Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

Abstract

Abstract. Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

An integrated approach to quantifying uncertainties in the remaining carbon budget

“…We note that we could equally have used a different emulator (e.g. MAGICC 20 ) for this purpose, though as shown in a recent intercomparison, there is little difference in the forcing distributions generated by different model emulators when driven by consistent forcings 65 .…”

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

“…HIRM could also be used with data generated by other SCMs. 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 (see Schwarber et al, 2019, for examples of different forcing to temperature IRFs).…”

“…The total radiative forcing in turn affects global temperature change, with all of Hector's radiative forcing agents exhibiting the same temperature response to change in radiative forcing. In effect, Hector can be considered to interpret forcing assumptions as effective radiative forcing values, which are more closely related to surface temperature changes than the previously used values for stratospheric-adjusted radiative forcing (Richardson et al, 2019;Smith et al, 2018b). This has no impact on the model dynamics that are our focus here and only impacts how numerical values are selected as input settings.…”

“…For example, this has been incorporated mechanistically for aerosols in the MAGICC model for around 30 years now (Wigley and Raper, 1992), and more recently inferred by Shindell (2014) from General Circulation Model results. Richardson et al (2019) used separate response functions for CO 2 , CH 4 , solar insolation, and aerosols, although the differences in these response functions were not discussed. As further information on speciesspecific IRFs become available it will be important to quantify the consequences of these different IRFs using tools such as HIRM.…”

Emulating ocean dynamic sea level by two-layer pattern scaling

“…We demonstrate this capability using SSP3-7.0, a CMIP6 scenario that has forcing intermediate between RCP4.5 and RCP8.5 (O'Neill et al, 2016) and is closer than either to nopolicy reference scenarios from most integrated assessment models (Riahi et al, 2017). The emission pathway of SSP3-7.0 used to drive the FaIR-2LM is taken from the Reduced Complexity Model Intercomparison Project (Nicholls et al 2020).…”