Systematically linking qualitative elements of scenarios across levels, scales, and sectors. (May 2016)

• Record Type: Journal Article
• Authors: Schweizer, Vanessa Jine; Kurniawan, Jude Herijadi
• Is Part Of: Environmental modelling & software. Volume 79(2016:May)
• Page Start: 322
• Page End: 333
• Publication Date: 2016-05
• Subjects: Cross-impact balance -- Multi-scale scenarios -- Socioeconomic scenarios -- Shared socioeconomic pathways -- Climate change -- Global change; 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.2015.12.014
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: New scenarios for climate change research connect climate model results based on Representative Concentration Pathways to nested interpretations of Shared Socioeconomic Pathways. Socioeconomic drivers of emissions and determinants of impacts are now decoupled from climate model outputs. To retain scenario credibility, more internally consistent linking across scales must be achieved. This paper addresses this need, demonstrating a modification to cross impact balances (CIB), a method for systematically deriving qualitative socioeconomic scenarios. Traditionally CIB is performed with one cross-impact matrix. This poses limitations, as more than a few dozen scenario elements with sufficiently varied outcomes can become computationally infeasible to comprehensively explore. Through this paper, we introduce the concept of 'linked CIB', which takes the structure of judgements for how scenario elements interact to partition a single cross-impact matrix into multiple smaller matrices. Potentially, this enables analysis of large CIB matrices and ensures internally consistent linking of scenario elements across scales. Highlights: Elements of multi-level qualitative scenarios have asymmetric interrelationships. Structures of interrelationships can be documented and partitioned into subsets. Analyses of subsets can systematically reconstitute a multi-level parent scenario. Internal consistency of multi-scale scenarios may be preserved with partitioning.