2. Climate response associated with the Southern Annular Mode in the surroundings of Antarctic Peninsula Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

3. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Images are courtesy of the National Snow and Ice Data Center (NSIDIC), University of Colorado

4. Spatial trends of the Antarctic Sea-Ice Concentration Monthly Antarctic sea-ice drifts derived from the SMMR/SSMI over 1979-2000 (Lui et al. 2004) Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Contours are trends [%] Left: full trends Right: trends after removing SAM and ENSO (contours give the trends due to SAM and ENSO)

5. Observed SAM-related variability in SIC Regression between seasonal SAM index and SIC (HadISST1), JAS, 1980-1999 (Lefebvre et al. 2004) Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Shadows * 100 are [%]

6. Questions marks Are the last generation CGCMs representing the SAM-related variability appropriately?Are the last generation CGCMs representing the SAM-related variability appropriately? Are those models capturing the recent observed warming in the Antarctic Peninsula region?Are those models capturing the recent observed warming in the Antarctic Peninsula region? Is it possible to extract an average picture of the SAM-related variability in a warmer climate?Is it possible to extract an average picture of the SAM-related variability in a warmer climate? Is the cryosphere sending signals about climate change?Is the cryosphere sending signals about climate change? Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

7. Based on two IPCC experiments 20C3M climate of the 20th century: Historical run SRES A2 climate change experiment: initial conditions from end of 20C3M, to 2100 Time slides 1970-1999: actual climate 2070-2099: future climate Selected variables ST, SLP, near surface wind and sea-ice SAM index is the PC-1 geop(500 hPa)

8. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

9. ModelsInstitution and Country CNRM CM3MètèoFrance, France GFDL CM 2.0Geophysical Fluid Dynamics Laboratory, USA GISS ERGoddard Institute for Space Studies, USA IPSL CM4Institut Pierre Simon Laplace, France MIROC 3. 2 MedRes Center for Climate System Research, National Institute for Environmental Studies and Frontier Research Center for Global Change, Japan MRI CGCM 2.3.2Meteorological Research Institute, Japan NCAR PCMNational Center for Atmospheric Research, USA Models documentation is available at www-pcmdi.llnl.gov Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

10. Multi-model ensemble mean, SLP filed 20C3M SRES A2 SRES A2 minus 20C3M - ++ SAM Positive Phase

11. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Multi-model Control Run Contours are the multi-model mean Shadows are the spread SLP ST SIC

12. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Control run minus reference climatologies NCEP (SLP, ST, 1970-1999) and Hadley (SIC, 1982-1999) SLP ST SIC Multi-model Control Run

13. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Multi-model Annual Mean Climate Change Projections Control run minus SRES A2 experiment Present climate is 1979-1999 while future climate is 2070-2099 SLP ST SIC

14. Ice Draft data U.S. Navy submarines Ice Thickness SINTEXG spring - years 81-130 Ice Thickness SINTEXG spring - years 81-130 150 W Sea ice thickness Comparison with observations Image courtesy of Enrico Scoccimarro, INGV

15. Multi-model SAM-Positive Phase-related variability Climate change projects into the positive phase of the SAM in annual mean conditions In present climate SAM is particularly strong during the austral spring In future climate SAM is also strong during the austral spring (and summer) We are going to explore into the SAM-PP-related variability and its change in a warmer climate Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

16. Present climate SAM-PP-related variability SLP SW ST SIV

17. Future climate SAM-PP-related variability ST (present conditions) SIV ST (future conditions) SIV Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

18. Future climate SAM-PP-related variability SLP (future conditions) SW SLP (present conditions) SW Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

19. Conclusions We extracted a picture of the response of the SAM to increasing GHG in a multi-model ensemble produced in the framework of the 4 th IPCC project. In mean average, SLP climate change projects into the positive phase (PP) of the SAM. We centered the attention in the surface climate variability associated with the SAM PP and its change in a warmer climate. Particular attention is on the surroundings of the Antarctic Peninsula Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

20. Conclusions (cont.) Over the present climate slice, the multi-model ensemble mean reproduce the regional warming around the AP associated with the SAM. When increasing GHG, warming in the neighborhoods of the AP (and decreasing of sea-ice volume in the sea-ice edge region) intensifies. This result suggests that recent observed sea-ice trend around the AP could be associated to anthropogenic forcings. Surface changes in T and SI are consistent with anomalous atmospheric heat transport associated with circulation anomalies. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

21. Word of warning … The confidence in sea-ice anomalies response is limited by the reduced number of models that provides the information and the large inter-model spread.The confidence in sea-ice anomalies response is limited by the reduced number of models that provides the information and the large inter-model spread. Even if the large scale response to the SAM variability is an important driver of the AP climate change, in CGCMs the local interactions between the atmosphere, sea and sea-ice are misrepresented.Even if the large scale response to the SAM variability is an important driver of the AP climate change, in CGCMs the local interactions between the atmosphere, sea and sea-ice are misrepresented. ! If the stratospheric ozone recovers the SAM variability could also be affected (Shindell and Schmidt 2004). Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

22. We emphasize that the results need to be view with caution, given the weaknesses in the models and the uncertainties related to the future evolution of the O 3. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra

23. March 2005, preliminary results were presented at IPCC meeting, Hawaii March 2005, preliminary results were presented at IPCC meeting, Hawaii May 2005, a manuscript was submitted to GRL (in revision) May 2005, a manuscript was submitted to GRL (in revision) Following the IPCC schedule… Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra December 2005, dead-line to be in press, then to be included in the IPCC AR4  December 2005, dead-line to be in press, then to be included in the IPCC AR4

24. Penguins of the Antarctic Peninsula do not believe on climate models !

25. SAM vs ENSO related variability Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Left: SAM signal Right: ENSO signal Regression coefficients indicate changes in SIC [%] and T [°C] corresponding to 1standard deviation change in the indices Regression maps of SIC (shaded) and T at 2m (contour) anomalies, 1979-2002 (Lui et al. 2004)