SUPPLEMENTARY INFORMATION

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1 SUPPLEMENTARY INFORMATION DOI: /NGEO1189 Different magnitudes of projected subsurface ocean warming around Greenland and Antarctica Jianjun Yin 1*, Jonathan T. Overpeck 1, Stephen M. Griffies 2, Aixue Hu 3, Joellen L. Russell 1, and Ronald J. Stouffer 2 1. Department of Geosciences, University of Arizona 2. Geophysical Fluid Dynamic Laboratory, NOAA 3. National Center for Atmospheric Research * Corresponding author address: Dr. Jianjun Yin Department of Geosciences, University of Arizona Tucson, AZ yin@ .arizona.edu; Phone: (520) NATURE GEOSCIENCE 1

2 1. Oceanic Heat Transport in the GFDL CM2 Models The performance of the GFDL CM2 in simulating the climate system has been systematically evaluated 1-4. Various metrics indicate that the GFDL CM2 is among the best models in many aspects 5. The ocean components of CM2.0 and CM2.1 use similar numerical methods and physical parameterizations. In particular, advective tracer transport and vertical mixing processes are identical. Both ocean models parameterize subgrid scale eddy processes via diffusive and advective (or skew diffusive) operators oriented along isopycnal surfaces or neutral surfaces 6,7. The heat flux arising from such neutral physics processes is proportional to, (S1) where the mixing tensor acting on the gradient of the tracer concentration is. (S2) Here, is the neutral diffusion coefficient, is the skew-diffusivity coefficient, and S is the magnitude of the neutral slope with components and. CM2.0 sets the neutral diffusivity ( ) equal to the eddy advection diffusivity, whereas CM2.1 sets the diffusivity equal to a constant 600 m 2 s -1. In both models, the skew diffusivity ( ) is proportional to the vertically averaged horizontal density gradient 2

3 , (S3) where is a dimensionless tuning parameter set to 0.07, L a length scale set to 50 km, a buoyancy frequency set to s -1, g is the gravitational acceleration equal to 9.8 m s -1, 1035 kg m -3 is the reference density for the Boussinesq approximation, and is the average of the horizontal density gradient taken over the depth range from 100 to 2000 m. Equation (1) gives the vertically integrated heat transport by advection and parameterized neutral physics processes. 2. Meltwater Experiments with the NCAR CCSM3 Model Similar to the GFDL CM2, the NCAR CCSM3 is also a leading fully coupled atmosphere-ocean general circulation model 8. The impact of additional meltwater from polar ice sheets has been investigated using CCSM3 9,10. The baseline experiment is the standard SRES A1B scenario run without additional meltwater from polar ice sheets. In the subsequent experiments, additional meltwater from the GIS or WAIS is added uniformly in the surrounding oceans of polar ice sheets. The initial meltwater flux at year 2000 is set to 0.01 Sv and Sv (1 Sv =10 6 m 3 /s) for the GIS and WAIS melt experiments, respectively. The meltwater flux increases by 1% or 3% per year compound until 2099, representing the range of possible ice sheet melt. The impact of the additional meltwater on the climate and ocean system can be studied by comparing these meltwater experiments with the baseline experiment (Fig. S9). 3

4 Supplementary Material References 1. Delworth, T. L. et al. GFDL s CM2 global coupled climate models. Part I: Formulation and simulation characteristics. J. Clim. 19, (2006). 2. Gnanadesikan, A. et al. GFDL s CM2 global coupled climate models. Part II: The baseline ocean simulation. J. Clim. 19, (2006). 3. Wittenberg, A. T. et al. GFDL s CM2 global coupled climate models. Part III: Tropical Pacific climate and ENSO. J. Clim. 19, (2006). 4. Stouffer, R. J. et al. GFDL s CM2 global coupled climate models. Part IV: Idealized climate response. J. Clim. 19, (2006). 5. Gleckler, P. J., Taylor, K. E. & Doutriaux, C. Performance metrics for climate models. J. Geophys. Res. 113, D06104 (2008). 6. Griffies, S. M. et al. Formulation of an ocean model for global climate simulations. Ocean Science 1, (2005). 7. Griffies, S. M. The Gent-McWilliams skew flux. J. Phys. Oceanogr. 28, (1998). 8. Collins, W. D. et al. The Community Climate System Model: CCSM3. J. Clim. 19, (2006). 9. Hu, A., Meehl, G. A., Han, W. & Yin, J. Transient response of the MOC and climate to potential melting of the Greenland Ice Sheet in the 21st century. Geophys. Res. Lett. 36, L10707 (2009). 10. Hu, A., Meehl, G. A., Han, W. & Yin, J. Effect of the potential melting of the Greenland Ice Sheet on the meridional overturning circulation and global climate in the future. Deep-Sea Res. II, doi: /j.dsr (2011). 4

