Preprints
https://doi.org/10.5194/wcd-2021-71
https://doi.org/10.5194/wcd-2021-71

  21 Oct 2021

21 Oct 2021

Review status: this preprint is currently under review for the journal WCD.

How well does CMIP6 capture the dynamics of Euro-Atlantic weather regimes, and why?

Joshua Dorrington1,, Kristian Strommen1,, and Federico Fabiano2 Joshua Dorrington et al.
  • 1Department of Atmospheric, Oceanic, and Planetary Physics, University of Oxford, UK
  • 2Institute of Atmospheric Sciences and Climate (ISAC-CNR), Bologna, Italy
  • These authors contributed equally to this work.

Abstract. Even the most advanced climate models struggle to reproduce the observed wintertime circulation of the atmosphere over the North Atlantic and Western Europe. During winter, this particularly challenging region is dominated by eddy-driven and highly non-linear flows, which are often studied from the perspective of regimes – a small number of qualitatively distinct atmospheric states. Poor representation of regimes associated with persistent atmospheric blocking events, or variations in jet latitude, degrade the ability of models to correctly simulate extreme events. In this paper we leverage a recently developed hybrid approach – which combines both jet and geopotential height data – to assess the representation of regimes in 8,400 years of historical climate simulations drawn from CMIP6, CMIP5 and HighResMip. We show that these geopotential-jet regimes are particularly suited to the analysis of climate data, with considerable reductions in sampling variability compared to classical regime approaches. We find that CMIP6 has a considerably improved spatial regime structure, and a more trimodal eddy-driven jet, relative to CMIP5, but still struggles with underpersistent regimes, and too little European blocking, when compared to reanalysis. Reduced regime persistence can be understood, at least in part, as a result of jets that are too fast and eddy feedbacks on the jet stream that are too weak – structural errors that do not noticeably improve in higher resolution models.

Joshua Dorrington et al.

Status: open (until 15 Dec 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Joshua Dorrington et al.

Data sets

Reanalysis and Model regime datasets, regression metrics, and example analysis code Josh Dorrington, Federico Fabiano https://github.com/joshdorrington/GJR_hist_climate_data

Joshua Dorrington et al.

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Short summary
We investigate how well current state-of-the-art climate models reproduce the wintertime weather of the North Atlantic and Western Europe, by studying how well different 'regimes' of weather are captured. Historically, models have struggled to capture these regimes, making it hard to predict future changes in wintertime extreme weather. We show models can capture regimes if the right method is used, but they show biases, partially as a result of biases in jet speed and eddy strength.