Série de simulations préparatoires à CMIP6, LMDZ-Orchidee, CTRL : V5.70a

RUN Atlas YEAR Atlas --DJF-- Atlas --JJA-- Cloud Fraction 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
V5.70a G - - - - - - - - Calipso Isccp X X Run force de l'ete, V5.70a 1980_1989 2.8107 1.635 240.654 239.019 265.205 -45.5916 26.186 -19.4056 3.01581 24.6266
RIM1607b - - - - - - - - - X X X Reglage no1 607bZ0, meilleur ETOA 1988_1996 -1999998 -999999 0 999999 999999 0 0 0 999999 999999
RIM2607b G - - - - - - - - X X X Reglage no2 607bZ0, meilleurs reg.dyn.trop. 1988_1996 5.5964 4.166 241.032 236.866 262.525 -46.3747 25.659 -20.7157 3.14206 27.0922
RIM3607b G - - - - - - - - X X X Reglage no2 + cld_lc=0.055, elcrit=0.5g/kg 1987_1987 5.3059 4.261 241.728 237.467 262.771 -45.7196 25.304 -20.4156 3.12664 27.1273

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 coupled CMIP5 simulations (historical)

Metrics with respect to forced-by-SST AMIP multi model

Metrics with respect to IPSLCM5A-LR (historical)