Evaluation of Climate Simulations

Transcription

1 Evaluation of Climate Simulations A.Will (BTU Cottbus) Results provided by A.Block, K.Keuler, K.Radtke, and M.Woldt

2 Overview CLM Community Model Quality CLM3 and COSMO_4.8 Model Uncertainties

3 1. CLM Community CLM Community The CLM Community is an open, international, network of scientists who signed the CLM Community agreement. The CLM Community Agreement specifies: - acceptance of the rules of good scientific practice of the DFG - free exchange of results - restriction to scientific use of the COSMO model - contribution to the aims of the CLM Community Aims of the CLM Community: - Quantification and Reduction of Model Uncertainties - Efficient Use of Computational Ressources - Preparation and Conduction of Consortial Scenario Runs

4 >5 new

5 Cooperations COSMO Meeting COSMO/CLM Training and Seminar CLM-Community Assembly Community Steering Committee Univ./R.Cent. NWP-research CLM Coordination, Steering group Data Assimilation Preprocessing (PPP,PEP, int2lm) Reference Version User Support / Technical Aspects Numerical Aspects Dynamics and Numerics Physical Aspects PP COLOBOC Soil and Vegetation Verification WG Chem.&Aeros. Clouds, Aerosols and Radiation Interpretation and Application Evaluation

6 History of the COSMO-CLM Beta LM Version official LM Version 1999 LM operational 1999 Start of CLM development at PIK 2000 One-year simulation (Brasilien, PIK) First climate simulation (EU Project PRUDENCE, GKSS) Community Model Status in Germany 2006 Consortial runs for the 21 st century 2007 Unified model version for weather and climate 2009 Unified model version for weather, climate, aerosols and chemistry

7 CLM Community development COSM O-Gr oups CLM -Gr oups CLM-Members New in 2007/2008: National Autonomous University of Mexico

8 Regions of Application of CCLM and Transferability Studies various (50km - 3km) e.g. Polar Lows, CoastDat2 PACES / Laptev See Downscaling Experimente TROPCYC/ Taifune Panama Niederschlag ICTS REGCLIMOSS ENSEMBLES-AMMA RiftLink (FU Berlin)

9 Fields of Activity: Model Development Institution New model components Status IMK-IFU, GKSS ETH, IMK-TRO, UCL IMK-TRO, BTU, UCL Processing External Parameters OASIS3, OASIS4 Coupler in COSMO Ocean-Atm-Coupl. For Baltic Sea and Mediterranean COSMO-CLandM Veg3D Passive and active Aerosol Effect Atmospheric Chemistry PIK, IMK-IFU River Routing Scheme Started COSMO-CLM-config. for Europe beta-version pep_0.5.2 GKSS, others IMK-TRO, BTU int2lm2, converter (global to int2lm) ppp-xxx, int2lm_1.8.3 cosmo_4.2_clm_5, and others COSMO improvements cosmo_5 in prepar. Uni Mainz Stand. Coupl. Interface, MACCHIATO ongoing Model & Data, HH GKSS, FU Berlin, BTU, IMK-TRO IAC-ETHZ (Land- Atm), JRC IMK-TRO BTU, ETHZ, PIK, GKSS, IMK-TRO Started in preparation First version avail. first beta-version avail. First simulations at ETH, Climate mode of COSMO-ART in preparation Climate mode of COSMO- ART in preparation nearly finished

10 2. Quality of CLM and COSMO-CLM CLM

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12 Scheme for Quality Control of Regional Climate Simulations Present Gegenwartsklima day clim Evaluation Evaluierungslauf sim C20-Control C20-Kontrolllauf sim SRES-Scenario SRES-Szenariolauf sim from observations Interpolated or analysed gridded data ERA40 EC5*-C20 EC5*-CCS Referenzdaten Reference data DWD, CRU, GPCC, HISTALP, ETH, MARS, ERA-Diagnose Vgl. 1 CLM-Eval CLM-C20 time periods ä CLM-CCS time periods Observed Reference climate Regional Reference climate Regional control climate Regional Scenario climate EC5* =coupled simulation with ECHMA5/MPI-OM - Comp. 1: Quality of the regional model

13 Leapfrog-Simulations Model run configuration: CLM3-E/K CLM_ > and LM_3.19 Model domain: EURope (193 x 217) Extended EURope (256x271) LME Data: ERA40 GME ECHAM5+OPYC Dx = 18km Dt := 90 s for leapfrog TERRA_ML 10 Layers z_1=1cm, z_10=11.5m Dts = 30 s

