How well do integrated assessment models represent non-CO2 radiative forcing?

Abstract

This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-CO 2 gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/m 2 in 2100) in non-CO 2 forcing projections for a 2.6 W/ Climatic Change (2015) How well do integrated assessment models represent non-CO 2 radiative forcing? m 2 mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required CO 2 forcing targets and policy costs.

The role of methane in future climate strategies: mitigation potentials and climate impacts

“…The climate parameters have been assessed using the same climate model for all the models and scenarios: MAGICC6 (Meinshausen et al, 2011), to ensure consistency in the climate-related results. In terms of its CH 4 forcing projections, this simple climate model fits well within the range of projections of complex climate models it emulates (Harmsen et al, 2015). The scenarios are compared to provide insight in the following:…”

Evaluating climate emulation: fundamental impulse testing of simple climate models

“…For the purposes of summarizing our results we compare the individual model responses to the comprehensive SCM multi-model mean for most of our experiments. We use this both for convenience and because the comprehensive SCMs can generally replicate the long-term results of general circulation models (GCMs; Meinshausen et al, 2011;Joos et al, 2013;Hartin et al, 2015Hartin et al, , 2016. This is also, in a general philosophical sense, in line with the finding from GCMs that multi-model means compare better to observations than individual models (Flato et al, 2013), although we note that the Flato et al (2013) finding was not specifically for global temperature.…”

“…Three comprehensive SCMs -Hector v2.0 (Kriegler, 2005;Hartin et al, 2015), MAGICC 5.3 BC-OC (Raper et al, 1996;Wigley and Raper, 2002;Smith and Bond, 2014), and MAGICC 6.0 (Meinshausen et al, 2011) -are used in this study (Sect. S2).…”

“…SCMs have less detailed representations than ESMs and themselves range in structure from idealized to more comprehensive climate representa-tions (Millar et al, 2017). Comprehensive SCMs are models rooted in physical processes (e.g., energy balance models) and capture the main pathway by which climate forcers alter the energy budget: emissions to concentrations, top-ofthe-atmosphere radiative forcing, and global mean surface air temperature (Geoffroy et al, 2013;Hartin et al, 2015;Meinshausen et al, 2011;Tanaka et al, 2007). Idealized SCMs use even fewer equations, which do not necessarily correspond to specific physical processes, to parametrically represent the climate system (Millar et al, 2017).…”

“…SCMs are widely used in scientific and decision-making contexts largely because of their advantageous features, in-cluding their ease of use, transparency, and low computational intensiveness. In particular, SCMs are traditionally used within human-Earth system models that couple the climate system with representations of dynamics within the human system (e.g., energy systems and land-use changes) (Hartin et al, 2015;Ortiz and Markandya, 2009;Schneider and Thompson, 2000;Strassmann and Joos, 2018) and are used to assess global forcing or temperature targets (e.g., Representative Concentration Pathways;van Vuuren et al, 2011b, Shared Socioeconomic Pathways;Moss et al, 2010). Several studies investigated potential sources of human-Earth system model uncertainty by exploring the climate components driving the models (Calel and Stainforth, 2017;Harmsen et al, 2015;van Vuuren et al, 2008van Vuuren et al, , 2011a.…”