new CRM diagnostics dedicated to convective

parameterization

J-I YanoP. Bechtold, J.-P. Chaboureau, F. Guichard,

J.-L. Redelsperger and J.-P. Lafore

LMD, CNRM-GAME & Laboratoire d’Aérologie, Toulouse

• restitution of convective fluxes Yano et al. to appear

• potential energy convertibility (PEC)

CRMs-SCMs comparisons

A lot of diagnostics have been produced

domain average quantities

mean profiles of T, q, Q1, Q2, cloud waterconvective fluxes, but not so much infact

sub-domain quantities, more delicateoften need to define criteria in CRMs (as in observations)

in-cloud propertiesconvective mass flux scheme

CRM simulations

MesoNH, 3D, x=2kmcomeNH, 2D and 3D, x=500m to 2km(nz ~ 50)

COARE cases : tropical convection over oceanARM case : and midlatitude convection over land

« segmentally constant » classification

i

iii

ii

ii www '' ''

knowing the mean properties of the different categories (up and down convective, up and down stratiform…) is not enough to recover the total convective fluxes (more complex than shallow convection)

not negligeable

new model, new simulations, same conclusion

(only the resolved part of the convective flux above)

analysis in this « real  » space: in terms of mass-flux based parameterizations, the CRM-derived estimates of mean properties within each category alone are not useful to evaluate parameterized convective fluxes

' ' wpc ' ' )/v(L qwpc

0)(w' & 0)(w' planes-1/2 two the in )(w, of values mean : ),w and ),wdduu

((

w’ < 0’ > 0

w’ < 0’ < 0

w’ > 0’ > 0

w’ > 0’ < 0

'' '' )','( ''

ddwwwp

w

in the probability space

very wide range of variability in over both half-planes (w’> 0 & w’<0)

see later

quadrants 4 the in (w, of values mean : ),w and ),w, ),w , ),w-d-ddd-u-uuu

)((((

(from snapshot at z~5km)

same but for the convective area

The spread is not decreased much

total flux

w wdd

uu

d

u

p

p

w ii

dduu

ip

,,,

improvement with 4 quadrants but still too low

)'().'(

)','(

pwp

wp

higher correlations for higher values (4 corners)

the effective values contributing to fluxes are much higher than simple means

use weighted average rather than simple average

We tried:

with parameter « a » , a = 0.25 hereafer

*

a

a

'

'''

2 half-planes

4 quadrants

weighted 4 quadrants

rms error for the 3 methods + standard deviation (solid)same results for momentum flux

latentheatflux

sensibleheatflux

the decomposition in the (w’, ’) probability space does not guaranty that the mass fluxes are the same for all the variables (, q, u, v, tracers)

in terms of parameterization:

uw

i wi for

uw

-uw -u

w

-dw

i wi for q

dw

combination of the 4 components into 2

i wi for i wi for q

** du

** du

** dduu

pp www

** dduu

nn www

positive drafts

negative drafts

ppw

ppwn

nwn

nw

summary, discussion, in the context of today (GCSS)

one-to-one comparison between CRMs and SCMs not always straightforward, e.g. convective fluxes

the method proposed here (with weighted averages) enables to advance on this issue, by shifting to the probability space

behind is the idea that the mass flux formulation stands more as an idealized framework rather than directly as a simplified picture of the reality (this view is coherent with recent LES analyses, e.g., showing the weaknesses of this formulation to retrieve the variances)

…to be further explored: the meaning of entrainment/detrainment in this modified context

a generalization of CAPE with the potential energy convertibility (PEC)

motivation:

CAPE is a very useful convective parameter but

CAPE has its own limitations in the context of parameterization e.g., extension of CAPE for entraining plumes

CAPE variations not simply linked to convectione.g., diurnal cycle of deep convection over land, dry intrusion periods over the warm pool

th

shdzbCAPE .

th

shdzwb

wPEC .

*)(

1

*)/(* wwbb

PEC ~ rate of conversion of energy normalized by a measure of the vertical momentum

dzwH

w

H

0

2)(1

)*(

th

shdzbPEC .*

PEC far from perfect but provides a better measure of moist convective instability than CAPE from the case-studies

Colors: 3 distinct COARE periods, from CRM runs

possible strategy: to modify entrainment rates so that they produce a buoyancy consistent with b* obtained from PECwork in progress