Two papers will be presented:
- 'Assessing present and future risk of water damage using building attributes, meteorology and topography' by Heinrich-Mertsching et al.
- 'The importance of context in extreme value analysis with application to extreme temperatures in the USA and Greenland' by Clarkson et al.
"The Discussion Meeting at this year’s RSS conference in Aberdeen will feature two papers on the Statistical Aspects of Climate Change. The Discussion Meetings Committee chose this topic area motivated by the UN Climate Change Conference (COP26) held in Glasgow last year and because climate changes and the environment is one of the RSS’s six current campaigning priorities for 2022.
You are welcome to listen to the speakers and join in the discussion of the papers which follows the presentations. All the proceedings will be published in a forthcoming issue of Journal of the Royal Statistical Society, Series C (Applied Statistics) ."
Dr Shirley Coleman, Chair and Honorary Officer for Discussion Meetings
Paper 1: ‘Assessing present and future risk of water damage using building attributes, meteorology and topography’
Weather-related risk makes the insurance industry inevitably concerned with climate and climate change. Buildings hit by pluvial flooding is a key manifestation of this risk, giving rise to compensations for the induced physical damages and business interruptions. In this work, we establish a nationwide, building-specific risk score for water damage associated with pluvial flooding in Norway. We fit a generalized additive model that relates the number of water damages to a wide range of explanatory variables that can be categorized into building attributes, climatological variables and topographical characteristics. The model assigns a risk score to every location in Norway, based on local topography and climate, which is not only useful for insurance companies, but also for city planning. Combining our model with an ensemble of climate projections allows us to project the (spatially varying) impacts of climate change on the risk of pluvial flooding towards the middle and end of the 21st century
Paper 2: ‘'The importance of context in extreme value analysis with application to extreme temperatures in the USA and Greenland'
Statistical extreme value models allow estimation of the frequency, magnitude and spatio-temporal extent of extreme temperature events in the presence of climate change. Unfortunately, the assumptions of many standard methods are not valid for complex environmental data sets, with a realistic statistical model requiring appropriate incorporation of scientific context. We examine two case studies in which the application of routine extreme value methods result in inappropriate models and inaccurate predictions. In the first scenario, record-breaking temperatures experienced in the US in the summer of 2021 are found to exceed the maximum feasible temperature predicted from a standard extreme value analysis of pre-2021 data. Incorporating random effects into the standard methods accounts for additional variability in the model parameters, reflecting shifts in unobserved climatic drivers and permitting greater accuracy in return period prediction. The second scenario examines ice surface temperatures in Greenland. The temperature distribution is found to have a poorly-defined upper tail, with a spike in observations just below 0◦C and an unexpectedly large number of measurements above this value. A Gaussian mixture model fit to the full range of measurements is found to improve fit and predictive abilities in the upper tail when compared to traditional extreme value methods.
‘Assessing present and future risk of water damage using building attributes, meteorology and topography’
: Claudio Heinrich-Mertsching*, Jens Christian Wahl*, Alba Ordonez*, Marita Stien#, John Elvsborg#, Ola Haug*, Thordis L. Thorarinsdottir*
* Norwegian Computing Center, Oslo, Norway
# Gjensidige Forsikring ASA, Oslo, Norway
'The importance of context in extreme value analysis with application to extreme temperatures in the USA and Greenland'
Daniel Clarkson, Emma Eastoe and Amber Leeson, University of Lancaster, UK
Judith Shorten for Discussion Meetings Committee and RSS Environmental Statistics Section