Série de simulations préparatoires à CMIP6, LMDZ-Orchidee, CTRL : CPL6v5.17h


RUN Atlas YEAR Atlas --DJF-- Atlas --JJA-- Zonal mean Dynamical regime Cloud Fraction Diurnal Cycle Scatter Plots Outputs Model Parameters Tested Parameter Period bils rt rst rlut rlutcs crest crelt cret eva pr prw
CLIMATOS 7.097 0.7823 240.4 239.6 269.4 -47.05 29.84 -17.21 3.415 2.61 27.46
CPL6v5.17h G N S - - - - - - X X Calipso Isccp X X X X 6.0.1 1940_1949 -0.1735 -0.935 240.814 241.749 266.623 -51.7843 24.874 -26.9103 2.9718
CPL6v5.4b G N S G N S G N S X X Calipso Isccp X X X X 6.0.2 2140_2149 0.2896 -0.3518 252.356 252.708 271.003 -44.6999 18.295 -26.4049 3.17242
v5.5pftXORCA1V01 G - S - - - - - - X X Calipso Isccp X X X X 6.0.3 2030_2039 0.7583 -0.694 241.038 241.732 269.115 -49.8704 27.383 -22.4874 3.12177
v5.63XORCA1T G N S - - - - - - X X Calipso Isccp X X X X 6.0.3i 1940_1949 1.0892 -0.3289 243.501 243.83 271.582 -47.9595 27.752 -20.2075 3.21405

Metrics computation

RMSE (Root Mean Square Error) between models and reference datasets (observations or reanalyses depending on the variable; identified at the top of the columns). The RMSE are computed on a 12-month climatological annual cycle (spatio-temporal variability + mean); they mix the information on the spatio-temporal correlation and standard-deviation ratio, as well as the mean bias. The results are shown in % of the average RMSE obtained for the set of simulations chosen as reference. A result of -10 indicates that this error is 10% lower than the average of the errors of the reference simulations.  Basically these metrics provide an overall view on whether the simulations are closer to or further of a set of reference simulations (say, the AMIP simulations, an AR4 simulation...)

Metrics with respect to CPL6v5.17h_1940_1949

Metrics with respect to AR4.00

Metrics with respect to CMIP5/AMIP multi model