Abstract

Compared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this talk, I will use three coupled dynamical prediction systems developed at the Geophysical Fluid Dynamics Laboratory to assess the seasonal prediction skill and predictability of Antarctic sea ice. These systems, based on the FLOR , SPEAR-lo, and SPEAR -med dynamical models, differ in their coupled model components, initialization techniques, atmospheric resolution, and model biases. This allows for an investigation of these factors in determining Antarctic sea ice prediction skill. Using suites of retrospective initialized seasonal predictions spanning 1992-2018, we find that each system is capable of skillfully predicting regional Antarctic sea ice extent (SIE) with skill that generically exceeds that of a persistence forecast. Winter SIE is skillfully predicted up to 11 months in advance in the Weddell, Amundsen and Bellingshausen, Indian, and West Pacific sectors, whereas winter skill is notably lower in the Ross sector. Zonally advected upper ocean heat content anomalies are found to provide the crucial source of prediction skill for the winter sea ice edge position. The SPEAR systems are notably more skillful than FLOR for summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE can be skillfully predicted up to 8 months in advance in SPEAR -med, due to the persistence and drift of initialized sea ice thickness anomalies from the previous winter. Overall, these results suggest a promising potential for providing operational regional Antarctic sea ice predictions on seasonal timescales.