High-Resolution Thermal Imaging in the Antarctic Marginal Ice Zone : Skin Temperature Heterogeneity and Effects on Heat Fluxes

• Published in: Earth and Space Science
• Main Authors: Tersigni, Ippolita, Alberello, Alberto, Messori, Gabriele, Vichi, Marcello, Onorato, Miguel, Toffoli, Alessandro
• Format: Article in Journal/Newspaper
• Language: English
• Published: Uppsala universitet, Luft-, vatten- och landskapslära 2023
• Subjects: Oceanography; Hydrology and Water Resources; Oceanografi; hydrologi och vattenresurser; Antarctic; Austral; Indian; Southern Ocean; The Antarctic; Antarc*; Sea ice
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-514361; https://doi.org/10.1029/2023EA003078

Insufficient in situ observations from the Antarctic marginal ice zone (MIZ) limit our understanding and description of relevant mechanical and thermodynamic processes that regulate the seasonal sea ice cycle. Here we present high-resolution thermal images of the ocean surface and complementary measurements of atmospheric variables that were acquired underway during one austral winter and one austral spring expedition in the Atlantic and Indian sectors of the Southern Ocean. Skin temperature data and ice cover images were used to estimate the partitioning of the heterogeneous surface and calculate the heat fluxes to compare with ERA5 reanalyses. The winter MIZ was composed of different but relatively regularly distributed sea ice types with sharp thermal gradients. The surface-weighted skin temperature compared well with the reanalyses due to a compensation of errors between the sea ice fraction and the ice floe temperature. These uncertainties determine the dominant source of inaccuracy for heat fluxes as computed from observed variables. In spring, the sea ice type distribution was more irregular, with alternation of sea ice cover and large open water fractions even 400 km from the ice edge. The skin temperature distribution was more homogeneous and did not produce substantial uncertainties in heat fluxes. The discrepancies relative to reanalysis data are however larger than in winter and are attributed to biases in the atmospheric variables, with the downward solar radiation being the most critical.