Subpolar North Atlantic mean state affects the response of the Atlantic Meridional Overturning Circulation to the North Atlantic Oscillation in CMIP6 models

• Published in: Journal of Climate
• Main Authors: Reintges, Annika, Robson, Jon I., Sutton, Rowan, Yeager, Stephen G.
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Meteorological Society 2024
• Subjects: Labrador Sea; North Atlantic; North Atlantic oscillation; Sea ice
• Online Access: https://centaur.reading.ac.uk/117082/; https://centaur.reading.ac.uk/117082/1/Reintges_et_al-revision2_accepted.pdf

The Atlantic Meridional Overturning Circulation (AMOC) plays an important role in climate, transporting heat and salt to the subpolar North Atlantic. The AMOC’s variability is sensitive to atmospheric forcing, especially the North Atlantic Oscillation (NAO). Because AMOC observations are short, climate models are a valuable tool to study the AMOC’s variability. Yet, there are known issues with climate models, like uncertainties and systematic biases. To investigate this, pre-industrial control experiments from models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) are evaluated. There is large, but correlated, spread in the models’ subpolar gyre mean surface temperature and salinity. By splitting models into groups of either a warm-salty or cold-fresh subpolar gyre, it is shown that warm-salty models have a lower sea ice cover in the Labrador Sea and, hence, enable a larger heat loss during a positive NAO. Stratification in the Labrador Sea is also weaker in warm-salty models, such that the larger NAO-related heat loss can also affect greater depths. As a result, subsurface density anomalies are much stronger in the warm-salty models than in those that tend to be cold and fresh. As these anomalies propagate southward along the western boundary, they establish a zonal density gradient anomaly that promotes a stronger delayed AMOC response to the NAO in the warm-salty models. These findings demonstrate how model mean state errors are linked across variables and affect variability, emphasizing the need for improvement of the subpolar North Atlantic mean states in models.