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.

Highlights

  • The wintertime atmospheric circulation in the Euro-Atlantic region is highly complex, featuring non-linear Rossby wave break15 ing (Woollings et al, 2008), complex orography (White et al, 2019), variability in the position, speed and angle of the low-level jet, and external forcings from ocean heat fluxes (Delworth and Zeng, 2016; Delworth et al, 2017), Arctic sea ice (Barnes and Screen, 2015), stratospheric signals (Domeisen et al, 2020) and tropical teleconnections (Rodríguez-Fonseca et al, 2016; Jiménez-Esteve and Domeisen, 2018)

  • We find that CMIP6 has a considerably improved spatial regime structure, and a more trimodal eddy-driven 10 jet, relative to CMIP5, but still struggles with underpersistent regimes, and too little European blocking, when compared to reanalysis

  • A powerful approach that is well-suited for understanding and characterising the fundamentally non-linear behaviour of this region is to think in terms of regime dynamics - a discretisation of the continuous atmospheric state into a small number of qualitatively distinct flow patterns

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Summary

Introduction

The wintertime atmospheric circulation in the Euro-Atlantic region is highly complex, featuring non-linear Rossby wave break ing (Woollings et al, 2008), complex orography (White et al, 2019), variability in the position, speed and angle of the low-level jet, and external forcings from ocean heat fluxes (Delworth and Zeng, 2016; Delworth et al, 2017), Arctic sea ice (Barnes and Screen, 2015), stratospheric signals (Domeisen et al, 2020) and tropical teleconnections (Rodríguez-Fonseca et al, 2016; Jiménez-Esteve and Domeisen, 2018). Since the time-invariance of regime patterns is assumed - often implicitly - by many applications of regimes to both predictability (Strommen et al, 2019a) and, crucially, climate change (Corti et al, 1999), this has seriously complicated the practical use of regimes to date This is in stark contrast to the regime behaviour of the eddy-driven North-Atlantic jet stream, which features visually obvious trimodality in its daily latitude distribution, with peaks robustly centred at particular latitudes. We will demonstrate that geopotential-jet regimes are identified and very well represented in climate models, indicating their suitability for such analysis They provide a comprehensive 70 assessment of historical regime variability, model bias, and the physical predictors of realistic regime representation within. We are able to provide a comprehensive analysis of the current state-of-the-art in climate model regime representation

Jet stream metrics
Regime computation and metrics
Description of predictive model parameters
Geopotential-jet regimes in reanalysis
Geopotential-jet regimes in CMIP5 and CMIP6
Jet latitude regimes in CMIP5 and CMIP6
Spatial regime structure
Regime occurrence
Regime persistence
Findings
Discussion and Conclusion
Full Text
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