ED037-0019
Spatio-temporal Patterns of Stratification in Circum-Antarctic Coastal Polynyas

Monday, 14 December 2020
Poster
Nathan Shunk, University of Maine, Orono, ME, United States and Yun Li, University of Delaware, School of Marine Science and Policy, College of Earth, Ocean and Environment, Newark, DE, United States
Abstract:
Coastal Antarctic polynyas are regions with concentrated phytoplankton blooms, and therefore have important implications for terrestrial and oceanic ecosystems and the associated carbon cycles. Seasonal water-column stratification, regulated by sea ice, can modulate the exposure of phytoplankton to light and nutrients, and thus is one of the most important factors that control the duration and strength of algal blooms. Polynyas differ greatly in their stratification, thus are not equally productive in terms of phytoplankton biomass, nor equally vulnerable to the changes in regional climate. To date, most studies have been focusing on individual polynyas, yet a systematic comparison of stratification patterns across polynyas is still lacking.

To bridge the knowledge gap, we examined the spatial and temporal variability of stratification in circum-Antarctic coastal polynyas. Using >10,000 in situ hydrographic casts from the World Ocean Database for the period 1970-present, we calculated 0-100 m Simpson Energy as a proxy for water-column stratification and constructed stratification seasonal climatology for each polynya. Our results showed that, across all the polynya, there is a factor of 2-4 change in seasonal peak and 1-2 months difference in the onset time of stratification. A diagram was constructed using stratification climatology against satellite-measured sea ice concentration (SIC). It revealed several distinct regimes. Generally, a similar seasonal cycle of SIC can be associated with strongly or weakly stratified polynyas, dependent upon the local physics (e.g., mixing). Water-column stratification displays more variations than expected from SIC, indicating a nonlinear response of stratification to the SIC driver. Our study also suggests that increasing the spatial coverage and sampling frequency of in situ observations is a necessary step toward a full understanding of polynya responses to climate change.