14 NEW NWE NOA SCA OSS NOS NEE All Comparisons: NEL BIS MEU EEU RUS 1. Selected regions SEL SWE SEU SWM VAS SEL SEW NAF MED NSK SSK ALP POE UNG SLW DTL ESS LIN SAX STU MEI MUN

15 Runge-Kutta-Simulations Model run configuration: CCLM4.8-EU440 CCLM_4.8_clm1 -> and int2lm_1.9_clm1 Configuration: europe-440 Model domain: EURope (101x111) Data: ERA40 Dx = 50km Dt := 360 s for RK TERRA_ML 10 Layers z_1=1cm, z_10=11.5m Dts = 30 s

16 CCLM_4.x Selected regions

17 1. T_2m

18 Comp. 1: T_2m, Difference of yearly climatologies (20y) Reference data for T_2m: DWD ERA40 CRU

19 Comp. 1: T_2m, Difference of monthly climatologies (7y) January and July

20 Comparison 1: T_2m, Climatological annual cycle (DTL) Comparison1: Quality of the regional model

21 T_2M, CCLM4.8-ECAD, DJF and MAM

22 T_2M, CCLM4.8-ECAD, JJA and SON

23 T_2M, CCLM4.8-ECAD, annual cycle

24 1. TOT_PREC

25 Comp. 1: TOT_PREC, Difference of yearly climatologies (20y) Reference data for T_2m: GPCC CRU DWD

26 Comp. 1: TOT_PREC, Difference of monthly climatologies (7y) January July Comp. 1: T_2m, Difference of yearly climatologies (20y)

27 Comparison 1: TOT_PREC, Climatological annual cycle (DTL) Comparison1: Quality of the regional model

28 PMSL

29 Mean PMSL Difference CLM050-CLM044, January July CLM050: extended Europe (257x271 grid points) CLM044: Evaluation domain (193x217 grid points)

30 Latent heat flux E

31 Mean annual cycle of latent heat flux (land points) 79-86

32 Summary and conclusions consistent surface energy balance underestimation of latent heat flux, especially in summer Overestimation of winter precipitation Cold winter bias in middle and southern Europe, but warm bias in Scandinavia Cold summer bias in Scandinavia and warm bias in southern Europe Underestimated DTR in Winter Overestimation of precipitation in Scandinavia and at the eastern boundary and underestimation in southern Europe, especially in the Balkan region and Po lowlands in summer Boundary effects of dynamics in the large domain extended EU

33 3. Model Uncertainties

34 Small Disturbance of Boundary Conditions Once in a Month TOT_PREC JJA 1981 DIFF:TOT_PREC, STD slope: DIFF: T_2m, STD slope:-0.4

35 Variability of climate simulations on climatological time scales (DTL) 4 Climate variability on different time scales of COSMO-CLM Klimavariabilität auf unterschiedlichen Zeitskalen Jahresmittel Temperatur A1B_2 vers. A1B_1 due to different initial conditions of the global model Temperaturdiffenz in K ,06 K years Mittelungszeitraum in Jahren

36 Range of Uncertainty of the expectation value 5 Temperaturänderung Deutschland (A1B, vs ) 4 Temperaturänderung in K Jan Feb Mär Apr Mai Jun Jul Aug Sep Okt Nov Dez

37 Theoretical experiment: 4 values taken by chance 20 times from an ensemble with distribution N N Anz.Simulationen Ensemble: n Max T 4 3 Mean 2 Single value Anzahl Ensembles Min

38 Theoretical experiment: 4 values taken by chance 20 times from an ensemble with distribution G 8 G Anz.Simulationen Ensemble: n 4 6 Max T 4 Mean Anzahl Ensembles Min

39 Theoretical experiment: 4, 8, 16 and 32 values taken by chance 20 times from an ensemble with distribution N N Anz.Simulationen Ensemble: n 4 N Anz.Simulationen Ensemble: n T 4 T Anzahl Ensembles N Anz.Simulationen Ensemble: n Anzahl Ensembles N Anz.Simulationen Ensemble: n T 4 T Anzahl Ensembles Anzahl Ensembles

40 Distribution N x 2 Normalverteilung : 2 Π p T

41 Theoretical experiment: 4, 8, 16 and 32 values taken by chance 20 times from an ensemble with distribution G G Anz.Simulationen Ensemble: n 4 G Anz.Simulationen Ensemble: n T 4 T Anzahl Ensembles G Anz.Simulationen Ensemble: n Anzahl Ensembles G Anz.Simulationen Ensemble: n T 4 T Anzahl Ensembles Anzahl Ensembles

42 Distribution G Gammaverteilung : 1 2 x x p T

43 Dependence on time step - leapfrog - Runge-Kutta