Série de simulations préparatoires à CMIP6, LMDZ-Orchidee, CTRL : CTRL6.0.5b

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

G - -

G - -

G - -

X

CTRL

2000_2004

3.2505

1.94

240.603

238.663

264.631

-45.8565

25.968

-19.8885

3.00433

24.9805

G - -

G - -

G - -

X

Z0

2000_2004

4.5063

3.145

240.677

237.532

263.935

-45.6546

26.403

-19.2516

2.84504

23.1142

G - -

G - -

G - -

X

GUST

2000_2004

0.2537

-0.998

239.422

240.42

265.973

-47.3986

25.553

-21.8456

3.19321

27.0169

V6.0.5b.GUST.ratqs

G - -

G - -

G - -

X

GUST ratqs

2000_2004

3.1167

1.845

240.194

238.349

265.88

-46.7309

27.531

-19.1999

3.14673

27.2782

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 CTRL6.0.5b_2000_2004

Metrics with respect to AR4.00

Metrics with respect to CMIP5/AMIP multi model