mesoscale convective systems in amma
DESCRIPTION
Mesoscale Convective Systems in AMMA. What has been learned from previous campaigns? GATE—off the coast of west Africa COPT81—over the west African continent What has been learned since these campaigns? TOGA COARE TRMM What can we learn from AMMA? How can we learn it? - PowerPoint PPT PresentationTRANSCRIPT
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Mesoscale Convective Systems in AMMA
What has been learned from previous campaigns?•GATE—off the coast of west Africa •COPT81—over the west African continent
What has been learned since these campaigns?•TOGA COARE •TRMM
What can we learn from AMMA?
How can we learn it?
How can this new MCS knowledge help the overall goals of AMMA?
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Pre-GATE view of tropical cloud population
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Houze et al. (1980)
Post-GATE view of tropical cloud population
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GATE & COPT 81: MCS water, mass, and heat budgets
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GATE(Gamache & Houze 1983)
.60R .40R
1.17R .41R
.29R
.37R
0
.13R
.16RCOPT81
(Chong & Hauser 1989)
Water Budget of a West African Mesoscale Convective Systemover ocean (GATE) and land (COPT81)
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He
igh
t (km
)
Deg K/day
Convective
Assumed heating profilesMCS heating profiles seen in GATE & elsewhere
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He
igh
t (km
)
Deg K/day
Convective
Stratiform
Assumed heating profilesMCS heating profiles seen in GATE & elsewhere
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He
igh
t (km
)
Deg K/day
Assumed heating profiles
0% stratiform
Assumed heating profiles
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He
igh
t (km
)
Deg K/day
Assumed heating profiles
0% stratiform
40% stratiform
Assumed heating profiles
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He
igh
t (km
)
Deg K/day
Assumed heating profiles
0% stratiform
40% stratiform
70% stratiform
Assumed heating profiles
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TRMM: Global mapping of MCSs
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Nesbitt, Zipser & Cecil (2000)
Contribution of convective system type to rainfall
AFRICA S. AMER. E. PAC. W. PAC.
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Schumacherand Houze (2003)
TRMM precipitation radar rain amount subdivided intoconvective and stratiform components
Total rain
Convective rain
Stratiform rain
Stratiform rain fraction
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TRMM PR Jan-Apr 1998El Niño precipitation, observed % stratiform, El Niño basic state
250 mb stream function, 400 mb heatingK/day
Schumacher, Houze, and Kracunas (2003)
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TOGA COARE: Implications of tropical MCSs for momentum transport in large-scale waves
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1000 km
1000
kmTOGA COARE
MCS momentum transport in strong westerlies
Moncrieff &Klinker 1997
plan view
cross section
A B
A B
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strong westerly region westerlyonset region
TOGA COARE: Ship and aircraft radar data relative to Kelvin-Rossby wave structure
Houze et al. 2000
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SW NE
Houze et al. 2000
TOGA COARE: Strong Westerly case of 11 February 1993
stratiformecho
Downward momentumtransport
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Where do we stand now with west African MCSs?• GATE & COPT81 showed us the existence and prominent importance of the MCSs in the west African phenomenology
• TOGA COARE & TRMM have shown us the global importance of mesoscale organization (esp. sf regions) in water budgets, vertical distribution of heating and momentum transports.
What’s missing?• We haven’t determined the mechanisms of interaction on the meso-to-synoptic scales.
Why AMMA?• AMMA is best place to use latest technology to see better how the meso-to-synoptic scale interaction occurs, esp in the context of AEJ and AEW.
• AMMA not only will allow this fundamental interaction to be studied but will allow the downstream effects on hurricane formation to be determined.
