Série de simulations préparatoires à CMIP6, LMDZ-Orchidee, CTRL : LMDZOR.AMIP

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
LMDZOR.AMIP G - - G - - G - - X X X LMDZOR AMIP 2000_2004 2.9571 1.809 241.51 239.701 265.837 -45.6122 26.136 -19.4762 3.00835 24.9546
LMDZOR.NUD - - - - - - - - - X X X LMDZOR NUDGED 2000_2004 0.6314 0.103 240.073 239.97 266.094 -46.9558 26.124 -20.8318 3.0475 25.0184
LMDZOR.NUD.Z0 G - - G - - G - - X X X LMDZOR NUDGED Z0 2000_2004 -1.9305 -2.237 238.833 241.07 266.917 -48.4627 25.847 -22.6157 3.23712 27.1213
LMDZOR.NUD.GUST G - - G - - G - - X X X LMDZOR NUDGED GUST 2000_2004 -0.0386 -0.229 239.41 239.639 267.316 -48.1688 27.677 -20.4918 3.21705 27.427

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 forced-by-SST AMIP multi model

Metrics with respect to coupled CMIP5 simulations (historical)

Metrics with respect to IPSLCM5A-LR (clim A verifier)