Variability and extremes: statistical validation of the Alfred Wegener Institute Earth System Model (AWI-ESM)

Justus Contzen,Thorsten Dickhaus,Gerrit Lohmann

doi:10.5194/gmd-15-1803-2022

Abstract

Abstract. Coupled general circulation models are of paramount importance to quantitatively assessing the magnitude of future climate change. Usual methods for validating climate models include the evaluation of mean values and covariances, but less attention is directed to the evaluation of extremal behaviour. This is a problem because many severe consequences of climate change are due to climate extremes. We present a method for model validation in terms of extreme values based on classical extreme value theory. We further discuss a clustering algorithm to detect spatial dependencies and tendencies for concurrent extremes. To illustrate these methods, we analyse precipitation extremes of the Alfred Wegener Institute Earth System Model (AWI-ESM) global climate model and from other models that take part in the Coupled Model Intercomparison Project CMIP6 and compare them to the reanalysis data set CRU TS4.04. The clustering algorithm presented here can be used to determine regions of the climate system that are then subjected to a further in-depth analysis, and there may also be applications in palaeoclimatology.

Highlights

Coupled general circulation models are frequently utilised to quantitatively assess the magnitude of future climate change
We presented approaches and methods to validate climate model outputs by comparing their extremal behaviour to the extremal behaviour of observational data
We compared precipitation extremes between the Alfred Wegener Institute Earth System Model (AWI-ESM) and the CRU TS4.04 data set of reanalysed observations

Summary

Introduction

Coupled general circulation models are frequently utilised to quantitatively assess the magnitude of future climate change. Validating these models by simulating different climate states is essential for understanding the sensitivity of the climate system to both natural and anthropogenic forcing. Usual methods for validating climate models include the evaluation of mean values and covariances and the comparison of empirical cumulative distribution functions. These analyses can be conducted over seasonal and annual averages (climatologies) or along latitudinal and longitudinal transects (Tapiador et al, 2012). Due to the inherent nature of extreme events, their evolution differs from that of the mean and the variance (Schär et al, 2004; IPCC, 2012) and depends on the strength of the events themselves (Myhre et al, 2019)

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Conclusion