1. CLIMARES, NERSC, October 2009 Arctic climate and future scenarios Ola M. Johannessen and Mats Bentsen Nansen Environmental and Remote Sensing Center

2. CLIMARES, NERSC, October 2009 Arctic Climate System Warm surface waters Cold Arctic waters Cold deep waters River runoff 100 Gt/year = 0.3 mm/yr Warming Ice/snow melting Increase run-off Wildcard - Greenland Ice Sheet Deep water formation conveyour belt Strong natural variablity

3. CLIMARES, NERSC, October 2009

4. Bergen Climate Model (BCM) Developed by the Nansen Center, the University of Bergen, and the Bjerknes Center. Development began in 1999 and it contributed results to CMIP3 (used for the IPCC AR4 assessment report). Model components: Atmosphere: Action de Recherche Petite Echelle Grande Echelle (ARPEGE, research project on small and large scales). Land: A simple soil model incorporated in ARPEGE. Sea-ice: Originally the NERSC sea-ice model was used. Recently the sea- ice model GELATO, developed at Meteo France, has been incorporated. Both are handled as a subroutine call from MICOM. Ocean: Miami Isopynic Coordinate Ocean Model (MICOM) extensively modified at the Nansen Center. Atmospheric chemistry: Only prescribed concentrations of chemical constituents. Ocean Carbon Cycle: None. Coupler: OASIS 2.2. Ice sheet: None.

5. CLIMARES, NERSC, October 2009 Status of Bergen Climate Model BCM is the only Norwegian climate model in this class of model complexity. BCM is still needed in many projects. Modifications and tuning of BCM and replacing the sea-ice model with GELATO have eliminated a cold bias of surface temperature, improved sea-ice realism, and reduced drift compared to IPCC AR4 simulations.

6. CLIMARES, NERSC, October 2009 A BCM simulation with natural forcing Courtesy: Odd Helge Otterå

7. CLIMARES, NERSC, October 2009 A BCM simulation with natural and anthropogenic forcing Courtesy: Odd Helge Otterå

8. CLIMARES, NERSC, October 2009 Temperature Johannessen et al. 2004

9. CLIMARES, NERSC, October 2009

10. BCM simulations of 20 th century with natural forcing Courtesy: Lingling Suo and Odd Helge Otterå

11. CLIMARES, NERSC, October 2009 BCM simulations of 20 th century with all forcings Courtesy: Lingling Suo and Odd Helge Otterå

12. CLIMARES, NERSC, October 2009 Comparison of BCM simulations and observations Courtesy: Lingling Suo and Odd Helge Otterå

13. CO 2 (ppm) 0°C -8°C 280 ppm 200 ppm 5.8°C 1.4°C 960 ppm 550 ppm Temperatur ( o C) CO 2 (ppm) 0°C -8°C 280 ppm 200 ppm 5.8°C 1.4°C 960 ppm 550 ppm Temperatur ( o C) 650,000 år 185020082100 Today:Highest level in 850.000 year Year 2100:Highest level in 20 million years The increase is mainly caused by (about 80%) burning of coal, oil, and gas; the rest is mainly caused by deforestation and changes in land use About 20% of the anthropogenic CO 2 emissions will remain in the atmosphere for more than 1000 years The CO 2 emissions of today will continue to have an impact on the climate for a long time 850,000 år 1850 Observed and expected atmospheric content of CO 2 850,000 år

14. Future climate scenarios IPCC 2007 + 3 ºC: Irreversible changes + 2 ºC compared to 1850: EU target

15. Arctic Sept Sea Ice Extent Stroeve et al. 2007 Red: observed Black: model esemble

16. CLIMARES, NERSC, October 2009 In collaboration with NERSC, the carbon cycle group at the Bjerknes Center and the University of Bergen have extended BCM with the Hamburg Ocean Carbon Cycle Model (HAMOCC) and the Lena-Potsdam-Jena land carbon cycle model (LPJ) to form BCM-C. Atmospheric CO 2 concentration is updated annually. Bergen Climate Model with carbon cycle (BCM-C)

17. CLIMARES, NERSC, October 2009 Surface temperature with A2 scenario CO 2 emissions Courtesy: Jerry Tjiputra

18. CLIMARES, NERSC, October 2009 Ocean and land CO 2 uptake with A2 scenario emissions Courtesy: Jerry Tjiputra

19. CLIMARES, NERSC, October 2009 From BCM to a Norwegian Earth System Model Desire to unify climate model and analysis tools in Norway to establish a common ESM. To meet demands in various projects and IPCC AR5 scenario integrations, the model system should include biochemical cycles and a more sophisticated atmospheric chemistry. Be able to exploit the computing recourses available now and in the near future. The development plan for ARPEGE was not satisfactory:  No finite volume version planned or other means to improve conservation.  Small development staff.  No plan to include interactive atmospheric chemistry.

20. CLIMARES, NERSC, October 2009 NorESM framework and model components NorESM is based on a development version of CCSM4 from the National Center for Atmospheric Research (NCAR), Boulder, USA. Model components: Atmosphere: Community Atmosphere Model (CAM 3.5.39). Land: Community Land Model (CLM 3.6.02). Sea-ice: Community Sea-Ice Model (CSIM/CICE 4). Ocean: Miami Isopynic Coordinate Ocean Model (MICOM) extensively modified at the Nansen Center. Atmospheric chemistry: Chemistry-aerosol-cloud package in CAM by University of Oslo and met.no. Ocean Carbon Cycle: Hamburg Model of Ocean Carbon Cycle (HAMOCC) adopted for use with an isopycnic ocean model. Coupler: CPL 7. Ice sheet: Currently none, but NCAR and LANL are working on this.

21. CLIMARES, NERSC, October 2009 CLM CAM CICE HAMOCC MICOM Atmospheric chemistry Components in blue communicate trough a coupling component. Components in red are subroutines of blue components. River routing NorESM framework and model components

22. CLIMARES, NERSC, October 2009 Coupled Model Intercomparison Project 5 (CMIP5) This project will produce simulations that will form the basis of climate modeling information to the IPCC AR5 report planned for 2013. Two distinct focuses for proposed experiments: Long term simulations (century time-scale). Near-term simulations (decadal time-scale). The long term simulations can be grouped as follows: Control, historical and AMIP simulations. Future climate projections, forced by prescribed concentration scenarios. Past and future climate simulation, forced by prescribed emissions. Simulations for feedback analysis and understanding model differences. Ensembles of historical and AMIP simulations. Simulations for climate change detection and attribution studies.