Changes in the distribution of observed annual maximum temperatures in Europe

TL;DR

This study analyzes long-term changes in the distribution of annual maximum temperatures across Europe from 1950 to 2018, revealing a significant shift towards hotter extremes and quantifying the increase in return levels over time.

Contribution

It introduces a spatially smoothed GEV modeling approach that incorporates CO2 levels to detect and quantify temperature extremes changes across Europe.

Findings

100-year return level of TXx increased by about 2°C from 1950 to 2018

Significant shifts in GEV location parameters towards higher temperatures

The 1950 climate's 100-year TXx corresponds to a 6-year return level in 2018

Abstract

In this study we consider the problem of detecting and quantifying changes in the distribution of the annual maximum daily maximum temperature (TXx) in a large gridded data set of European daily temperature during the years 1950-2018. Several statistical models are considered, each of which models TXx using a generalized extreme value (GEV) distribution with the GEV parameters varying smoothly over space. In contrast to several previous studies which fit independent GEV models at the grid box level, our models pull information from neighbouring grid boxes for more efficient parameter estimation. The GEV location and scale parameters are allowed to vary in time using the log of atmospheric CO2 as a covariate. Changes are detected most strongly in the GEV location parameter with the TXx distributions generally shifting towards hotter temperatures. Averaged across our spatial domain, the 100-year return level of TXx based on the 2018 climate is approximately 2{\deg}C hotter than that based on the 1950 climate. Moreover, also averaging across our spatial domain, the 100-year return level of TXx based on the 1950 climate corresponds approximately to a 6-year return level in the 2018 climate.