Christine P Chai’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’

Statistical aspects of climate change

Paper 1: Assessing present and future risk of water damage using building attributes, meteorology and topography

Authors: 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

Paper 2: The importance of context in extreme value analysis with application to extreme temperatures in the USA and Greenland

Authors: Daniel Clarkson, Emma Eastoe, Amber Leeson, University of Lancaster, UK

Disclaimer: The opinions and views expressed here are those of the author and do not necessarily state or reflect those of Microsoft.

Discussion

Climate change has been an emerging research field given its tremendous effect on human beings, and I am happy to see discussions like (Clarkson et al., 2023; Heinrich-Mertsching et al., 2022). To increase awareness of modelling climate change, we also need to inoculate the public against online misinformation (Treen et al., 2020; Van der Linden et al., 2017). Neither statistical model is perfect, and their limitations can easily be attacked by researchers with a vested interest in the fossil fuels industry. In terms of environmental science, there is still much work to do in both the scientific side and the education side.

In the second paper (Clarkson et al., 2023), I appreciate the introduction to the history of extreme value theory and applications. With the increasing availability of spatio-temporal image data, spatial statistics has become multidimensional and more complex than ever. Sometimes a parsimonious model is sufficient, and I am pleasantly surprised to see a relatively simple method to model extreme temperatures over time. In the extreme value analysis with random effects, this article is focused on the upper tail (high temperature). Can the Gaussian mixture model fit be applied to the lower tail as well? Unexpectedly cold winters also cause damage to human beings and property.

Data availability

No new data were generated or analyzed in support of this research.

References

Author notes