Seasonal prediction and predictability of regional antarctic Sea ice
Journal
Journal of Climate
Journal Volume
34
Journal Issue
15
Pages
6207-6233
Date Issued
2021
Author(s)
Bushuk M
Winton M
Haumann F.A
Delworth T
Lu F
Zhang Y
Jia L
Zhang L
Cooke W
Harrison M
Hurlin B
Johnson N.C
Kapnick S.B
McHugh C
Murakami H
Rosati A
Wittenberg A.T
Yang X
Zeng F.
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, 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. © 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
Subjects
Antarctica; Climate variability; Coupled models; Data assimilation; Sea ice; Seasonal forecasting
SDGs
Other Subjects
Climatology; Forecasting; Antarctic sea ice; Coupled modeling; Dynamical predictions; Geophysical fluid dynamics laboratories; Initialization technique; Sea ice concentration; Sea-ice thickness; Seasonal prediction; Sea ice; climate prediction; data assimilation; glaciology; ice cover; prediction; sea ice; seasonal variation; timescale; Southern Ocean
Type
journal article