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Arctic climate and future scenarios

Arctic climate and future scenarios. Ola M. Johannessen and Mats Bentsen. Nansen Environmental and Remote Sensing Center. Arctic Climate System. Warm surface waters. Cold Arctic waters. Cold deep waters. River runoff. Warming Ice/snow melting Increase run-off

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Arctic climate and future scenarios

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  1. Arctic climate and future scenarios Ola M. Johannessen and Mats Bentsen Nansen Environmental and Remote Sensing Center

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

  3. 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 thesea-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.

  4. 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.

  5. A BCM simulation with natural forcing Courtesy: Odd HelgeOtterå

  6. A BCM simulation with natural and anthropogenic forcing Courtesy: Odd HelgeOtterå

  7. Temperature Johannessen et al. 2004

  8. BCM simulations of 20th century with natural forcing Courtesy:LinglingSuo and Odd HelgeOtterå

  9. BCM simulations of 20th century with all forcings Courtesy:LinglingSuo and Odd HelgeOtterå

  10. Comparison of BCM simulations and observations Courtesy:LinglingSuo and Odd HelgeOtterå

  11. 960 ppm 960 ppm 550 ppm 550 ppm CO2 (ppm) CO2 (ppm) 280 ppm 280 ppm 200 ppm 200 ppm 5.8°C 5.8°C Temperatur (oC) Temperatur (oC) 0°C 0°C 1.4°C 1.4°C -8°C -8°C 850,000 år 1850 650,000 år 1850 2008 2100 Observed and expected atmospheric content of CO2 About 20% of the anthropogenic CO2 emissions will remain in the atmosphere for more than 1000 years The CO2 emissions of today will continue to have an impact on the climate for a long time • 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 850,000 år

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

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

  14. Bergen Climate Model with carbon cycle (BCM-C) 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 CO2 concentration is updated annually.

  15. Surface temperature with A2 scenario CO2emissions Courtesy: Jerry Tjiputra

  16. Ocean and land CO2 uptake with A2 scenario emissions Courtesy: Jerry Tjiputra

  17. 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.

  18. 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.

  19. NorESM framework and model components Atmospheric chemistry CAM CICE CLM River routing Components in blue communicate trough a coupling component. Components inred are subroutines of blue components. MICOM HAMOCC

  20. 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.

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