03 Jan 2024
 | 03 Jan 2024

Model spread in multidecadal NAO variability connected to stratosphere-troposphere coupling

Rémy Bonnet, Christine McKenna, and Amanda Maycock

Abstract. The underestimation of multidecadal variability in the winter-time North Atlantic Oscillation (NAO) by global climate models remains poorly understood. Understanding the origins of this weak NAO variability is important for making model projections more reliable. Past studies have linked the weak multidecadal NAO variability in models to an underestimated atmospheric response to the Atlantic Multidecadal Variability (AMV). We investigate historical simulations from CMIP6 large ensemble models and find that most of the models do not reproduce observed multidecadal NAO variability, as found in previous generations of climate models. We explore statistical relationships with physical drivers that may contribute to intermodel spread in NAO variability. There is a significant anti-correlation across models between the AMV-NAO coupling parameter and multidecadal NAO variability over the full historical period (r=-0.55, p<0.05). However, this relationship is relatively weak and becomes obscured when using a common period (1900–2010) and detrending the data in a consistent way with observations to enable a model-data comparison. This suggests that the representation of NAO-AMV coupling contributes to a modest proportion of intermodel spread in multidecadal NAO variability, although the importance of this process for model spread could be underestimated given evidence of a systematically poor representation of the coupling in the models. We find a significant intermodel correlation between multidecadal NAO variability and multidecadal stratospheric polar vortex variability and a stratosphere-troposphere coupling parameter, which quantifies the relationship between stratospheric winds and the NAO. The models with the lowest NAO variance are associated with weaker polar vortex variability and a weaker stratosphere-troposphere coupling parameter. The two stratospheric indices are uncorrelated across models and together give a pooled R2 with NAO variability of 0.7, which is larger than the fraction of intermodel spread related to the AMV (R2=0.3). The identification of this relationship suggests that modelled spread in multidecadal NAO variability has the potential to be reduced by improved knowledge of observed multidecadal stratospheric variability; however, observational records are currently too short to give a robust constraint on these indices.

Rémy Bonnet, Christine McKenna, and Amanda Maycock

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-3103', Amy Butler, 29 Jan 2024
  • RC2: 'Comment on egusphere-2023-3103', Anonymous Referee #2, 01 Feb 2024
Rémy Bonnet, Christine McKenna, and Amanda Maycock
Rémy Bonnet, Christine McKenna, and Amanda Maycock


Total article views: 227 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
173 45 9 227 15 3 2
  • HTML: 173
  • PDF: 45
  • XML: 9
  • Total: 227
  • Supplement: 15
  • BibTeX: 3
  • EndNote: 2
Views and downloads (calculated since 03 Jan 2024)
Cumulative views and downloads (calculated since 03 Jan 2024)

Viewed (geographical distribution)

Total article views: 228 (including HTML, PDF, and XML) Thereof 228 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 04 Mar 2024
Short summary
Climate models underestimate multidecadal winter North Atlantic Oscillation (NAO) variability. Understanding the origin of this weak variability is important for making reliable climate projections. We use multi-model climate simulations to explore statistical relationships with drivers that may contribute to NAO variability. We find a relationship between modeled stratosphere-troposphere coupling and multidecadal NAO variability, offering an avenue to improve the simulation of NAO variability.