Global gridded data for the Shared Socio-economic Pathways

The shared socio-economic pathways (SSPs) provide storylines for plausible future global developments under a consistent set of assumptions. Primarily, the SSPs have been used to derive quantitative scenarios of greenhouse gas emissions for use in general circulation models and other large-scale, physically based models of environmental change. Their use in large-scale socio-environmental simulation modelling has been less forthcoming. Behavioural models of land systems, typically operating within agent-based frameworks, attempt to explicitly represent the varied socio-environmental factors that characterise the SSP storylines. Such simulation models are often geospatial and grid-based, capable of representing dynamics at resolutions of up to 10s km2 over large extents (continental to global). However, such approaches demand geospatial (usually gridded) input data for multiple social and human variables - often together known as capitals - such as education levels and infrastructure. The lack of such input data for the future SSP storylines has been a substantial limitation in the application of large-scale behavioural models of land systems specifically and of socio-environmental modelling more generally. ... mehrHere, we present global gridded data for socio-economic capitals useful for simulation models and consistent with the SSP storylines, disaggregated spatially to a 0.25o grid. We analyse the spatial and temporal characteristics of the projected data, comparing them to projections of GDP, and discuss their utility and limitations for large-scale socio-environmental modelling.