EGU23-2242, updated on 26 Oct 2023
https://doi.org/10.5194/egusphere-egu23-2242
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A Quantile Generalised Additive Approach for Compound Climate Extremes: Pan-Atlantic Extremes as a Case Study

Leonardo Olivetti1, Gabriele Messori1,2,3, and Shaobo Jin4
Leonardo Olivetti et al.
  • 1Department of Earth Sciences, Uppsala University, Uppsala, Sweden
  • 2Centre of Natural Hazards and Disaster Science (CNDS), Uppsala University, Uppsala, Sweden
  • 3Department of Meteorology and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
  • 4Department of Statistics, Uppsala University, Uppsala, Sweden

We present an application of quantile generalised additive models (QGAMs) to study the rela-
tionship between spatially compounding climate extremes - namely extremes that occur (near-)
simultaneously in geographically remote regions. We take as example wintertime cold spells
in North America and co-occurring wet or windy surface weather extremes in Western Europe,
which we collectively term Pan-Atlantic compound extremes. QGAMS are largely novel in cli-
mate science applications and present three key advantages over conventional statistical models
of weather extremes:


1. they do not require a direct identification and parametrisation of the extremes themselves,
since they model all quantiles of the distributions of interest;
2. they do not require any a priori knowledge of the functional relationship between the predic-
tors and the dependent variable;
3. they make use of all information available, and not only of a small number of extreme values.


Here, we use QGAMs to both characterise the co-occurrence statistics and investigate possible
dynamical drivers of the Pan-Atlantic compound extremes. We find that recent cold spells in
North America are a useful predictor of upcoming near-surface extremes in Western Europe,
and that QGAMs can predict those extremes more accurately than conventional peak-over-
threshold models.

How to cite: Olivetti, L., Messori, G., and Jin, S.: A Quantile Generalised Additive Approach for Compound Climate Extremes: Pan-Atlantic Extremes as a Case Study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2242, https://doi.org/10.5194/egusphere-egu23-2242, 2023.

Supplementary materials

Supplementary material file