Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 11, issue 1
Articles | Volume 11, issue 1
https://doi.org/10.5194/ascmo-11-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-11-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 1
20 Feb 2025
 | 20 Feb 2025

Reducing reliability bias in assessments of extreme weather risk using calibrating priors

Stephen Jewson, Trevor Sweeting, and Lynne Jewson

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Short summary
We investigate how to make statistical predictions of extreme weather such that events predicted to occur with a probability of 1 % will occur 1 % of the time. We apply the methods we describe to a standard extreme weather attribution example from the recent climate literature. We find that the methods we describe imply that extremes are roughly twice as likely as when estimated using maximum likelihood. We have developed a software package to make it easy to apply these methods.
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