, the dashed line is directly sampled (see text; similar to green line in Figure 11), and the dotted line is the same as the solid line, but based on doubled variance of climate variability when deriving the attributed warming estimates.…”