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Climate response associated with the Southern Annular Mode in the surroundings of Antarctic Peninsula Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Images are courtesy of the National Snow and Ice Data Center (NSIDIC), University of Colorado Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra 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) • Contours are trends [%] • Left: full trends • Right: trends after removing SAM and ENSO (contours give the trends due to SAM and ENSO) Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Observed SAM-related variability in SIC Regression between seasonal SAM index and SIC (HadISST1), JAS, 1980-1999 (Lefebvre et al. 2004) • Shadows * 100 are [%] Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Questions marks • Are the last generation CGCMs representing the SAM-related variability appropriately? • 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 the cryosphere sending signals about climate change? Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra 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) Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Models documentation is available at www-pcmdi.llnl.gov Models Institution and Country CNRM CM3 MètèoFrance, France GFDL CM 2.0 Geophysical Fluid Dynamics Laboratory, USA GISS ER Goddard Institute for Space Studies, USA IPSL CM4 Institut 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 2.3.2 Meteorological Research Institute, Japan NCAR PCM National Center for Atmospheric Research, USA Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Multi-model ensemble mean, SLP filed 20C3M SRES A2 SRES A2 minus 20C3M + - + SAM Positive Phase 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 Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra SIC Multi-model Control Run Control run minus reference climatologies NCEP (SLP, ST, 1970-1999) and Hadley (SIC, 1982-1999) SLP ST Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra SIC 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 Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra SIC Sea ice thickness Comparison with observations Image courtesy of Enrico Scoccimarro, INGV Ice Thickness SINTEXG spring - years 81-130 Ice Draft data U.S. Navy submarines Ice Thickness SINTEXG spring - years 81-130 150 W 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 Present climate SAM-PP-related variability SLP SW ST SIV Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Future climate SAM-PP-related variability ST ST (future conditions) (present conditions) SIV Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra SIV Future climate SAM-PP-related variability SLP SLP (present conditions) (future conditions) SW Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra SW 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 4th 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 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 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. • 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 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 O3. Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra Following the IPCC schedule… March 2005, preliminary results were presented at IPCC meeting, Hawaii May 2005, a manuscript was submitted to GRL (in revision) December 2005, dead-line to be in press, then to be included in the IPCC AR4 Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra SAM vs ENSO related variability Regression maps of SIC (shaded) and T at 2m (contour) anomalies, 1979-2002 (Lui et al. 2004) •Left: SAM signal • Right: ENSO signal Regression coefficients indicate changes in SIC [%] and T [°C] corresponding to 1standard deviation change in the indices Andrea F. Carril, Claudio G. Menéndez and Antonio Navarra