Relationship of Cloud Water Budgets to
Heating Profile Calculations
Austin and Houze 1973
Houze et al. 1980
Houze 1982
17-19 May 2006, Seattle
Austin and Houze 1973
Houze et al. 1980
PREMISE
Measure rain amount as a function of
radar Echo Heights
--> Large-scale Mass Transport Profile (aka LH)
Houze 1982
PREMISE
Can also relate eddy & radiative heating profiles to
water budget to obtain
latent + eddy + radiative
heating
Tropical MCSs inject lots of hydrometeors into upper troposphere
Idealized life cycle of tropical MCS as proposed by Houze 1982
Contributions to Total Heating by Convective Cloud System
Conv. LH
Strat. LH
Conv. Eddy
Rad.
Strat. Eddy
These combine to give “top-heavy” heating profile
TOTAL HEATING
Houze 1982 idealized case
Think of the following schematic as a composite of the water budget of an
MCS over its whole life cycle
Ac
As
After Houze et al. (1980)
Ac
As


E  a C  C 
A  b C  C 
Rs   s Csu  CT
Stratiform water budget equation
Csu  CT  Rs  Esd  As
Rain not simply related to condensation
sd
s
su
su
where
s  a  b  1
T
T
As
Water budget parameters could be measured
Cloud radar  As
Precip radar  Rs
Doppler & soundings  As, Csu, CT


E  a C  C 
A  b C  C 
Rs   s Csu  CT
sd
s
su
su
T
T
where
 s  a  b  1  error
Ac
As
Convective region water budget equation
Ccu  Rc  Ecd  Ac  CT
Ac
Sum over all
cloud height
categories i
As
R   Rci
For each height category i
i
Ccu   Ccui
i
Ecd   Ecdi
i
CT   CTi
i
Ac   Aci
i
Rci   iCci
Esdi   iCci
Aci  iCci
CTi  iCci
with the constraint
 i   i   i  i  1
(each height cat.)
ZAC
Ac
XAC
*A*s * * *
* *
XAC
Dimensions and hydrometeor content of anvils
are determined by the cloud dynamics and are
related to the radiative heating profiles
ZAS
Summary
• Latent, eddy, and radiative heating are interrelated through
the water budget of the precipitating cloud system.
• Profiles of latent heating estimated by spectral methods
are not independent of eddy and radiative heating profiles.
• Water budget parameters can be used to establish the
internal consistency of latent eddy and radiative heating
profiles.
Thank you!
Extra Slides:
In TWP-ICE we are subdividing the anvil into mixed and ice anvils
Example from TWP-ICE
Precipitation Radar
20 January 2006 0000UTC
11˚
S
12˚
S
13˚
S
130˚E
131˚E
dB
Z 6
11˚0
S5
3
4
6
12˚3
S9
3
2
2
13˚5
1
S
8
6 km 1
1
132˚E
4
20 January 2006 0900UTC
130˚E
131˚E
dB
Z 6
11˚0
S5
3
4
6
12˚3
S9
3
2
2
13˚5
1
S
8
6 km 1
1
132˚E
4
20 January 2006 1800UTC
dBZ
6
0
53
46
39
32
25
18
6 km
130˚E
131˚E
132˚E
Cloud Radar
11
4
dBZ
20
28
ATTENUATED
Height (km)
16
21
14
12
7
8
0
-7
4
-14
0
-21
2200
19Jan06
0000
20Jan06
0200
20Jan06
0400
20Jan06
0600
20Jan06
0800
20Jan06
1000
20Jan06
1200
20Jan06
1400
20Jan06
1600
20Jan06
1800
20Jan06
2000
20Jan06
-28
Longer-term
records of
the water
budget
parameters
also are
being
derived.
Figures here
are for
duration of
TWP-ICE.
TWP-ICE
Precipitation
Radar Rain Rate
(~20 % stratiform)
TWP-ICE Cloud Radar
Anvil Frequency
This will also
be done for a
longer-term
climatology.
We will use
cloud &
precipitation
radars
permanently
located at
Darwin.
Could use empirically derived water budget parameters b and s, to
estimate the stratiform regions’ anvil mass proportional to the SF rain:
For example
As =(bRs)/s
400 hPa
K/day
200 hPa streamfunction response to CRF assumed proportional to
TRMM rain by Schumacher et al. (2004)
Looking at it the other way around: Whatever latent heating budget is
derived from the TRMM precip info must be internally consistent with the
radiative heating profiles