OS049-05
Seasonal prediction and predictability of regional Antarctic sea ice
Wednesday, 16 December 2020: 08:58
Virtual
Mitchell Bushuk1, Michael Winton2, Alexander Haumann3, Thomas L Delworth1, Feiyu Lu1, Liwei Jia1, Liping Zhang1, Xiaosong Yang1, Matt Harrison1, Anthony John Rosati1, Colleen McHugh1, Nathaniel Johnson1, Sarah B. Kapnick1, Fanrong Jenny Zeng1, Hiroyuki Murakami1, Andrew Thorne Wittenberg1 and Kai-Chih Tseng4, (1)NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (2)NOAA / Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (3)Princeton University, Princeton, United States, (4)Princeton University, Princeton, NJ, United States
Abstract:
Compared 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, atmospheric resolution, initialization techniques, 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. We find that advected upper ocean heat content anomalies provide a crucial source of prediction skill for the winter sea ice edge position. The recently-developed 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. Overall, these results suggest a promising potential for providing operational regional Antarctic sea ice predictions on seasonal timescales.
