The diversity of socio-economic pathways and CO2 emissions scenarios: Insights from the investigation of a scenarios database. (June 2016)

• Record Type: Journal Article
• Authors: Guivarch, Céline; Rozenberg, Julie; Schweizer, Vanessa
• Is Part Of: Environmental modelling & software. Volume 80(2016:Jun.)
• Page Start: 336
• Page End: 353
• Publication Date: 2016-06
• Subjects: Scenario discovery -- Diversity -- Socioeconomic pathways -- Emissions scenarios -- Database; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.03.006
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The new scenario framework developed by the climate change research community rests on the fundamental logic that a diversity of socio-economic pathways can lead to the same radiative forcing, and therefore that a given level of radiative forcing can have very different socio-economic impacts. We propose a methodology that implements a "scenario discovery" cluster analysis and systematically identifies diverse groups of scenarios that share common outcomes among a database of socio-economic scenarios. We demonstrate the methodology with two examples using the Shared Socio-economic Pathways framework. We find that high emissions scenarios can be associated with either high or low per capita GDP growth, and that high productivity growth and catch-up are not necessarily associated with high per capita GDP and high emissions. Highlights: We adapt scenario discovery cluster analysis to explore socioeconomic scenario diversity. A diversity of scenarios with high cumulative CO2 emissions is explored. High emissions scenarios can be associated with either high or low per capita GDP growth. Diverse scenarios can correspond to any of the Shared Socioeconomic Pathways domains.