heating profiles associated with deep convection estimated from trmm and future satellites
DESCRIPTION
Heating Profiles Associated with Deep Convection Estimated from TRMM and Future Satellites. Robert Houze University of Washington. Wei-Kuo Tao Goddard Space Flight Center. 19th Scientific Steering Group Session of the Global Energy and Water Cycle Experiment, January 23, 2007, Honolulu, HI. - PowerPoint PPT PresentationTRANSCRIPT
Heating Profiles Associated with Deep Convection Estimated from TRMM and Future
SatellitesRobert Houze
University of Washington
19th Scientific Steering Group Session of the Global Energy and Water Cycle Experiment, January 23, 2007, Honolulu, HI
Wei-Kuo TaoGoddard Space Flight Center
Relationship of Cloud Water Relationship of Cloud Water Budgets to Heating Profile Budgets to Heating Profile
CalculationsCalculations
Austin and Houze 1973Houze et al. 1980Houze 1982, 1989Takayabu 2002
Shige et al. 2006
Relationship of Cloud Water Relationship of Cloud Water Budgets to Heating Profile Budgets to Heating Profile
CalculationsCalculations
Austin and Houze 1973Houze et al. 1980Houze 1982, 1989Takayabu 2002
Shige et al. 2006
Latent heating only
Total heating
Houze 1982
PREMISEPREMISE
Can also relate all components of heating profiles to water budget of
convective clouds
Total Heating = Latent + Eddy + Radiative
Houze 1982
PREMISEPREMISE
Can also relate all components of heating profiles to water budget of
convective clouds
Total Heating = Latent + Eddy + Radiative
Idealized life cycle of tropical MCS
Houze 1982
Conv. LH Strat. LH
Rad.Conv. EddyStrat. Eddy
Contributions to Total Heating by Convective Cloud System Contributions to Total Heating by Convective Cloud System
Houze 1982
TOTAL HEATING
These combine to give “top-heavy” heating profile These combine to give “top-heavy” heating profile
Houze 1982
Includes latent, eddy, and radiative
“top heavy”
Think of the following schematic as a composite of the water budget of an MCS over its whole life cycle
Think of the following schematic as a composite of the water budget of an MCS over its whole life cycle
After Houze et al. (1980)
AcAs
Csu+CT =Rs + Esd + As
Rs=εs Csu +CT( )
Esd =a Csu +CT( )
As =b Csu +CT( )
whereεs + a+b=1
Stratiform water budget equation
Rain not simply related to condensation
AsAs
Ac
Ccu=Rc + Ecd + Ac +CT
Convective region water budget equation
AsAs
Ac
R = Rcii∑
Ccu = Ccuii∑
Ecd = Ecdii∑
CT = CTii∑
Ac = Acii∑
Rci=ε iCci
Esdi =α iCci
Aci =βiCci
CTi =ηiCci
ε i +α i + βi +ηi =1
Sum over all cloud height categories i
For each height category i
with the constraint
(each height cat.)
“Spectral Method”…Shige et al.
AsAs
Ac
TRMM Latent Heating Workshops
1st Workshop: NASA Goddard Space Flight Center Greenbelt, May 10-11 2001 (W. Olson, R. Johnson and W.-K. Tao) 18 participants
2nd Workshop: NCAR Boulder CO, October 10-11 2001 (M. Moncrieff, A. Hou and W.-K. Tao) ~ 30 participants after 9.11
3rd Workshop: Nara Japan, September 10-11 2004 (E. Smith, S. Shige and W.-K. Tao) 20 participants
4th Workshop: Seattle Washington, May 17-19 2006 (R. Houze, E. Smith and W.-K. Tao) 26 participants
Tao, W.-K., R. Houze, Jr., and E. Smith, 2007: Summary of the 4th TRMM Latent Heating Workshop, Bull. Amer. Meteor. Soc., (submitted)
Heat Budget
Latent HeatingEddy fluxes
At a level z
Q1 = QR + π[−
1ρ∂ρ ′w ′θ∂z
− ′rV • ∇ ′θ ] +
LvCP
(c−e) +L f
CP
( f −m) +LsCP
(d−s)
RadiationTotal heating
NOTE: Pc & Ps provide a
constraint when determining LH(z)
1
g(Q
1Ptop
Pbase∫Lx∫ −QR )ΔpΔx=L Pc + Ps( ) + So
Vertically integrated
Convective Stratiform
= + + LH(z)
Can’t measure directly
TRMM Observations
Precipitation Radar (PR)—Pc, Ps, Echo Height
TRMM Microwave Imager (TMI)—multifrequency microwave radiances
LH algorithms designed to be physically consistent with some combination of these observations
Five Different Latent Heating Algorithms
Convective - Stratiform Heating - CSH (Tao/Lang et al. 1993, 2000)
PR* or TMI* (Cloud model generated look-up table)
Spectral Latent Heating - SLH (Shige/Takayabu et al. 2003, 2006)
PR (Cloud model generated look-up table)Goddard Profiling - GPROF (Olson et al. 1999, 2006)
TMI or PR/TMI Combined (Cloud model generated look-up table)
Hydrometeor Heating - HH (Yang/Smith et al. 1999)
PR or PR/TMI Combined (Hydrometeor mass conservation)
Precipitation Radar Heating - PRH (Satoh/Noda 2001)PR (Hydrometeor mass conservation)
How do we validate latent heating algorithms?
