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Hélène Côté and Daniel Caya Climate Simulations Group Consortium Ouranos Variability and Extremes in the CRCM Development of Scenarios of Climate Variability.

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Presentation on theme: "Hélène Côté and Daniel Caya Climate Simulations Group Consortium Ouranos Variability and Extremes in the CRCM Development of Scenarios of Climate Variability."— Presentation transcript:

1 Hélène Côté and Daniel Caya Climate Simulations Group Consortium Ouranos Variability and Extremes in the CRCM Development of Scenarios of Climate Variability and Extremes: Current Status and Next Steps Victoria, October 2003

2 Outline Current status of CRCM –Policy Run II vs Policy Run III –Production runs with version –Preliminary results (the first 5 years of the 25-year run) –Next operational version: CRCM –Development of CRCM 4.0 Variability issues in regional climate modelling Modelling the extremes –The data we have –What we plan to do Validation issues How to improve the model

3 From Policy Run II to Policy Run III vs RadiationFouquart and Morcrette unchanged Land surfaceBeautified Bucket ( 1 layer + force- restore) unchanged ConvectionKain-Fritsch (1990)Bechtold-Kain-Fritsch (Bechtold et al 2001) CloudsF (relative humidity)F (relative humidity) + convective clouds Boundary layerBulk transfert, mixing lengh-Kunchanged Atmospheric composition Specified [O 3 ] [CO 2 ]unchanged NestingDavies relaxationSpectral nudging ( Biner et al 2000, Denis et al) SSTsFrom Monthly GCM valuesFrom Daily GCM values or AMIP obs. Lake ModelNoMixed-layer (Goyette et al 2000) Leap-yearNoYes New featuresImplicit treatment of Tg Atmospheric budget

4 Current Simulations Configuration 45 km grid point spacing 193 x 145 grid points 29 vertical levels Lid: 30 km Archival : every 6 hours (pcp every timestep) Transient CO2 Spinup period: 2 years Approx. 1 month CPU time per simulated year …. 5.7Gb of model outputs per simulated month…. Topography (m) Policy Run II domain

5 Current Simulations Driving data OceanPeriodSpectral nudging CRCMDone (14/10/03) NRA-1AMIP yes / 364 NRA-1AMIP no / 364 CGCM2 i s92a CGCM yes / 364 CGCM2 is92a CGCM yes / 364

6 CO 2 Equivalent Concentration IS92aCRCM –CRCM CGCM2, ,

7 Precipitation rate (mm/day) 5-year mean: Summer CRCM/NCEP CRU2 CRCM-CRU2 CRU2: Climatic Research Unit TS °X 0.5° (Mitchell et al. 2003)

8 Precipitation rate (mm/day) 5-year mean: Winter CRCM/NCEP CRU2 CRCM-CRU2

9 Maximum Screen Temperature (ºC) 5-year mean: Summer CRCM/NCEP CRU2 CRCM-CRU2

10 Maximum Screen Temperature (ºC) 5-year mean: Winter CRCM/NCEP CRU2 CRCM-CRU2

11 Minimum Screen Temperature (ºC) 5-year mean: Summer CRCM/NCEP CRU2 CRCM-CRU2

12 Minimum Screen Temperature (ºC) 5-year mean: Winter CRCM/NCEP CRU2 CRCM-CRU2

13 CRCM Version Improve some biases of related to the boundary layer: Retun the control from the planetary waves Too warm (Tmin) and too wet (pcp) 1-layer bucket too deep and very wet Excessive cloud cover (Tmin too high) Too much evaporation Too much preciptation

14 Planned Simulations Driving data OceanPeriodSpectral nudging CRCMStart CGCM2 scenario * 1xCO2 2xCO2 yes3.6.3Early 2004 CGCM2 scenario * 1xCO2 2xCO2 yes3.6.3Early 2004 GCMx 1xCO2 2xCO2 yes3.6.3Early 2004 *We have to choose from CGCM2 simulations based on different CO2 emission scenarios. GCMx: A different GCM

