new crm diagnostics dedicated to convective parameterization j-i yano p. bechtold, j.-p. chaboureau,...
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![Page 1: New CRM diagnostics dedicated to convective parameterization J-I Yano P. Bechtold, J.-P. Chaboureau, F. Guichard, J.-L. Redelsperger and J.-P. Lafore LMD,](https://reader036.vdocuments.net/reader036/viewer/2022070414/5697c00e1a28abf838cc9d88/html5/thumbnails/1.jpg)
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)
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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
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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
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« 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
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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
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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)
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same but for the convective area
The spread is not decreased much
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total flux
w wdd
uu
d
u
p
p
w ii
dduu
ip
,,,
improvement with 4 quadrants but still too low
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)'().'(
)','(
pwp
wp
higher correlations for higher values (4 corners)
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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
'
'''
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2 half-planes
4 quadrants
weighted 4 quadrants
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rms error for the 3 methods + standard deviation (solid)same results for momentum flux
latentheatflux
sensibleheatflux
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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
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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
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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
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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
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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 .*
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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
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possible strategy: to modify entrainment rates so that they produce a buoyancy consistent with b* obtained from PECwork in progress