Updating Catastrophe Models to Today's Climate – An Application of a Large Ensemble Approach to Extreme Rainfall.¶
Lang, A., & Poschlod, B. (2024). Updating Catastrophe Models to Today's Climate – An Application of a Large Ensemble Approach to Extreme Rainfall. Climate Risk Management, 44.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Extrapolation Beyond Sampled Regime
- Parametric insurance, forecasting, and engineering qualification: catastrophe-model triggers, time-series prediction intervals, and qualification certificates all carry in-sample confidence machinery that cannot encode that the underlying regime has moved.
This sourceShows catastrophe models built on stationary historical hazard frequencies systematically misstate present risk as the underlying climate regime shifts (e.g., rising 50-year rainfall return levels), so in-sample confidence machinery cannot encode that the regime has moved.
Supported in partVerified against the publisher's abstract
The abstract backs only the catastrophe-model leg: hazard parameters calibrated on past observations may need updating as the climate regime shifts; it says nothing about forecasting intervals or engineering qualification certificates.
“risk modelers have to ask themselves the question whether a certain ‘hazard’ parameter based on past observations and calibrated on past data is still valid or needs to be updated”
- Parametric insurance, forecasting, and engineering qualification: catastrophe-model triggers, time-series prediction intervals, and qualification certificates all carry in-sample confidence machinery that cannot encode that the underlying regime has moved.
Verification¶
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Registry ID ref:87582670d86c · see in the full table