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The ASTEX Lagrangian model intercomparison case
Stephan de Roode and Johan van der Dussen
TU Delft, Netherlands
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The ASTEX First Lagrangian (June 1992)
Lagrangian evolution of cloudy boundary layer observed Five aircraft flights Duration: two days
Flight 1Flight 2
Flight 3
Flight 4
Flight 5
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ASTEX observed stratocumulus to cumulus transition
Bretherton and Pincus, 1995
Bretherton et al, 1995
Duynkerke et al, 1995
De Roode and Duynkerke, 1997
GCSS case,1995
EUCREM/GCSS,Duynkerke et al, 1999
like GCSS ATEX case,Stevens et al, 2001
Study of ASTEX First Lagrangian wtih SCM and 2D models by Bretherton et al, 1999:
"there are substantial quantitative differences in the cloud cover and liquid water path
between models."
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Satellite images Flights 1 and 5
precise position air mass during last flight uncertain
longitude
latit
ude
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Observations
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Contents
Motivation
LES results
Cloud layer depth evolution analysis
SCM results
Conclusions/outlook
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ASTEX case: motivation
stratocumulus to cumulus transition controled by
- SST, large-scale divergence, inversion stability -> sensitivity tests
Use ASTEX observations to validate LES & SCM results of a transition
additional diagnostics from LES
-eddy diffusivity, PDFs of heat and moisture, mass flux statistics, 3D
fields
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GCSS ASTEX A209 case,1995
EUCREM/GCSS,Duynkerke et al, 1999
Only 3~4 hours simulation time
current LES: Detailed microphysics Multiband radiation Longer simulation time
Motivation for a revised ASTEX case
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Model initialization
Model set up and large-scale forcing Large-scale forcing (SST & large-scale subsidence) from Bretherton et al. (1995, 1999) Model initialization from Flight 2 (A209)
- Identical to first GCSS ASTEX "A209" modeling intercomparison case Microphysics: drizzle and cloud droplet sedimentation Shortwave and longwave radiation
ERA-Interim
Bretherton ERA-40
mean in ASTEX triangle ERA-Interim
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LES participants
LES model Institution InvestigatorDALES TU Delft de RoodeUCLA/MPI MPI SanduUKMO UKMO LockSAM Univ
WashingtonBlossey
DHARMA NASA AckermanWarschau Warschau Kurowski
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Use SCM version that is identical to the operational GCM
SCM model Institution InvestigatorRACMO KNMI dal GessoEC-Earth KNMI dal GessoECMWF ECMWF SanduECMWF-MF DWD KoehlerJMA Japan KawaiPDF based scheme
Wisconsin Larson
LMD GCM LMD BonyUKMO UKMO LockArpege Meteo France Bazile/Beau
MPI ECHAM Suvarchal
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Contents
Motivation
LES results
Cloud layer depth evolution analysis
SCM results
Conclusions/outlook
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Cloud boundaries: all LES models give cumulus under stratocumulus
Boundary layer too deep compared to observations
Last 10 hours of simulations are less reliable (sponge layer, coarser vertical resolution)
DHARMA
UKMO
SAM
UCLA
DALES
lowest cloud base height
inversion height
mean cloud base height
DALES: large domain are shown
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Cloud liquid water path
Large difference in LWP!
DHARMA
UKMO
SAM
UCLA
DALES
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Cloud cover
DHARMA
UKMO
SAM
UCLA
DALES
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Surface precipitation
DHARMA
UKMO
SAM
UCLA
DALES
180 W/m2
More heavy and intermittent precipitation on a larger domain
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Entrainment rates in previous LES intercomparison runs
too large?
Heus et al. (2010)
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Entrainment
Entrainment rate doubles during the second night
Entrainment rate smaller than during previous ASTEX intercomparison case. According to Ackerman and Bretherton this is due to cloud droplet sedimentation leading to a reduction of evaporative cooling at cloud top.
DHARMA
UKMO
SAM
UCLA
DALES
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Liquid water potential temperature
Slight differences in the upper part of domain: - DALES & UCLA used ASTEX A209 specs with constant lapse rate - ASTEX Lagrangian:blend of observations and ERA 40 (needed for radiation and single-column models)
DHARMA
UKMO
SAM
UCLA
DALES
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Total water content
Mean state during first part of ASTEX Lagrangian is well represented
DHARMA
UKMO
SAM
UCLA
DALES
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Liquid water content
last part of simulation: wrong cloud height
DHARMA
UKMO
SAM
UCLA
DALES
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East-west wind component
Change in geostrophic forcing well implemented
DHARMA
UKMO
SAM
UCLA
DALES
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North-south wind component
Do we need a larger weakening of the geostrophic forcing?
DHARMA
UKMO
SAM
UCLA
DALES
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Vertical wind velocity variance
DHARMA
UKMO
SAM
UCLA
DALES
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Horizontal wind velocity variance
More variance at a larger horizontal domain
DHARMA
UKMO
SAM
UCLA
DALES
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Horizontal wind velocity variance
DHARMA
UKMO
SAM
UCLA
DALES
More variance at a larger horizontal domain
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Total water variance
Larger horizontal domain can contain more variance
DHARMA
UKMO
SAM
UCLA
DALES
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Precipitation
DHARMA
UKMO
SAM
UCLA
DALES
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Jump in downward longwave rad smaller in observations
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Longwave down
Presence of high clouds during latter part of transition.
