Comparison of CMIP6 Historical Climate Simulations and Future Projected Warming to an Empirical Model of Global Climate

Abstract

Abstract. The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is the latest modeling effort for general circulation models to simulate and project various aspects of climate change. Many of the general circulation models (GCMs) participating in CMIP6 provide archived output that can be used to calculate equilibrium climate sensitivity (ECS) and forecast future temperature change based on emissions scenarios from several Shared Socioeconomic Pathways (SSPs). Here we use our multiple linear regression energy balance model, the Empirical Model of Global Climate (EM-GC), to simulate and project changes in global mean surface temperature (GMST), calculate ECS, and compare to results from the CMIP6 multi-model ensemble. An important aspect of our study is comprehensive analysis of uncertainties due to radiative forcing of climate from tropospheric aerosols (AER RF) in the EM-GC framework. We quantify the attributable anthropogenic warming rate (AAWR) from the climate record using the EM-GC and use AAWR as a metric to determine how well CMIP6 GCMs replicate human-driven global warming over the last forty years. The CMIP6 multi-model ensemble indicates a median value of AAWR over 1975–2014 of 0.217 °C/decade (range of 0.150 to 0.294 °C/decade; all ranges given here are for 5th and 95th confidence intervals), which is notably faster warming than our best estimate for AAWR of 0.135 °C/decade (range of 0.097 to 0.195 °C/decade) inferred from analysis of the Hadley Center Climatic Research Unit data record for GMST. Estimates of ECS found using the EM-GC (best estimate 2.01 °C; range of 1.12 to 4.12 °C) are generally consistent with the range of ECS of 1.5 to 4.5 °C given by IPCC's Fifth Assessment Report. The CMIP6 multi-model ensemble exhibits considerably larger values of ECS (median 3.74 °C; range of 2.19–5.65 °C). The dominant factor in the uncertainty for our empirical determinations of AAWR and ECS is imprecise knowledge of AER RF for the contemporary atmosphere. We calculate the likelihood of achieving the Paris Agreement target (1.5 °C) and upper limit (2.0 °C) of global warming relative to pre-industrial for seven of the SSPs using both the EM-GC and the CMIP6 multi-model ensemble. In our model framework, SSP1-2.6 is the 1.5 °C pathway with a 64.8 % probability of limiting warming at this level by the end of century and SSP4-3.4 is the 2.0 °C pathway, with a 74.0 % probability of achieving the Paris upper limit. In addition, we quantify the sensitivity of future warming to the curbing of the current rapid growth of atmospheric methane and show major near-term limits on the future growth of methane are especially important for achievement of the 1.5 °C goal of future warming. Finally, we assess warming projections in terms of future anthropogenic emissions of atmospheric carbon. In our model framework, humans can emit only another 268 Gt C after 2019 to have a 66 % likelihood of limiting warming to 1.5 °C, and another 565 Gt C to have the same probability of limiting warming to 2.0 °C. Given the current emission of 11.7 Gt C per year due to combustion of fossil fuels and deforestation, our EM-GC simulations suggest the 1.5 °C warming target of the Paris Agreement will not be achieved unless carbon and methane emissions are severely curtailed in the next two decades.

Evaluation of CMIP6 GCMs Over the CONUS for Downscaling Studies

“…A lack of in‐depth evaluation of GCMs in studies with a limited number of evaluation measures runs the risk of errors in their ranking in the CMIP ensemble. A model can yield reasonable climatological distribution of desired fields over a region while poorly simulating key Earth system processes (e.g., Beobide‐Arsuaga et al., 2021; McBride et al., 2021; Mckenna et al., 2020). Alternatively, high covariance among the extensive suite of evaluation metrics used to investigate the skillfulness of models can also influence the GCM ranking process.…”

Impact of Meteorological factors on wheat growth period and irrigation water requirement —A case study of the Beijing-Tianjin-Hebei region in China

“…The global climate change since the past 132 years (1880-2012) was also elaborated. Moreover, the IPCC 2013 report predicts the trend of climate change at the end of the 21st century through a variety of scenario models: Temperature rise varies regionally, and it will be higher on the land than the sea by 1.4-1.7 °C, with the Arctic recording the highest temperature (McBride et al, 2020). Extreme hot weather events will increase, and the duration will be lengthened in most areas, and extreme cold weather events will decrease.…”