Country-resolved combined emission and socio-economic pathways based on the Representative Concentration Pathway (RCP) and Shared Socio-Economic Pathway (SSP) scenarios

Abstract

Abstract. Climate policy analysis needs reference scenarios to assess emission targets and current trends. When presenting their national climate policies, countries often showcase their target trajectories against fictitious so-called baselines. These counterfactual scenarios are meant to present future greenhouse gas (GHG) emissions in the absence of climate policy. These so-called baselines presented by countries are often of limited use, as they can be exaggerated and as the methodology used to derive them is usually not transparent. Scenarios created by independent modeling groups using integrated assessment models (IAMs) can provide different interpretations of several socio-economic storylines and can provide a more realistic backdrop against which the projected target emission trajectory can be assessed. However, the IAMs are limited in regional resolution. This resolution is further reduced in intercomparison studies, as data for a common set of regions are produced by aggregating the underlying smaller regions. Thus, the data are not readily available for country-specific policy analysis. This gap is closed by downscaling regional IAM scenarios to the country level. The last of such efforts has been performed for the SRES (“Special Report on Emissions Scenarios”) scenarios, which are over a decade old by now. CMIP6 (Coupled Model Intercomparison Project phase 6) scenarios have been downscaled to a grid; however they cover only a few combinations of forcing levels and SSP storylines with only a single model per combination. Here, we provide up-to-date country scenarios, downscaled from the full RCP (Representative Concentration Pathway) and SSP (Shared Socio-Economic Pathway) scenario databases, using results from the SSP GDP (gross domestic product) country model results as drivers for the downscaling process. The data are available at https://doi.org/10.5281/zenodo.3638137 (Gütschow et al., 2020).