A larger longwave radiative cooling rate will cause a larger entrainment rate and deeper boundary layers
DHARMA
UKMO
SAM
UCLA
DALES
Obs t=36h
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Shortwave down
UCLA: Solar zenith angleDALES: Error in radiation statistics of ASTEX version of the model
DHARMA
UKMO
SAM
UCLA
DALES
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Estimate large-scale divergence from LES radiation in free atmosphere
Bretherton and Pincus (1995)
Estimated divergence = 2~3 10-6 s-1 during Lagrangian
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we (
cm/s
)LW
P (g
/m2 )
Large-scale divergence, entrainment (we) and liquid water path (LWP)
In constant divergence runstratocumulus vanishes, and longwave radiative cooling at cloud top becomes very small
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Cloud cover (cc) and cloud boundaries
Divergence decreasing: deep solid stratocumulus Divergence constant: shallow cumulus
lowest cloud base
average cloud base
average cloud top
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Contents
Motivation
LES results
Cloud layer depth evolution
SCM results
Conclusions/outlook
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Cloud base height evolution
(g/kg)
z (m
)
qsat
cloud base
qT
€
∂zb
∂t=
∂qT
∂t−
∂qsat
∂t∂qsat
∂z
=
∂qT
∂t−
L vqs
RvT2
∂T∂t
∂qsat
∂z
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€
∂zb
∂t=
∂qT
∂t−
∂qsat
∂t∂qsat
∂z
=
∂qT
∂t−
L vqs
RvT2
∂T∂t
∂qsat
∂z
Cloud base height evolution
(g/kg)
z (m
)
qT
cloud base
qsat
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Cloud base height evolution
(g/kg)
z (m
)
qT
cloud base
qsat
€
∂zb
∂t=
∂qT
∂t−
∂qsat
∂t∂qsat
∂z
=
∂qT
∂t−
L vqs
RvT2
∂T∂t
∂qsat
∂z
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Tendencies in mixed layer
€
∂θL
∂t= −
∂w'θL '∂z
−1
ρcp
∂Frad
∂z=
w eΔθL +w'θL 'z=zb− ΔFrad / ρcp( )
zT −zb
€
∂qT
∂t= −
∂w'qT '∂z
−∂Sq T
∂z=
w eΔqT +w'qT 'z=zb− ΔSq T
zT −zb
drizzle
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Cloud base height evolution
€
∂zb
∂t=
w eΔqT +w'qT 'z=zb− ΔSq T
−L vqs
RvT2 w eΔθL +w'θL 'z=zb
− ΔFrad / ρcp( )[ ]
zT −zb( )∂qs
∂zz=zb
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Cloud base and top height evolution
€
∂zcld
∂t= w e +w −
w eΔqT +w'qT 'z=zb− ΔSq T
−L vqs
RvT2 w eΔθL +w'θL 'z=zb
− ΔFrad / ρcp( )[ ]
zT −zb( )∂qs
∂zz=zb
€
zcld ↑
€
zcld ↓
€
zcld ↑
€
zcld ↓
€
zcld ↓
€
zcld ↓
€
zcld ↑
if rad cooling
Positive w ("upsidence") deepens cloud layer!
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Cloud base and top height evolution
rcpwq_zbase= 11.3 W/m2
rLvwq_zbase = 60.0 W/m2
DLW= 74.0 W/m2
Div = 5.0 10-6 s-1
zbase = 300 m, zi= 600 mDqL =5K, DqT = -1.1 g/kg
increase with time of:- cloud top height - cloud layer depth
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Example: Dycoms
rcpwq_zbase= 11.3 W/m2
rLvwq_zbase = 60.0 W/m2
DLW= 74.0 W/m2
Div = 5.0 10-6 s-1
zbase = 500 m, zi= 800 mDqL =12K, DqT = -9.1 g/kg
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Contents
Motivation
LES results
Cloud layer depth evolution
SCM results
Conclusions/outlook
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SCM cloud boundaries
Deepening of boundary layer is well represented
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SCM LWP
Liquid water path variation is large
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SCM total cloud cover
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SCM surface precipitation
Similar diffusivities for moisture and heat?
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East-west wind velocity
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East-west wind velocity
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Liquid water potential temperature
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Liquid water content
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SCM cloud fraction
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Eddy diffusivity
Do SCMs use similar diffusivities for moisture and heat?
LES results EUROCS FIRE stratocumulus
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What did we learn
LES models can reproduce bulk features of the observed cloud transition
- mean state and turbulence structure
Entrainment rate smaller than in previous ASTEX intercomparison cases
Negative divergence halfway the transition causes deeper cloud layers (found from
sensitivity tests).
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Problems and possible case refinements
Too deep boundary layer
1. change divergence
2. downwelling longwave radiation: check moisture content in free atmosphere
- time varying upper atmosphere?
3. presence of high clouds during the last part of the Lagrangian
4. domain size
Reduce geostrophic forcing even further?
All models need to use same initial profiles
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Outlook/suggestions
LES output
3D fields
Radiation
All modelers should provide a "fingerprint" of their radiative tranfer code by running their
codes for one step using a few different thermodynamic profiles and for different solar
zenith angles