15 CRCM 4.0 Prototype in development in collaboration with the CRCM Network (R.Laprise et al) –MC2 dynamics + GCMIII physics Ed Chan MSC, Virginie Lorant CCCma –All CRCM physics and features need to be implemented –Prototype to be completed in early 2005

16 Variability Longer timeserie to assess variablity –25 years simulations instead of 10 years 2 compoments of the variability: –Intramonthly (seasonal) vs Interannual variabilityIntramonthly (seasonal) vs Interannual variability –Intramonthly variability: difficult to validate due to a lack of temporal resolution of gridded observed datasets Results : Validation of interannual variability

17 Precipitation Rate (mm/day) 5-year Interannual Standard-Deviation Summer CRCM/NCEP CRU2 CRCM-CRU2

18 Precipitation Rate (mm/day) 5-year Interannual Standard-Deviation Winter CRCM/NCEP CRU2 CRCM-CRU2

19 Maximum Screen Temperature 5-year Interannual Standard-Deviation Summer CRCM/NCEP CRU2 CRCM-CRU2

20 Maximum Screen Temperature 5-year Interannual Standard-Deviation Winter CRCM/NCEP CRU2 CRCM-CRU2

21 Minimum Screen Temperature 5-year Interannual Standard-Deviation Summer CRCM/NCEP CRU2 CRCM-CRU2

22 Minimum Screen Temperature 5-year Interannual Standard-Deviation Winter CRCM/NCEP CRU2 CRCM-CRU2

23 CRCM monthly extremes Precipitations extremes : computed from precipitation archived every timestep (15 min) –Highest precipitation rate for different durations –Wet days for different thresholds –Dry days for different thresholds –Precipitation histogram Daily extremes of specific humidity (screen) Daily screen temperature extremes Highest gusts at the lowest level of the model

24 CRCM climate extremes (all in early stage of development) Records of the simulation Normals of the simulation Climate indices (Stardex, etc…) Precipitation histograms Temperature distributions

25 5-year January Daily Precipitation Histogram nearest gridpoint vs station data: Victoria From the 0.2 mm threashold –124 / 155 rain days in CRCM 3 events above 25 mm during the simulation On average, –MSC obs: 17.8 / 31 (57%) rain days –CRCM : 24.8 / 31 (80%) rain days Precipitation too frequent Average number of days Total number of days

26 5-year January Daily Precipitation Histogram nearest gridpoint vs station data: Dryden Average number of days Total number of days From the 0.2 mm threashold –106 / 155 rain days in CRCM 0 event above 25 mm during the simulation On average, from [0.2-5[ mm –MSC obs: 12.2 / 31 (39%) rain days –CRCM : 21.2 / 31 (68%) rain days Precipitation too frequent [0.2-5[

27 5-year January Daily Precipitation Histogram nearest gridpoint vs station data: Kuujuaq From the 0.2 mm threashold –100 / 155 rain days in CRCM 0 event above 25 mm during the simulation On average, –MSC obs: 15.4 / 31 (49.6%) rain days –CRCM : 20.0 / 31 (64.5%) rain days Precipitation too frequent [0.2-5[ Average number of days Total number of days

28 Validation issues Gridded climatologies –Lack of resolution –Lack of temporal resolution –Lack of variables –Lack of information about the topography (except CRU) CRCM –Limited time-series –Grid point vs station data –Interpolation of datasets on the CRCM grid

29 Improving regional climate models Better representation of surface caracteristics – variables used by land surface scheme Include smaller lakes –bathymetry, lake surface temperature, ice –from Better parameterisations CRCM ensembles

30 5-year Pressure field variability: July (mb) Interannual standard-deviationIntramonthly standard-deviation Signature of the synoptic activity

31 Screen Temperature (ºC) 5-year mean: Summer CRCM/NCEP CRU2 CRCM-CRU2

32 Screen Temperature (ºC) 5-year mean: Winter CRCM/NCEP CRU2 CRCM-CRU2

33 Screen Temperature 5-year Interannual Standard-Deviation Summer CRCM/NCEP CRU2 CRCM-CRU2

34 Screen Temperature 5-year Interannual Standard-Deviation Winter CRCM/NCEP CRU2 CRCM-CRU2


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