Atmospheric forcing of sea ice anomalies in the Ross Sea polynya region

• Published in: The Cryosphere
• Main Authors: E. R. Dale, A. J. McDonald, J. H. J. Coggins, W. Rack
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2017
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; Austral; Ross Ice Shelf; Ross Island; Ross Sea; Ice Shelf; Sea ice; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-11-267-2017; https://doaj.org/article/a513e234c67748e0b7ae28fd8f0c2e1f

We investigate the impacts of strong wind events on the sea ice concentration within the Ross Sea polynya (RSP), which may have consequences on sea ice formation. Bootstrap sea ice concentration (SIC) measurements derived from satellite SSM/I brightness temperatures are correlated with surface winds and temperatures from Ross Ice Shelf automatic weather stations (AWSs) and weather models (ERA-Interim). Daily data in the austral winter period were used to classify characteristic weather regimes based on the percentiles of wind speed. For each regime a composite of a SIC anomaly was formed for the entire Ross Sea region and we found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya and vice versa. By analyzing sea ice motion vectors derived from the SSM/I brightness temperatures we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events, which persist for several days after a strong wind event has ended. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of sea ice in the region. We were able to partially recreate these correlations using colocated, modeled ERA-Interim wind speeds. However, large AWS and model differences are observed in the vicinity of Ross Island, where ERA-Interim underestimates wind speeds by a factor of 1.7 resulting in a significant misrepresentation of RSP processes in this area based on model data. Thus, the cross-correlation functions produced by compositing based on ERA-Interim wind speeds differed significantly from those produced with AWS wind speeds. In general the rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. The SIC recovery continues over a time period greater than the average persistence of strong wind events and sea ice motion anomalies. This suggests that sea ice recovery occurs through thermodynamic rather than ...