Seasonal Prediction and Predictability of Regional Antarctic Sea Ice

• DOI: 10.1175/jcli-d-20-0965.1
• Publication Date: 2021-05-10T16:05:35Z
• Authors: Mitchell Bushuk; Michael Winton; F. Alexander Haumann; Thomas Delworth; Feiyu Lu; Yongfei Zhang; Liwei Jia; Liping Zhang; William Cooke; Matthew Harrison; Bill Hurlin; Nathaniel C. Johnson; Sarah B. Kapnick; Colleen McHugh; Hiroyuki Murakami; Anthony Rosati; Kai-Chih Tseng; Andrew T. Wittenberg; Xiaosong Yang; Fanrong Zeng
• Keywords: 13. Climate action; 14. Life underwater; 01 natural sciences; 0105 earth and related environmental sciences

AbstractCompared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this work, we utilize 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. Using suites of retrospective initialized seasonal predictions spanning 1992–2018, we investigate the role of these factors in determining Antarctic sea ice prediction skill and examine the mechanisms of regional sea ice predictability. We find that each system is capable of skillfully predicting regional Antarctic sea ice extent (SIE) with skill that exceeds a persistence forecast. Winter SIE is skillfully predicted 11 months in advance in the Weddell, Amundsen/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 recently developed SPEAR systems are more skillful than FLOR for summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE is skillfully predicted up to 9 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 Antarctic sea ice predictions on seasonal time scales.