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Zeng-Zhen Hu (1) Svetlana I. Kuzmina (2) Lennart Bengtsson (3) David M. Holland (4)

Arctic S ea- I ce C hange and Its C onnection with Arctic C limate C hange in CMIP 2 S imulations. Zeng-Zhen Hu (1) Svetlana I. Kuzmina (2) Lennart Bengtsson (3) David M. Holland (4) (1) Center for Ocean-Land-Atmosphere Studies 4041 Powder Mill Road, Suite 302 , Calverton, MD 20705

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Zeng-Zhen Hu (1) Svetlana I. Kuzmina (2) Lennart Bengtsson (3) David M. Holland (4)

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  1. Arctic Sea-Ice Changeand ItsConnectionwith Arctic Climate Change inCMIP2Simulations Zeng-Zhen Hu (1) Svetlana I. Kuzmina (2) Lennart Bengtsson (3) David M. Holland (4) (1) Center for Ocean-Land-Atmosphere Studies 4041 Powder Mill Road, Suite 302, Calverton, MD 20705 E-amil: hu@cola.iges.org (2) Nansen International Environmental and Remote Sensing Center Bolshaya Monetnaya Street, 26/28, St. Petersburg, 197101, Russia (3) Max-Planck-Institute for Meteorology Bundesstrasse 55, Hamburg, D-20146, Germany; andEnvironmental Systems Science Centre,Reading, UK (4) Center for Atmosphere-Ocean Science Courant Institute of Mathematical Sciences, New York University 251 Mercer Street, New York, NY 10012 USA

  2. More and More People Believes that Global Warming Is True From: http://www.giss.nasa.gov/research/observe/surftemp/2001fig1.gif

  3. Possible Global Warming Signal in Observed Sea-Ice Change(Decreasing is dominated)

  4. However, Uncertainty in CGCM Simulating the Current Climate Is Still Large, Particularly in High Latitudes. IPCC2001, Figure 8.2: December-January-February climatological surface air temperature in K simulated by the CMIP1 model control runs.

  5. How Can People Believe the Simulated Future Climate Change ?! IPCC 2001, Figure 9.6: (a) The time evolution of the globally averaged temperature change relative to the years (1961 to 1990) of the SRES simulations A2 (top) and B2 (bottom) (Unit: °C). See Table 9.1 for more information on the individual models used here. (b) The timeevolution of the globally averaged precipitation change relative to the years (1961 to 1990) of the SRESsimulations A2 (top) and B2 (bottom) (Unit: %).

  6. What Cause the Uncertainty ? • It is the model differences, including: (1) Model dynamic frame (2) Model physical processes cloud – radiation atmosphere chemistry land surface-hydrology sea – ice so on Among these processes, sea-ice is one of very important sources resulting in the uncertainty!

  7. Objectives • The two-dimensionaldistribution of the mean and uncertainty of Arctic sea ice, and climate changes at the time of CO2 doubling and theirinterconnection • The sensitivity of Arctic surface air temperature(SAT) change to sea-ice area change in different models andin various periods of forced integrations of the CMIP models • The possible influence of CO2doubling on the north-south SLP gradient and the mean westerly winds • The differences resulting from model-dependent physics

  8. Observational & CMIP2 Data 1. Observations 1x1 sea-ice concentration in the Arctic, 1953-1995 (Chapman and Walsh, 1991); seasonal 1x1 sea-ice thickness in 1960-1982 (Bourker and Garrett, 1987) 2. Models 14 CMIP2 CGCMs (http://www-pcmdi.llnl.gov/cmip): (see next page) 3. Experiments CMIP2 (http://wwwpcmdi.llnl.gov/cmip): Control run: 1-80 years Scenario run:Standard gradual increase (1 % per year compound) in CO2, 1-80 years; CO2 doubling at 60-80 years.

  9. CMIP2 Models

  10. Surface Temperature (SAT) & Sea-Ice Thickness (SIT) Are Cooperated:Larger (smaller) warming/uncertainty of SAT is tied up with larger (smaller) reduction/uncertainty of SIT

  11. Surface Temperature (SAT) & Sea-Ice Concentration (SIC) Are Also Cooperated:Larger (smaller) warming/uncertainty of SAT is associated with larger (smaller) reduction/uncertainty of SIC

  12. NH Sea-Ice Area & Arctic SAT:(1) Sensitivity (-2.0 to 0.5 C/M km**2) is varied from model to model(2) Sensitivity is different even in different period of a transient integration;(3) Colder (warmer) Arctic climate may favor higher (lower) sensitivity;(4) Sensitivity seems not related to initial sea-ice area.

  13. Sensitivity & the changes in poleward ocean heat transport (Holland and Bitz, 2003, Clim. Dyn.):MRI model: lowest sensitivity corresponds to strongest poleward ocean heat transportNCAR model: largest sensitivity corresponds to weakest poleward ocean heat transport

  14. Projected SLP & Sea-Ice Thickness Changes:(1) Larger (smaller) decrease /uncertainty of SLP is associated with larger (smaller) reduction/uncertainty of SIT;(2) The north-south SLPgradient and the mean westerly winds are enhanced.

  15. Differences resulting from model physics:Both the mean and intermodel spread patternsshow considerable differences in some regions between models with and without flux adjustment.

  16. Main Results • At the time of CO2 doubling, Arctic SAT increases 1 to 5 C, SIT decreases 0.3-1.8m, SIC reduces more than 10%. • Values of thesensitivity of Arctic surface airtemperature change with respect to sea-ice area change vary from -2.0 to -0.5 C/10^6 km^2 for most CMIP2 models.The sensitivity is modeldependent. For some models, the sensitivity is different evenin different period of a transient integration. • Colder (warmer) Arctic climatemay favor higher (lower) sensitivity. That may be associated with the intensity of poleward ocean heat transport. • The north-south SLP gradient and the mean westerly winds are enhancedatthe time of CO2 doubling. • There are considerable differences between models with andwithout flux adjustment in some regions. • There are NO significant and consistent sensitivity differences between the mean simulations with and without sea-ice dynamics. • Both SIT & SIC are sensitive to the increasein greenhouse gas concentrations and connected with SAT & SLP changes in the Arctic. • Simulated mean and intermodel spread patterns of SAT change are similar to those of SIT, SIC, and SLP changes, implying that the mean and uncertainty of projected Arctic climate change may be largely affected by the interaction between sea-ice and the atmosphere.

  17. Further Information and Acknowledgements Further Information : Web page: ftp://grads.iges.org/pub/hu/paper/2004HUetal_JGR.pdf (JGR-Atmosphere, 109, D10106, 2004) E-mail: hu@cola.iges.org; Acknowledgements : The authors thank E. Schneider, R. Stouffer, B. Huang, and D.Strausfor their discussion and suggestions, and also B. Wu and J. Adams fortheir assistance in processing the observed sea-ice data. This work was supported by grant from the U. S.Department ofEnergy (De-FG02-01ER63256). DMHacknowledges support fromthe Office of Polar Programs of the National Science Foundationgrants OPP-9901039 and OPP-0084286. All CMIP2 modeling groups are acknowledged for making the simulations available.CMIP2 is supported and the model data are distributed by theProgram for Climate Model Diagnosis and Intercomparison (PCMDI)at the Lawrence Livermore National Laboratory (LLNL).

  18. END • THANKS

  19. CMIP2 models simulate the mean sea-ice concentrations reasonably well

  20. CMIP2 models simulate the mean sea-ice thickness NOT very well

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