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SUMMARY:Seasonal prediction and predictability of regional Antarctic sea i
 ce - Mitch Bushuk\, Geophysical Fluid Dynamics Laboratory
DTSTART:20201021T130000Z
DTEND:20201021T140000Z
UID:TALK150712@talks.cam.ac.uk
CONTACT:Dr Irena Vankova
DESCRIPTION: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 Fl
 uid Dynamics Laboratory to assess the seasonal prediction skill and predic
 tability of Antarctic sea ice. These systems\, based on the FLOR\, SPEAR-l
 o\, and SPEAR-med dynamical models\, differ in their coupled model compone
 nts\, initialization techniques\, atmospheric resolution\, and model biase
 s. This allows for an investigation of these factors in determining Antarc
 tic sea ice prediction skill. Using suites of retrospective initialized se
 asonal predictions spanning 1992-2018\, we find that each system is capabl
 e of skillfully predicting regional Antarctic sea ice extent (SIE) with sk
 ill 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 s
 kill is notably lower in the Ross sector. Zonally advected upper ocean hea
 t 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 improvem
 ents in sea ice concentration and sea ice thickness initialization. Summer
  Weddell SIE can be skillfully predicted up to 8 months in advance in SPEA
 R-med\, due to the persistence and drift of initialized sea ice thickness 
 anomalies from the previous winter. Overall\, these results suggest a prom
 ising potential for providing operational regional Antarctic sea ice predi
 ctions on seasonal timescales.
LOCATION:British Antarctic Survey\, Zoom
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