First results of recently performed scenario simulations for the Baltic Sea for 1961-2099 ECOSUPPORT co-workers Annual General Assembly 15 Oct 2009 H.E.

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Presentation transcript:

First results of recently performed scenario simulations for the Baltic Sea for ECOSUPPORT co-workers Annual General Assembly 15 Oct 2009 H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University

First results of recently performed scenario simulations for the Baltic Sea for ECOSUPPORT co-workers Annual General Assembly 15 Oct 2009 H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University

First results of recently performed scenario simulations for the Baltic Sea for ECOSUPPORT co-workers Annual General Assembly 15 Oct 2009 H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University

First results of recently performed scenario simulations for the Baltic Sea for ECOSUPPORT co-workers Annual General Assembly 15 Oct 2009 H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University H.E. Markus Meier Swedish Meteorological and Hydrological Institute and Stockholm University

Regional climate models: Improving global climate scenarios Global Regional  Increased resolution → detailed regional forcing  Greater number of explicitly resolved processes

New simulations at SMHI: 1.Hindcast simulation : RCAO/ERA-40 2.Two transient simulations : RCAO/GCM New compared to BACC: no time slices, IPCC 2007, new model versions

The Rossby Centre ensemble NoAOGCM (Institute, country) Emission scena rio Horisontal resolution (km) 1Arpège (CNRM, France)A1B50 2BCM (NERSC, Norway)A1B CCSM3 (NCAR, USA)A250 5A1B50 6B250 7ECHAM4 (MPI-met, Germany)A250 8B250 9ECHAM5 (MPI-met, Germany)A250 10A1B B150 16HadCM3 (Hadley Centre, UK) ref (Q0)A1B50 17low (Q3)50 18high (Q16)50 19low (Q3)25 20IPSL-CM4 (IPSL, France)A1B50 All simulations on the ENSEMBLES grid with RCA3

NoAOGCM (Institute, country) Emission scena rio Horisontal resolution (km) 1Arpège (CNRM, France)A1B50 2BCM (NERSC, Norway)A1B CCSM3 (NCAR, USA)A250 5A1B50 6B250 7ECHAM4 (MPI-met, Germany)A250 8B250 9ECHAM5 (MPI-met, Germany)A250 10A1B B150 16HadCM3 (Hadley Centre, UK) ref (Q0)A1B50 17low (Q3)50 18high (Q16)50 19low (Q3)25 20IPSL-CM4 (IPSL, France)A1B50 Different AOGCMs All simulations on the ENSEMBLES grid with RCA3 The Rossby Centre ensemble

NoAOGCM (Institute, country) Emission scena rio Horisontal resolution (km) 1Arpège (CNRM, France)A1B50 2BCM (NERSC, Norway)A1B CCSM3 (NCAR, USA)A250 5A1B50 6B250 7ECHAM4 (MPI-met, Germany)A250 8B250 9ECHAM5 (MPI-met, Germany)A250 10A1B B150 16HadCM3 (Hadley Centre, UK) ref (Q0)A1B50 17low (Q3)50 18high (Q16)50 19low (Q3)25 20IPSL-CM4 (IPSL, France)A1B50 Different AOGCMs Different initial conditions All simulations on the ENSEMBLES grid with RCA3 The Rossby Centre ensemble

NoAOGCM (Institute, country) Emission scena rio Horisontal resolution (km) 1Arpège (CNRM, France)A1B50 2BCM (NERSC, Norway)A1B CCSM3 (NCAR, USA)A250 5A1B50 6B250 7ECHAM4 (MPI-met, Germany)A250 8B250 9ECHAM5 (MPI-met, Germany)A250 10A1B B150 16HadCM3 (Hadley Centre, UK) ref (Q0)A1B50 17low (Q3)50 18high (Q16)50 19low (Q3)25 20IPSL-CM4 (IPSL, France)A1B50 Different AOGCMs Different initial conditions Different model formulation (GCM) All simulations on the ENSEMBLES grid with RCA3 The Rossby Centre ensemble

NoAOGCM (Institute, country) Emission scena rio Horisontal resolution (km) 1Arpège (CNRM, France)A1B50 2BCM (NERSC, Norway)A1B CCSM3 (NCAR, USA)A250 5A1B50 6B250 7ECHAM4 (MPI-met, Germany)A250 8B250 9ECHAM5 (MPI-met, Germany)A250 10A1B B150 16HadCM3 (Hadley Centre, UK) ref (Q0)A1B50 17low (Q3)50 18high (Q16)50 19low (Q3)25 20IPSL-CM4 (IPSL, France)A1B50 Different AOGCMs Different initial conditions Different model formulation (GCM) Different emission scenarios All simulations on the ENSEMBLES grid with RCA3 The Rossby Centre ensemble

