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Cloud Resolving Model Studies of Tropical Deep Convection Observed
During HIBISCUS 2004.
By Daniel Grosvenor, Thomas W. Choularton, & Hugh Coe
- The University of Manchester, United Kingdom
With thanks to:
Gerhard Held - IPMET, Brazil;Jorge Gomes – CPTEC, Brazil;Andrew Robinson – UCAM, United Kingdom.
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Aims of Work
• To simulate transport of material from lower to upper troposphere by deep convective clouds– Gases, aerosols, water vapour, ice hydrometeors
• Testing and improvement of model– Comparisons to observations
• GCM parameterisations– Data set for development and testing
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The LEM Model• Cloud Resolving Model• UK Met Office• Bulk microphysics parameterisation
– 38 conversion processes between:• Vapour, liquid, rain, ice, snow, graupel.
• Double moment for ice hydrometeors• Highly variable resolution:-
– Boundary layer processes– Deep convection
• Periodic boundary conditions
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24th February, 2004 Case Study• Large squall line moving from north passes
over Bauru.
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Model Initialisation• One sounding for whole domain
– Time forcing possible
• Available soundings:– 09:00 LT Campo Grande– 17:15 LT Bauru– 21:00 LT Sao Paulo
• Bauru sounding fairly stable - no deep convection produced by model– Campo Grande sounding used and model forced
towards Bauru sounding
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Model Initialisation
• Squall line initialised using a warm perturbation
• 2-D, 500km domain, 1km resolution
• Sensitivity to aerosol concentration tested
• Comparisons to radar statistics of echo tops and 3.5km CAPPI data
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Timeseries of max 3.5km radar reflectivity
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Timeseries of 3.5km radar reflectivity modes
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Log-Normal Distribution of 3.5km dBZ from 14:00-23:00
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Timeseries of Max EchotopsM
axim
um o
f 10d
BZ
rad
ar e
cho
tops
(km
)
Local Time
Ma
xim
um
of
10
dB
Z r
ad
ar
ech
o t
op
s (k
m)
CCN = 720cm-3
CCN = 240cm-3
Radar data
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Local Time
Mo
de
of
10
dB
Z r
ad
ar
ech
o t
op
s (k
m)
CCN = 720cm-3
CCN = 240cm-3
Radar data
Timeseries of Echotop Modes
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Timeseries of Echotop Variances
Local Time
Va
ria
nce
of
10
dB
Z r
ad
ar
ech
o t
op
s (k
m2)
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Log-Normal Distribution of Echotops from 14:00-23:00
-5
-4.5
-4
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
Log
10 o
f N
orm
alis
ed D
istr
ibut
ion
of E
cho
Top
s
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Max Tracer at each Height as Percentage of Max Input
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CFC-11 tracer measurements from SF-4 (DIRAC, UCAM)
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Profile of Mean Liquid Water
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Conclusions• Echotop agreement reasonable but lack of high
echotops• Simulated 3.5km dBZ generally too high – related to
above?• 2-D simulations produce highly time variable
statistics• Mean values hard to compare with 2-D simulations –
slices through radar data should be better• Tracer outflow height close to apparent outflow
from observations
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Future Work
• Vertical radar slice comparisons (RHIs)
• ECMWF/Meso model for soundings and forcing – comparisons to clouds obtained in these models
• Full double moment scheme
• Vertical aerosol transport
• EMM (Explicit Microphysics Model)