Estimating changes in extreme quantiles over time, applied to desert temperatures

TL;DR

This study uses Bayesian GEV regression on climate model data to quantify and compare projected changes in extreme desert temperatures over the 21st century, highlighting significant increases under severe scenarios.

Contribution

It introduces a Bayesian GEV regression framework with model selection via BIC to estimate and compare future extreme temperature changes across desert regions using CMIP6 models.

Findings

Significant increases in 100-year extreme maxima under severe climate scenarios.

Bayesian BIC model selection improves prediction accuracy.

Consistent trend of increasing temperature extremes across regions and models.

Abstract

We quantify changes DeltaQ in 100-year return values for regional annual maxima and minima of near-surface atmospheric temperature from output of five CMIP6 models, for five of the Earth's desert regions, over the interval (2025,2125). We use generalised extreme value (GEV) regression to characterise changes in extremes, considering a range of different parametric forms for the variation of GEV parameters with time, and coupling models for different scenarios so that they provide a common GEV tail in the first year of observation. Parameters are estimated using Bayesian inference. We perform a simulation study using ground truth models generating data qualitatively similar to the CMIP6 output, to assess the relative performance of different information criteria in selecting models from a set of candidates, to minimise error in predictions of DeltaQ. The Bayesian information criterion (BIC) provides best performance, out-performing the divergence and widely-applicable information criteria in particular. Using BIC-selected GEV regression models, we estimate joint posterior distributions of DeltaQ over three forcing scenarios, for different combinations of region, GCM and climate ensemble. Estimates show a consistent trend across regions, GCMs and climate ensembles, of DeltaQ increasing with climate scenario for both regional annual maxima and minima. Aggregating posterior distributions over climate ensembles and GCMs, we find evidence for significant increases in DeltaQ for regional annual maxima under more severe forcing scenarios for all desert regions. Similar but weaker and less significant trends are observed for regional annual minima.