Parameterizing convective
organization
Brian Mapes, University of Miami
Richard Neale, NCAR
What is organization?
• Deviations from random parcel/ uniform
environment/ no history assumptions
embodied in a GCM’s convection
treatment.
Worth parameterizing?
• ...to the degree that errors attributable
to those assumptions can be reduced.
A parsimonious, corrective approach
• Address the biggest possible bundle (‘EOF1’) of
the many phenomena that are lacking, at
minimum cost/complexity (1 variable, linear)
• Simplicity also commensurate with lack of
globally systematic knowledge to base on
A parsimonious, corrective approach
• Correction = Expectation[ reality – model ]
1. depends on model
• not just “out there” to be measured in sky or CRMs
2. depends on field realities of convection
• not a fiction, not derivable as theory
Example: organization increases during
diurnal convective rain development
Khairoutdinov and Randall 2006
What increases?
• Variance or magnitude
of fluctuations, of many
variables, at many
altitudes
• Coherence among
above
• Scale of fluctuations
(slope of size spectrum)
• Local environment of
coherent structures
4 new variables? No.
One.
New model branch: CAM5_UWens_org
1. Disabled Zhang-McFarlane
– UW (Bretherton-Park) ”shallow” plume scheme only
» deep convection too dilute, but a functioning climate
2. I extended code to ensemble of UW plumes
– unified physical basis for PBL – shallow – deep
» TKE / CIN closure  buoyancy driven plume fluxes
3. ORG governs plume ensemble members
– now to demonstrate it’s worth its weight
a) full proposed organization scheme
evaporation
of rain
subgrid
geography
and breezes
forced,
decaying,
advected
org(lat,lo
n,t)
plume overlap
more likely
(preconditioned
local environs)
wider plumes with
less lateral mixing
inhibition/closure
stochastic
component
shear rolls,
deformation
filaments
updraft base T >
grid cell mean
more, deeper convection
precipitation
precipitation
rain
evap.
org
CAM5 with
UWens 2plume
ensemble
org2rkm2
plume overlap
more frequent
wider 2nd plume
2nd plume closure
plume base T’
convection +
b) implementations tested so far
Org scheme in CAM5_UWens_org - summer 2010
evaporation
of rain
subgrid
geography
and breezes
stochastic
component
plume overlap
more likely
(preconditioned
local environs)
forced,
decaying,
advected
org(lat,loorg2rkm
n,t)
shear (rolls,
deformation
lines, etc.)
=5
wider plumes
(entrain less)
inhibition
org2Tpertupdraft base
= 1 warmer than grid
mean
more, deeper convection
precipitation
stable
The Entrainment Dilemma:
a well-trod track
too undilute (ZM)
(CCM3/CAM3)
mean state
obs.
unstable
too diluted
(CCM2/ Hack,
UW shallow only)
precip variability 
Entrainment dilemma: tropical sounding
UWens with
an undilute
member:
too stable
UW only:
too dilute
unstable state
stable
Dilemma: a well-trod track
too undilute (ZM)
(CCM3/CAM3)
dilution
+freezing
CAM3.5+
too diluted
(CCM2/ Hack,
UW shallow only)
unstable
mean state
obs.
precip variability 
Entrainment dilemma: tropical sounding
Entrainment dilemma: tropical sounding
UWens with
an undilute
member:
too stable
UW only:
too dilute
unstable state
Org and the entrainment dilemma
UWonly:
unstable
bias,
excess
variance
UW_ens_org:
about right
Org and the entrainment dilemma
UWonly:
unstable
bias,
excess
variance
UW_ens_org:
about right
stable
Dilemma: a well-trod track
too undilute (ZM)
(CCM3/CAM3)
IDEA: Org-dependent convection can be
restrained by mixing in non-rainy places
(increasing variance), while deep
convection is less dilute once organized in
rainy places (no unstable bias)
mean state
obs.
unstable
too diluted
(CCM2/ Hack,
UW shallow only)
precip variability 
Others have roughly same idea
• “A Systematic
Relationship between
Intraseasonal
Variability and Mean
State Bias in AGCM
Simulations”
• Daehyun Kim, Adam H.
Sobel, Eric D. Maloney,
Dargan M. W. Frierson,
and In-Sik Kang
Hysteresis involving org?
STABILITY
dawn
low org
high org
convection
persists
NOON
DEEP CONVECTION 
afternoon
rain peak
STABILITY
? Hysteresis on longer time scales from
org timescale of ~3h ?
low org
high org
convection
persists
DEEP CONVECTION 
Summary
1. Organization is a set of subgrid variances and
relationships that are lacking in average plume/
uniform environment schemes.
2. Entrainment limits convective development, in
unorganized cloud fields.
3. Org scheme allows less-dilute convection, once
organized. This avoids mean bias from 2.
4. CAM5-UWens-org models exist, they run, and they
appear to escape the Entrainment Dilemma.
5. Diurnal cycle delay by org’s timescale (~3h) is a virtue
in itself.
6. Further characterization is underway.