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dc.contributor.authorICASP14
dc.date.accessioned2023-08-03T11:02:08Z
dc.date.available2023-08-03T11:02:08Z
dc.date.issued2023
dc.identifier.citationMeiler, S., Ciullo, A., Bresch, D. N., & Kropf, C. M. (2023). Uncertainty and sensitivity analysis for probabilistic, global modelling of future tropical cyclone risk. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland. https://doi.org/10.25546/103244
dc.descriptionPUBLISHED
dc.description.abstractModelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, growing economies, evolving societies, and declining ecosystems. Here we apply a new feature of the CLIMADA climate risk modelling platform, which allows carrying out global uncertainty and sensitivity analysis. We showcase the comprehensive treatment of uncertainty and sensitivity of CLIMADAメs outputs for the assessment of future global tropical cyclone (TC) risk. Our results show that socio-economic development contributes more strongly to TC risk increase in the future and is a more uncertain risk driver than climate change. Besides, we find that exposure scaling based on the Shared Socioeconomic Pathways (SSP) is the input variable with the most significant impact on TC risk change calculations. In conclusion, we argue that a thorough and systematic assessment of future global TC risk will help focus forthcoming research efforts and enable better-informed adaptation decisions and mitigation strategies.
dc.language.isoen
dc.relation.ispartofseries14th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP14)
dc.rightsY
dc.titleUncertainty and sensitivity analysis for probabilistic, global modelling of future tropical cyclone risk
dc.title.alternative14th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP14)
dc.typeConference Paper
dc.type.supercollectionscholarly_publications
dc.type.supercollectionrefereed_publications
dc.identifier.doihttps://doi.org/10.25546/103244
dc.rights.ecaccessrightsopenAccess
dc.identifier.urihttp://hdl.handle.net/2262/103244


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    14th International Conference on Application of Statistics and Probability in Civil Engineering

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