Building physical constraints into weather-related risk estimates
Lead Research Organisation:
University of Reading
Department Name: Mathematics and Statistics
Abstract
When required to extrapolate to very rare return periods, standard extreme value models and their typified statistical inference techniques can lead to estimates with a large amount of uncertainty. In many situations, these estimates start to exceed plausible levels and such large values can reduce the confidence that end-users have in the final results from extreme value models.
In the context of recent extreme weather events, natural hazard characterisation continues to be an important area of research for EDF Energy. This PhD project is seen as a way to improve the natural hazard characterisation approaches used within EDF Energy. The overall goal is to obtain more reliable constraints on extreme rainfall risk from historical records, using physical principles to draw inference from observable causes to certain extreme events. This project will combine new developments in extreme value theory with recent advances in approaches for understanding the physical drivers of extreme events.
In the context of recent extreme weather events, natural hazard characterisation continues to be an important area of research for EDF Energy. This PhD project is seen as a way to improve the natural hazard characterisation approaches used within EDF Energy. The overall goal is to obtain more reliable constraints on extreme rainfall risk from historical records, using physical principles to draw inference from observable causes to certain extreme events. This project will combine new developments in extreme value theory with recent advances in approaches for understanding the physical drivers of extreme events.
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/S513878/1 | 30/09/2018 | 30/06/2022 | |||
2325291 | Studentship | EP/S513878/1 | 13/01/2020 | 14/04/2024 | Graham Davies |