Reduced complexity model intercomparison project phase 1: Protocol, results and initial observations

Abstract

Abstract. Here we present results from the first phase of the Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination of reduced complexity climate models (RCMs), which are used to complement and extend the insights from more complex Earth System Models (ESMs), in particular those participating in the Sixth Coupled Model Intercomparison Project (CMIP6). In Phase 1 of RCMIP, with 14 participating models namely ACC2, AR5IR (2 and 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR and WASP, we highlight the structural differences across various RCMs and show that RCMs are capable of reproducing global-mean surface air temperature (GSAT) changes of ESMs and historical observations. We find that some RCMs are capable of emulating the GSAT response of CMIP6 models to within a root-mean square error of 0.2 °C (of the same order of magnitude as ESM internal variability) over a range of scenarios. Running the same model configurations for both RCP and SSP scenarios, we see that the SSPs exhibit higher effective radiative forcing throughout the second half of the 21st Century. Comparing our results to the difference between CMIP5 and CMIP6 output, we find that the change in scenario explains approximately 46 % of the increase in higher end projected warming between CMIP5 and CMIP6. This suggests that changes in ESMs from CMIP5 to CMIP6 explain the rest of the increase, hence the higher climate sensitivities of available CMIP6 models may not be having as large an impact on GSAT projections as first anticipated. A second phase of RCMIP will complement RCMIP Phase 1 by exploring probabilistic results and emulation in more depth to provide results available for the IPCC's Sixth Assessment Report author teams.

Diagnosing Transient Response to CO2 Forcing in Coupled Atmosphere‐Ocean Model Experiments Using a Climate Model Emulator

“…Besides the core CMIP6 experiments used in this study, associated model intercomparison projects have been conducting a variety of long‐term experiments forced with idealized CO 2 changes (Jones et al, ; Keller et al, ; Webb et al, ). Emulating those results and comparing different methods (Nicholls et al, ) will clarify the range of acceptable use.…”

HIRM v1.0: A hybrid impulse response model for climate modeling and uncertainty analyses

“…This could be a useful way of decomposing differences in responses between SCMs (e.g. Nicholls et al 2020) into differences in the emissions to forcing step compared to differences in the model's response to a forcing impulse. Similarly, HIRM could be used to examine the uncertainty due to the different forcing to temperature responses amongst SCMs.…”

Silicone v1.0.0: an open-source Python package for inferring missing emissions data for climate change research

“…Silicone provides an alternative means of complementing such results by infilling using scenarios with similarities to the desired narrative, removing the need for more numerical free parameters between formulae. A notebook can be found in the silicone examples github detailing the calculations and demonstrating this usage, titled "Infill_stylised_path.ipynb" (Lamboll, 2020), using data from (Nicholls, Meinshausen, et al, 2020). It shows that curves with different values in some of the parameters, termed ∞ and , can be complemented using a number of techniques.…”