Check consistency of derived latent heating profiles with total heating
determined from soundings.
Soundings Total Heating, Q1
Q
1=π[
∂θ∂t
+V • ∇θ +w∂θ∂z
]
Yanai et al. 1973, and others
TestbedsSCSMEX LBA
ARM SGP
ARM
KWAJEX
At testbed sites:
•Determined Q1 profiles from soundings
•Checked consistency with CRM Q1 with sounding data
•Checked consistency of algorithm Q1 or LH with sounding data
Zhang, Johnson, Schumacher
LBA
SCSMEX
KWAJEX
Q1 =π[∂θ∂t
+V • ∇θ +w∂θ∂z
]
Mean profiles at testbed sites
Workshop Results
CSH & SLH similar for all four testbeds
QRQR
CRM Simulated Retrieved & Observed
SCSMEX Result
Eddy Q1
LH
OBSCSHSLH
• Improve NWP (Rajendran et al. 2004)
•Validate Climate Model (Chen, Del Genio, Chen, 2006)
•Assimilate Q1 heating profiles into Global Model(Hou and Zhang 2006)
Recent Applications
Rajendran et al. (2004, J. Meteor. Soc. Japan)
72-Hour Forecast with ECPS ( FSU - GSM T126L14)
Rain (satellite observations): 8 February 1998 (12 UTC )
0 2 5 10 15 20 35
(mm day -1 )
GM 60E 120E IDL 120W 6OW GM
GM 60E 120E IDL 120W 6OW GM
72-Hour Forecast Control Run ( FSU - GSM T126L14)
GM 60E 120E IDL 120W 6OW GM
45N
30N
15N
EQ
15S
30S
45S
45N
30N
15N
EQ
15S
30S
45S
45N
30N
15N
EQ
15S
30S
45S
Improved 72 h forecast
GPCP
With LH algorithm
Control
Chen, Del Genio, Chen (2006, J. Climate)
GISS
CSH
Mean Anomalies
Climate Model Validation Mean & ENSO 1998 DJF anomalies at altitude of peak latent heating
for the CSH product & GCM
Current Products Available in TSDIS(Experimental)
CSH (3A25 - PR) - 0.5 x 0.5 degree, Monthly
GPROF (2A12 - TMI) - Orbital, Instantaneous
HH (2B31 - Combined) - Orbital, Instantaneous
0.5 x 0.5 degree from daily - weekly - seasonalConvective and Stratiform regionRegimes (e.g., African Monsoon)
19 vertical layers: 0.5, 1, 2, ……….18 kmLH, Q1-QR and Q1
Latent Heating Products (Beta - V1 in 2007)
5th TRMM/GPM Latent Heating Workshop (April or May 2007 - DC Area)
Soliciting the requirements from large-scale modeling and dynamic community
Latent heating profiles
•Can be determined if the cloud water budget parameters are known
But radiative heating profiles
•Also related through the cloud water budget
AsAs
Ac
ΔXAC
ΔZAC
Dimensions and hydrometeor content of anvils are determined by the cloud dynamics
IWCIWC
Rs=εs Csu +CT( )
As =b Csu +CT( )
Recall
Using empirically derived values of the water
budget parameters b and εs, the stratiform
regions’ anvil mass is proportional to the stratiform rain
As =(bRs)/εs
200 hPa streamfunction response to CRF assumed proportional to TRMM rain by Schumacher et al. (2004)
400 hPaK/day
SummarySummary
•Algorithms for determining LH(z) are being developed by TRMM/GPM community, experimental products in TSDIS
•Profiles of latent heating, eddy, and radiative heating profiles not independent but rather closely interrelated through cloud water budgets.
•Cloud water budget is a powerful way to determine the consistency of latent, radiative, and eddy heating.
• If latent and radiative heating determined independently, physical inconsistencies could arise. Cloud water budget provides a means for establishing consistency.
•Water budget parameters need to be determined--via field studies supported by high resolution modeling
•Algorithms for determining LH(z) are being developed by TRMM/GPM community, experimental products in TSDIS
•Profiles of latent heating, eddy, and radiative heating profiles not independent but rather closely interrelated through cloud water budgets.
•Cloud water budget is a powerful way to determine the consistency of latent, radiative, and eddy heating.
• If latent and radiative heating determined independently, physical inconsistencies could arise. Cloud water budget provides a means for establishing consistency.
•Water budget parameters need to be determined--via field studies supported by high resolution modeling
Thank you!