5 Table S1. The IPCC Fourth Assessment Report (AR4) models with the simulations and projections of ocean temperature available at PCMDI. The simulations of the upper ocean temperature ( m) during are compared to the observation (ref. 18). The root-mean-square-error (RMSE) is calculated for each model. The models with RMSE greater than 4 and with problems at high latitudes (IAP FGOALS) are not used. Totally 19 AR4 models are chosen for the ensemble mean projections of the 21 st century. Data from 13 AR4 models are available for the 22 nd century projections. Model Institution Root-Mean-Square- Error ( o C) BCCR BCM2.0 Bjerknes Centre for Climare Research, Norway 1.70 CCCMA CGCM3.1 Canadian Centre for Climate Modeling Analysis, Canada 1.70 CCCMA CGCM3.1 T63 Canadian Centre for Climate Modeling Analysis, Canada 1.43 CNRM CM3 Centre National de Recherches Meteorogiques, France 2.21 CSIRO MK3.0 Commonwealth Scientific and Industrial Research Organisation, Australia 2.18 CSIRO MK3.5 Commonwealth Scientific and Industrial Research Organisation, Australia 1.94 GFDL CM2.0 Geophysical Fluid Dynamics Laboratory, USA 1.83 GFDL CM2.1 Geophysical Fluid Dynamics Laboratory, USA 1.37 GISS AOM Goddard Institute for Space Studies, USA 4.13 GISS EH Goddard Institute for Space Studies, USA 2.12 GISS ER Goddard Institute for Space Studies, USA 4.64 IAP FGOALS Institute of Atmospheric Physics, China 1.83 INGV ECHAM4 National Institute of Geophysics and Volcanology, Italy 1.99 IPSL CM4 Institut Pierre Simon Laplace, France 1.63 MIROC3.2 HIRES University of Tokyo, Japan 1.80 MIROC3.2 MEDRES University of Tokyo, Japan 1.57 MIUB ECHO G University of Bonn, Meteorological Administration, Germany/Korea 1.60 MPI ECHAM5 Max Planck Institute for Meteorology, Germany 2.41 MRI CGCM2.3.2 Meteorological Research Institute, Japan 1.69 NCAR CCSM3 National Center for Atmospheric Research, USA 1.63 NCAR PCM National Center for Atmospheric Research, USA 2.42 UKMO HADCM3 Hadley Centre for Climate Prediction and Research, UK

6 Figure S1. Global map of recent observed and ensemble mean projections of subsurface ( m) ocean warming ( o C) for the 21st and 22nd century under the A1B scenario. a, Observed annual mean ocean temperature 18 (shading) and the bias of the ensemble mean simulation by 19 AR4 models during (contours). b, Projected ocean warming by 19 AR4 models during c, Projected ocean warming by 13 AR4 models during Stippling in b and c indicates the ensemble mean divided by the ensemble standard deviation is less than 1, identifying regions where the models show less agreement.

7 Figure S2. Individual model projections of the ocean warming (oc) in m surrounding Greenland during The results are from the A1B scenario runs. See Table S1 for model information.

8 Figure S2. (Continued) Individual model projections of the subsurface ocean warming (oc) in m surrounding Greenland during

9 Figure S3. Changes in total surface heat flux (W/m 2 ) over the 21 st century. Upper panels: surface heat flux during ; lower panels: surface heat flux anomalies during Positive values indicate downward heat fluxes. Vectors indicate ocean currents (m/s) in m.

10 Figure S4. Ocean temperature changes ( o C) over the 21 st century. Upper Panels: 73 o N; middle panels: 63 o N; lower panels: zonal mean in the Southern Ocean. Contours show the ocean temperature during Shading shows the temperature anomalies during

11 Figure S5. Changes in volume transport by ocean currents over the 21 st century. The time series include the East Greenland Current (EGC), West Greenland Current (WGC), Atlantic Meridional Overturning Circulation (AMOC), Southern Ocean Meridional Overturning (SOMOC), North Atlantic Subpolar Gyre (NA SPG) and Antarctic Circumpolar Current (ACC). The EGC and WGC are the transport in the upper 500 m across Fram and Davis Strait, respectively. The indices for the AMOC and SOMOC are, respectively, defined as the maximum overturning streamfunction at 45 o N in the Atlantic and south of 30 o S. The ACC index is the transport across the Drake Passage. The SPG index is the extrema of the barotropic streamfunction in the gyre circulation regions compared to a fixed point at the gyre edge.

12 Figure S6. Sea ice change over the 21st century. Shading shows the annual mean sea ice thickness anomalies (m) during compared to Black and red lines indicate the annual mean sea ice extent (ice concentration greater than 15%) during and , respectively.

13 Figure S7. Wind Stress anomalies in the CM2.0 and CM2.1 projections. Upper and middle panels: solid lines show wind stress and dashed lines show the anomalies. Bottom panels: zonal mean of heat transport (TW) by advection in CM2.1. Vectors show heat transport and contours are isopycnic surfaces (σ o ). Black and red colors indicate the results during and , respectively. Box indicates the region of the enhanced upwelling of cold deep waters.

14 Figure S8. Barotropic streamfumction (Sv) in the Southern Ocean. Black color shows the values during Red color shows the values during

15 Figure S9. Feedback of meltwater on subsurface ocean warming. The simulations are performed using the NCAR CCSM3 climate model. The results show the ocean temperature anomalies induced by additional meltwater in the A1B scenario run. Upper panel: 1% increase rate in Greenland melt; middle panel: 3% increase rate of Greenland melt; lower panel: 3% increase rate of Antarctic melt. The additional meltwater only has a very small impact (±0.1 o C) on the subsurface warming around Greenland and Antarctica. See ref. 28 for details.