1. Seasonal Forecast of Antarctic Sea Ice
Xiaojun Yuan and Dake Chen
Lamont-Doherty Earth Observatory of Columbia University
WCRP Workshop on Seasonal Prediction, 4-7 June, 2007
Barcelona, Spain

2. Outline
What influence Antarctic Sea Ice Variability at Seasonal Time Scale?
Remote influence
Regional impact
The Statistical Forecast Model
The Markov model
Validation and Forecast
Summary
Outstanding Questions

3. Temperature Differences between El Nino and La Nina Composites~ ~
Temperature Differences between El Nino and La Nina Composites
Between 1980 and 2002
SAT
EL Nino years: 82-83, 86-87, 87-88, 91-92, 97-98
La Nina years: 84-85, 85-86, 88-89, 95-96, 98-99, 99-00
SST
Liu, et al. 2002

4. Yuan 2004

5. Differences between El Nino and La Nina Composites
Sea Ice
SAT
SLP El Nino Composite
SLP La Nina Composite
Yuan 2004

7. Yuan, 2004

10. Ice lags 2-month
Yuan, 2005

11. Percentage of grid points with correlation significant at 99% confidence level.
ice lag
ice lead
Yuan, 2005

12. Seasonal Forecast of Antarctic Sea Ice
A linear Markov Model
Sea ice
Surface air temperature
Sea level pressure
Surface winds
( satellite and reanalysis data)
Multivariate empirical orthogonal functions (MEOF)
PCs of leading modes are used to train the seasonally dependent transition matrices
The Markov model predicts the PCs from one month to the next.
Eigenvectors of leading modes from MEOFs
Seasonal sea ice forecast
Chen and Yuan, 2004

14. Chen and Yuan, 2004

17. Chen and Yuan, 2004

18. Chen and Yuan, 2004

19. Current Sea Ice Forecast

20. Summary
Antarctic sea ice in the western hemisphere is predictable at season time scale with reasonable good skill.
The predictability comes from the spatially coherent large climate variability in the Ocean-Atmosphere-ice coupled system.
Outside of the Antarctic Dipole region, climate variability is not distinct or coherent, therefore no good prediction skill exists.
The best prediction skill is found in the large climate action centers associated with ENSO and dominant high latitude climate modes, and in winter.

21. Outstanding Questions
Can this predictability in southern high latitudes be useful to extrapolar seasonal forecast?
The magnitude of the ADP anomaly is large, the spatial scale is half hemisphere, temporal scale of the anomaly is season and longer.
How do the polar processes feedback to extra-polar climate variability?
Understanding the mechanisms of the feedback of polar processes to extrapolar climate variability leads to a better integration of cryosphere into the global climate system.