Impact of the AR6 Updates to the Assessment of Effective Radiative Forcing on the Projections of Reduced Complexity Climate Models

While General Circulation models (GCMs) provide detailed forecasts on global warming, they are computationally expensive. Reduced complexity climate models (RCMs) allow for much more computationally efficient simulations. Many RCMs utilize inputs that originate from various sources like previous GCM outputs, the SSP Database, or the annexes of the Sixth IPCC Assessment report (AR6). The AR6 report provided updates to the formulation of effective radiative forcing (ERF) for most greenhouse gases (GHGs) and tropospheric aerosols used in climate model projections, relative to values in AR5. Additionally, projected time series for the abundance of Greenhouse Gases (GHGs) for various Shared Socioeconomic Pathway (SSP) scenarios have also received an update by AR6, compared to prior data in the SSP database. In this work, we provide a comprehensive assessment of the impacts of the AR6 report to the above datasets, using our RCM, the Empirical Model of the Global Climate (EM-GC). We quantify the likelihood of limiting the rise in global mean surface temperature (GMST) to either the target (1.5 ⁰C) and upper limit (2.0 ⁰C) of the Paris Climate Agreement (PCA). A special emphasis is also put on providing projections using various datasets and estimates for the ERF of tropospheric aerosols published after the release of the AR6 report. Using the updated datasets result in a considerable increase in the projected rise in global mean surface temperature compared to simulations using input data from the SSP database. We find that the probability of achieving either the target (1.5 ⁰C) and upper limit (2.0 ⁰C) of the PCA decreases substantially upon the adoption of the AR6 framework due to the combined effect of the reassessment of the ERF for GHGs and for tropospheric aerosols. Additionally, we show that human activity is responsible for a larger increase in GMST, than had been previously quantified, based upon older assessments of the ERF for GHGs and tropospheric aerosols. Nonetheless, even using the updated AR6 datasets, we forecast a substantially smaller future rise in GMST than was estimated by most of the GCMs that participated in CMIP6. This finding agrees with the conclusions of several other studies that find an overly rapid warming in CMIP6 GCMs compared to warming forecasted using a variety of empirical approaches.