Quantifying uncertainty in aggregated climate change risk assessments.
Ontology highlight
ABSTRACT: High-level assessments of climate change impacts aggregate multiple perils into a common framework. This requires incorporating multiple dimensions of uncertainty. Here we propose a methodology to transparently assess these uncertainties within the 'Reasons for Concern' framework, using extreme heat as a case study. We quantitatively discriminate multiple dimensions of uncertainty, including future vulnerability and exposure to changing climate hazards. High risks from extreme heat materialise after 1.5-2 °C and very high risks between 2-3.5 °C of warming. Risks emerge earlier if global assessments were based on national risk thresholds, underscoring the need for stringent mitigation to limit future extreme heat risks.
SUBMITTER: Harrington LJ
PROVIDER: S-EPMC8655081 | biostudies-literature | 2021 Dec
REPOSITORIES: biostudies-literature
ACCESS DATA