Subnational climate scenarios provide critical societal and environmental information for resolving future climate-related risks and response options at a scale more relevant to the systems being affected or taking action.
Despite progress in incorporating human dimensions into national and subnational climate scenarios, existing approaches which directly downscales global or national demographic projections to provide local information insufficiently capture what is likely the principle source of spatial heterogeneity in demographic outcomes: migration between sub-regions, which can significantly change the broad patterns of population distribution at a scale that lies between the national and the local.
Please join the Population Council to explore a novel set of scenarios for internal (state to state) migration rates within the United States, as well as an extension of Shared Socioeconomic Pathways (SSPs) to incorporate assumptions of demographic events. The SSPs offer a set of future “pathways” identified by an international team of climate scientists, economists, demographers, and energy systems modelers that examine how social, demographic, and economic factors might change over the rest of century. Intended to provide global and even local information for use in climate change modeling, the SPPs include five narratives as well as quantitative measures of population and GDP and are feeding into the Intergovernmental Panel on Climate Change (IPCC) assessment reports.
Senior Associate Leiwen Jiang, working with co-authors, will also share the consistent multiscale population and urbanization projections at national and state levels, as well the spatial downscaling results at 1 km grids within each state. The new projections suggest that the spatial distribution of populations can vary much more widely across SSPs than currently available US population projections indicate. The model therefore has the potential to improve characterization of climate-related risks to populations, as well as the resulting spatial patterns of mitigation and adaptation challenges.