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!