NoAOGCM (Institute, country) Emission scena rio Horisontal resolution (km) 1Arpège (CNRM, France)A1B50 2BCM (NERSC, Norway)A1B CCSM3 (NCAR, USA)A250 5A1B50 6B250 7ECHAM4 (MPI-met, Germany)A250 8B250 9ECHAM5 (MPI-met, Germany)A250 10A1B B150 16HadCM3 (Hadley Centre, UK) ref (Q0)A1B50 17low (Q3)50 18high (Q16)50 19low (Q3)25 20IPSL-CM4 (IPSL, France)A1B50 Different AOGCMs Different initial conditions Different model formulation (GCM) Different emission scenarios Different horizontal resolution All simulations on the ENSEMBLES grid with RCA3 The Rossby Centre ensemble

Biases in the recent past climate ( ): winter (DJF) mean temperature and MSLP Source: Erik Kjellström, SMHI

Biases in the recent past climate ( ): summer (JJA) mean temperature and MSLP Source: Erik Kjellström, SMHI

Seasonal mean 2m air temperature at Gotland Deep – downscaling results using RCA Observations

Seasonal mean 10m wind speed at Gotland Deep – downscaling results using RCA Observations

Seasonal mean precipitation at Gotland Deep – downscaling results using RCA Observations

Mean 2m air temperature (winter), ObservationsRCA/ERA40RCA/ECHAM5

Mean 2m air temperature (summer), ObservationsRCA/ERA40RCA/ECHAM5

Mean 2m air temperature (summer), ObservationsRCAO/ERA40RCAO/ECHAM5

Climate change ( vs ): winter (DJF) mean temperature and MSLP Source: Erik Kjellström, SMHI

Climate change ( vs ): summer (JJA) mean temperature and MSLP Source: Erik Kjellström, SMHI

Mean seasonal cycles of SST (in °C) averaged for the Baltic Sea Black: Hindcast Red: RCAO/ECHAM5 A1B Blue: RCAO/HadCM3 A1B Solid: Control period Dashed: Scenario period

Filtered runoff (m 3 /s) Black: Observations Red: RCAO/ECHAM5 A1B Blue: RCAO/HadCM3 A1B

Volume averaged, annual mean temperature Volume averaged, annual mean salinity Black: Hindcast Red: RCAO/ECHAM5 A1B Blue: RCAO/HadCM3 A1B

Changes of bottom oxygen concentrations (in ml/l) RCAO/HadCM3 A1B Annual meanWinter (DJF)Summer (JJA)

Annual meanWinter (DJF)Summer (JJA) Changes of bottom oxygen concentrations (in ml/l) RCAO/ECHAM5 A1B

Annual mean phytoplankton concentration (in mgChl m -3 ) vertically averaged over the upper 10 m HadCM3 A1B Present climate Future climate

Annual mean phytoplankton concentration (in mgChl m -3 ) vertically averaged over the upper 10 m ECHAM5 A1B Present climate Future climate

Summary 1.The quality of the GCMs differs significantly. As a starting point we have selected ECHAM5 and HadCM3. We performed transient simulations with realistic control climate for the Baltic Sea. 2.Improved summer SSTs using the coupled RCAO model. 3.We found increased runoff but the mean wind speed changes are statistically not significant. Hence salinity decreases are smaller than in earlier scenario simulations. 4.Overall oxygen decrease but slight increases in ECHAM5 driven scenario simulations in intermediate depths. 5.Increased phytoplankton concentrations in both scenario simulations. 6.Next steps: runoff from a hydrological model HYPE, higher resolution in RCA (25 km)

First results based on RCO-SCOBI and IPCC 2001: 1.Future climate might be characterized by increased water temperatures, increased mixing, and (reduced loads) in the Baltic Proper 2.Increased water temperatures => decreased oxygen concentrations in all regions 3.Increased mixing => increased oxygen concentrations below the halocline => reduced winter DIP and reduced denitrification (i.e. increased DIN) 4.Increased water temperature and increased mixing => increased (decreased) phytoplankton concentrations in the south-western (northern) Baltic Proper 5.In future climate the ”business-as-usual in agricultural practices” scenario may have larger impacts than in present climate 6.The BSAP will likely reduce the phytoplankton concentrations also in future climate