The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

Abstract

Abstract. Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Projection (CMIP6) that that will provide multi-model climate projections based on alternative scenarios of future emissions and land-use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP’s objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modelling, and impacts, adaptation and vulnerability communities, and will form an important part of the evidence base in the next IPCC assessment. At the same time, it will provide the basis for investigating a number of targeted scientific questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land-use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with climate model projections expected to be available within the 2018–2020 time frame.

C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6

“…They also align closely with simulations performed as part of ScenarioMIP (O'Neill et al, 2016) by quantifying the role of carbon cycle feedbacks in the evolution of atmospheric CO 2 due to anthropogenic carbon emissions. Synergies with other MIPs are discussed in Sect.…”

“…ScenarioMIP (O'Neill et al, 2016) acknowledges scientific and policy interest in a scenario with a substantial overshoot in radiative forcing during the 21st century. As such they include a tier-2 concentration-driven scenario called SSP5-3.4-OS: an overshoot pathway, which follows SSP5-8.5 up to 2040, followed by aggressive mitigation to reduce emissions to zero by about 2070, and by substantial negative global emissions thereafter.…”

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

“…This forcing is also used for the historical simulations of experiment A2. For forecasts which extend beyond the period for which historical forcing is specified, the "medium" SSP2-4.5 forcing of ScenarioMIP (O'Neill et al, 2016) is used. This forcing scenario is used for several other MIPs and is chosen since "land use and aerosol pathways are not extreme relative to other SSPs (and therefore appear as central for the concerns of DAMIP and DCPP), and also because it is relevant.…”

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): understanding sea ice through climate-model simulations

“…For example, in the Antarctic, the influence of biases in the mean state and trends of the atmosphere (Mahlstein et al, 2013;Haumann et al, 2014;Purich et al, 2016) and ocean (e.g. Armour and Bitz, 2015) simulations are thought to be the main cause for biases in the simulated sea-ice cover.…”

“…In combining our understanding of internal variability, the tuning of individual models, and the influence of atmospheric-and oceanic-mean state biases on the sea-ice simulation, we will be able to assess how much these factors can explain differences, both in the pre-industrial control simulation of individual models and across CMIP6 experiments, in particular the CMIP6 historical and ScenarioMIP (O'Neill et al, 2016) experiments that are of direct relevance to policy makers. We also request output from the CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) experiments abrupt-4×CO 2 and 1pctCO2 as described by Eyring et al (2016), as these allow direct insights into the equilibrium and transient sensitivity of sea ice to changes in the external forcing.…”