(AUTRES) Série de simulations préparatoires à CMIP6, LMDZ-Orchidee, CTRL : LMDZORt2mR

RUN Atlas YEAR Atlas --DJF-- Atlas --JJA-- 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
LMDZORt2mR G - - G - - G - - X X CM610 no bug t2m diagno 1990_1999 4.5328 4.6929 246.683 241.99 263.255 -40.5999 21.265 -19.3349 3.10694 25.0395
TESTnoroughusda G - - G - - G - - X X CM610 no rough zobler 1999_2008 4.4726 4.6513 246.515 241.864 263.059 -40.9326 21.195 -19.7376 3.12222 25.1566
TESTnoroughusdawbmx G - - G - - G - - X X CM610 no rough zobl wbmx 1999_2008 5.1604 5.3383 248.391 243.053 263.6 -39.1331 20.547 -18.5861 3.15166 24.8626
LMDZORt2mnrsoil G - - G - - G - - X X CM610 no do_rsoil 2000_2009 4.0207 4.195 245.973 241.778 263.088 -41.0562 21.31 -19.7462 3.16153 25.1255

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)