Southern Ocean polynyas in CMIP6 models

• Published in: The Cryosphere
• Main Authors: M. Mohrmann, C. Heuzé, S. Swart
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2021
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; Antarctic; Southern Ocean; Curl; Antarc*; Iceberg*; Sea ice; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-15-4281-2021; https://doaj.org/article/e13dc47752ca4730be1d8af433ca3c7d

Polynyas facilitate air–sea fluxes, impacting climate-relevant properties such as sea ice formation and deep water production. Despite their importance, polynyas have been poorly represented in past generations of climate models. Here we present a method to track the presence, frequency and spatial distribution of polynyas in the Southern Ocean in 27 models participating in the Climate Model Intercomparison Project Phase 6 (CMIP6) and two satellite-based sea ice products. Only half of the 27 models form open-water polynyas (OWPs), and most underestimate their area. As in satellite observations, three models show episodes of high OWP activity separated by decades of no OWP, while other models unrealistically create OWPs nearly every year. In contrast, the coastal polynya area is overestimated in most models, with the least accurate representations occurring in the models with the coarsest horizontal resolution. We show that the presence or absence of OWPs is linked to changes in the regional hydrography, specifically the linkages between polynya activity with deep water convection and/or the shoaling of the upper water column thermocline. Models with an accurate Antarctic Circumpolar Current transport and wind stress curl have too frequent OWPs. Biases in polynya representation continue to exist in climate models, which has an impact on the regional ocean circulation and ventilation that should be addressed. However, emerging iceberg discharge schemes, more adequate vertical grid type or overflow parameterisation are anticipated to improve polynya representations and associated climate prediction in the future.