Selection of Sub-Ensemble for EDF Climate Service

This selection focuses on creating a sub-ensemble of CMIP6 climate projections for the EDF in-house climate service. The criteria involve representation of the whole CMIP6 ensemble, inclusion of independent models, historical performance evaluation, and incorporating low probability high impact scenarios. The comparison between CMIP5 and CMIP6 projections for France is examined, along with model dependencies and performance across different elements. The model selection process identifies specific models based on various factors for further analysis.

• Climate projections
• CMIP6
• EDF climate service
• Model selection
• France

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1. Selection of a sub- ensemble of CMIP6 projections for the EDF in-house climate service P.-A. Michelangeli, S. Parey, J. Bo , H. Omrani, H. Filahi, L. Collet, B. Oueslati, K. Pol, C. Legorgeu

2. SELECTION CRITERIA Sub-sample representative of the whole CMIP6 projection ensemble Sub-sample with (roughly) independent models Some elements of the performance across France in the historical period Equilibrium climate sensitivity in the observed very likely range + 1 or 2 more sensitive models as low probability high impact scenarios 2

3. COMPARISON OF THE CMIP5 AND CMIP6 PROJECTIONS FOR FRANCE: DP / DT stars = CMIP5 circles = CMIP6 | 3

4. MODEL DEPENDENCIES Number of common components: Atmosphere Ocean Land Ice The bigger and the darker = more common components | 4 Bo , J. (2018). Interdependency in multimodel climate projections: Component replication and result similarity, Geophysical Research Letters, 45, 2771 2779.; https://doi.org/10.1002/2017GL076829

5. MODEL PERFORMANCE For each season: distance = mean absolute error of spatial averages across France (ref = CRU-TS4) Distance computed for: Climatological mean Interannual variability (standard-deviation) Trends For models with ensemble members Computation of the distance for each member Ensemble mean of the distances 5

6. ELEMENTS OF MODEL PERFORMANCE ACROSS FRANCE 1951-2014 | 6

7. ELEMENTS OF MODEL PERFORMANCE ACROSS FRANCE 1951-2014 | 7

8. MODEL SELECTION Models with missing scenarios Models with sensitivity > 5 C Models close to others ECS ( C) Mod le Hist SSP1- 2.6 SSP2- 4.5 SSP3- 7.0 SSP5- 8.5 FIO-ESM-2-0 GFDL-CM4 GFDL-ESM4 GISS-E2-1-G GISS-E2-1-G-CC GISS-E2-1-H HadGEM3-GC31- LL HadGEM3-GC31- MM INM-CM4-8 INM-CM5-0 IPSL-CM6A-LR KACE-1-0-G MCM-UA-1-0 MIROC-ES2L MIROC6 MPI-ESM-1-2- HAM MPI-ESM1-2-HR MPI-ESM1-2-LR MRI-ESM2-0 NESM3 NorCPM1 NorESM2-LM NorESM2-MM SAM0-UNICON TaiESM1 UKESM1-0-LL 3 1 3 39 1 1 4 3 XXXX 1 2 XXXX XXXX 1 3 1 3 15 XXXX XXXX 1 XXXX XXXX 1 2 XXXX XXXX XXXX 3 1 1 7 XXXX XXXX 3 4.72 3.87 3.16 ACCESS-CM2 ACCESS-ESM1-5 AWI-CM-1-1-MR 3 10 5 1 3 1 1 3 1 1 3 5 3 10 1 3.89 2.60 2.72 3.04 3.26 2.29 5.62 BCC-CSM2-MR BCC-ESM1 CAMS-CSM1-0 CanESM5 CanESM5-CanOE 3 3 2 40 3 1 1 1 1 3.11 5.55 2 40 3 2 40 3 2 40 3 2 40 3 5.42 2 1 XXXX XXXX 3 5.16 5.14 4.75 1.83 1.92 4.56 4.48 3.65 2.68 2.61 2.96 CESM2 CESM2-FV2 CESM2-WACCM 11 3 3 3 XXXX 1 3 XXXX 3 3 XXXX 1 3 XXXX 3 1 10 32 3 2 10 10 2 1 1 6 2 1 2 3 XXXX 1 1 11 3 1 1 3 XXXX 1 5 11 3 1 1 3 XXXX 1 1 6 3 1 10 3 XXXX 4.79 CESM2-WACCM- FV2 CMCC-CM2-SR5 CMCC-ESM2 CNRM-CM6-1 CNRM-CM6-1-HR 3 XXXX XXXX XXXX XXXX 3.52 1 1 30 1 1 1 6 1 1 1 6 1 1 1 6 1 1 1 6 1 4.83 4.28 2.98 3.00 3.15 4.72 3.05 2.54 2.50 3.72 4.31 5.34 10 10 5 5 30 3 1 1 1 17 2 10 1 2 XXXX 1 1 XXXX 1 5 2 10 1 2 XXXX 3 1 XXXX 1 5 10 10 5 XXXX XXXX 1 1 XXXX 1 5 2 10 2 2 XXXX 1 1 XXXX 4.76 5.32 CNRM-ESM2-1 E3SM-1-0 E3SM-1-1-ECA E3SM-1-1 EC-Earth3 EC-Earth3-Veg EC-Earth3-Veg-LR 9 5 1 1 23 5 1 5 XXXX XXXX XXXX 7 4 XXXX 5 XXXX XXXX XXXX 22 5 XXXX 5 XXXX XXXX XXXX 7 4 XXXX 5 XXXX XXXX 1 7 4 1 4.10 4.31 8 1 5 3.00 2.88 FGOALS-f3-L FGOALS-g3 3 6 1 1 1 1 1 1 1 4

9. PROJECTIONS IN THE EDF CLIMATE SERVICE ECS ( C) 3.87 3.16 3.04 2.29 5.62 4.75 3.52 4.76 4.10 2.88 2.60 2.72 4.56 4.48 2.68 3.00 3.15 2.54 4.31 5.34 Model Historical SSP1-2.6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 SSP2-4.5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 SSP3-7.0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 SSP5-8.5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ACCESS-ESM1-5 AWI-CM-1-1-MR BCC-CSM2-MR CAMS-CSM1-0 CanESM5 CESM2-WACCM CMCC-CM2-SR5 CNRM-ESM2-1 EC-Earth3 FGOALS-g3 GFDL-ESM4 GISS-E2-1-G IPSL-CM6A-LR KACE-1-0-G MIROC-ES2L MPI-ESM1-2-LR MRI-ESM2-0 NorESM2-LM TaiESM1 UKESM1-0-LL 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 9

10. MAIN VARIABLES Temperature: Tas, Tasmax, Tasmin Surface wind Precipitation Radiation: rsds, rlds Humidity: hurs, huss Pressure Land-sea mask orography 10

11. A PROBLEM FOR TAIESM1 tasmax Raw data for 1 grid point Bias adjusted data (CDFt) 11

12. THANKS