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Technology in GATE & COPT81• Upper-air sondes in GATE—poor quality winds
• Ship radar in GATE--precip only, no Doppler, no polarimetry, no S-band
• Land radar in COPT81 --dual-Doppler, no polarimetry, limited coverage, no S-band, no large-scale context
• Aircraft in GATE—mostly in situ flight track met obs, some dropsondes, photos out the window
Technology available for AMMA• Better rawinsondes, ISS (integrated sounding systems), profilers
• Mobile S-band for land deployment, with polarimetry
• Doppler radar on ship
• Airborne Doppler radar
• Long range dropsondes, driftsondes
• Doppler lidars
• More diverse set of satellites
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NSF/NCAR S-pol radar
• Polarimetric• Doppler• S-band, 10.7 cm• Zh, Vr, Zdr, Kdp, Ldr
•Portable—Deployed successfully in TRMM/LBA (Brazil), MAP (Italian Alps) and other difficult sites
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Integrated Sounding Systems
•UHF Doppler wind profiler (~ 0.1 – 7 km agl)•Radio-Acoustic Tv profiler (~0.2 – 2 km agl)•GPS rawinsonde sounding system •Automated surface met obs•Seatainer packaged•Soundings , > 2/day + event-based
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Proposed Use of the R/V Ronald H. Brown During AMMA
Instruments
• Radar (Scanning C-band Doppler; Vertically pointing Ka-band Doppler)
• Rawinsonde
• 915 MHz wind profiler
• DIAL/Mini-MOPA LIDAR
• Multi-spectral radiometers
• Air-sea flux system
• Meteorological observation (T,RH, P), rain gauges and ceilometer
• Oceanographic measurements including SST, CTD and ADCP
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Summary: MCSs in AMMA
GATE & COPT81 showed that mesoscale organization was an important part of the tropical cloud population, both on land and offshore
Since GATE & COPT81, the mesoscale organization of tropical cloud populations has been seen to have global significance, esp. via TRMM & TOGA COARE
•Water budgets & precipitation•Heating profiles•Momentum transports
AMMA is the best place to use new technology to understand the meso-synoptic scale connection, since the interaction ofwest African MCSs & larger-scale dynamics is so robust:
•AEJ & AEWs•Saharan air layer•Tropical cyclone formation
These meso-synoptic scale linkages are essential to the overall picture of the west African monsoon sought by AMMA
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Convection, microphysics, & lightning in AMMA
S. A. Rutledge
AMMA domain is a natural laboratory to study aerosol/cloud interactions and associated feedbacks to cloud dynamics.
Lightning: Recent work from TRMM-LBA (Brazil) suggeststhat aerosols may exert a fundamental control on flash rate and cloud dynamics. This issue can be further evaluated in AMMA.
Precipitation microphysics: Need to understand the microphysical aspects of the formation of the stratiform anvil precipitation.
Overarching issue: Microphysical aspects of African convective systems virtually unexplored.
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Global frequency and distribution of lightning as observed from space
Christian, Hugh J. , Richard J. Blakeslee, Dennis J. Boccippio, William L. Boeck, Dennis E. Buechler, Kevin T. Driscoll, Steven J. Goodman, John M. Hall, William J. Koshak, Douglas M. Mach, and Michael F. Stewart, Global frequency and distribution of lightning as observed from space by the Optical Transient Detector, J. Geophys. Res., accepted, 2002.
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01/99 - 03/99 Lightning Activity - Daily Detections(5 day moving average)
0
5000
10000
15000
20000
25000
30000
Day
Sit
e D
etec
tio
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(~st
roke
s)
12/99 - 03/00 Lightning Activity - Daily Detections(5 day moving average)
0
5000
1000015000
20000
25000
3000035000
40000
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Sit
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(~st
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= East regime
Brazilian Lightning Detection Network (BLDN):
• Oscillations apparent
• East (west) anomalies =more (less) lightning.
CCN higher in east regime;argued to lead to more lightning; a competinghypothesis is that CAPE is higher in East regime compared to West regime
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Hydrometeor Identification-Example from STEPS 2000
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Retrieve mixing ratio estimates
from polarimetric data
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Performance of the S-POL radar rainfall estimate relative to rain gauges for
February 1999 TRMM-LBAMethod BIAS STANDARD
ERROR
S-POL Optimal
-4.8% 14.4%
S-POL Median -10.7% 17.9%
S-POL Closest -11.1% 20.6%
Using polarimetric techniques,accurate rain rates can becalculated and used for budget calculations and hydrological applications
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Summary: Convection, microphysics, & lightning in AMMA
S. A. Rutledge
West Africa is the best place to study aerosol effects on tropical convection
Ice phase microphysics are critical in both the MCS stratiform anvil precipitation and in lightning—aerosol may affect both
S-band polarimetric radar provides the basic tool for pursuing this work