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American Meteorological Society, Weather, Climate, and Society, 2(14), p. 619-636, 2022

DOI: 10.1175/wcas-d-21-0014.1

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Climate Change Impact Chains: A Review of Applications, Challenges, and Opportunities for Climate Risk and Vulnerability Assessments

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Shifting from effect-oriented toward cause-oriented and systemic approaches in sustainable climate change adaptation requires a solid understanding of the climate-related and societal causes behind climate risks. Thus, capturing, systemizing, and prioritizing factors contributing to climate risks are essential for developing cause-oriented climate risk and vulnerability assessments (CRVA). Impact chains (IC) are conceptual models used to capture hazard, vulnerability, and exposure factors that lead to a specific risk. IC modeling includes a participatory stakeholder phase and an operational quantification phase. Although ICs are widely implemented to systematically capture risk processes, they still show methodological gaps concerning, for example, the integration of dynamic feedback or balanced stakeholder involvement. Such gaps usually only become apparent in practical applications, and there is currently no systematic perspective on common challenges and methodological needs. Therefore, we reviewed 47 articles applying IC and similar CRVA methods that consider the cause–effect dynamics governing risk. We provide an overview of common challenges and opportunities as a roadmap for future improvements. We conclude that IC should move from a linear-like to an impact web–like representation of risk to integrate cause–effect dynamics. Qualitative approaches are based on significant stakeholder involvement to capture expert-, place-, and context-specific knowledge. The integration of IC into quantifiable, executable models is still highly underexplored because of a limited understanding of systems, data, evaluation options, and other uncertainties. Ultimately, using IC to capture the underlying complex processes behind risk supports effective, long-term, and sustainable climate change adaptation.