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Quantifying uncertainty in aggregated climate change risk assessments.

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

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Quantifying uncertainty in aggregated climate change risk assessments.

Harrington Luke J LJ Schleussner Carl-Friedrich CF Otto Friederike E L FEL

Nature communications 20211208 1

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 a ...[more]

PMID: 34880228

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Dataset Information

Quantifying uncertainty in aggregated climate change risk assessments.

Publications

Quantifying uncertainty in aggregated climate change risk assessments.

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