Download Lect13_PBLclouds

Boundary Layer Clouds
St & Sc
Stratus and stratocumulus
Transition
Trade cumulus
Intertropiccal Convergence Zone (ITCZ)
SGP Low cloud coverage (ceilometer
& MPL): 27.8% (Lazarus et al. 2000)
Cooling effect
Warming effect
NASA: The Earth Radiation Budget Experiment (ERBE)
It measures the energy budget at the top of
the atmosphere.
Energy budget at the top of atmosphere (TOA)
Incoming solar radiation 340 W/m2
Reflected SW radiation
Q1= 50 W/m2
Fictitious
climate
system
No clouds
Incoming solar radiation 340 W/m2
Reflected SW radiation
Q= 100 W/m2
shortwave cloud forcing
dQ=Q1-Q=-50 W/m2 (cooling)
Emitted LW radiation
F1= 270 W/m2
Emitted LW radiation
F= 240 W/m2
longwave cloud forcing
dF=F1-F=30 W/m2 (warming)
Present
climate
system
with clouds
SW cloud forcing = clear-sky SW radiation – full-sky SW radiation
LW cloud forcing = clear-sky LW radiation – full-sky LW radiation
Net cloud forcing (CRF) = SW cloud forcing + LW cloud forcing
Current climate: CRF = -20 W/m2 (cooling)
But this does not mean clouds will damp global warming! The impact
of clouds on global warming depends on how the net cloud forcing
changes as climate changes.
Direct radiative forcing due to doubled CO2, G = 4 W/m2
  0  positive cloud feedback

CRF
G
  0  zero cloud feedback
  0  negative cloud feedback
e.g.
If the net cloud forcing changes from -20 W/m2 to -16 W/m2 due
to doubling CO2, the change of net cloud forcing
will add to the direct CO2 forcing. The global warming will be
amplified by a fact
ofCRF
2.  - 16 - (-20)  4 W/m 2
Cloud radiative effects depend on cloud distribution, height, and optical properties.
Low cloud
High cloud
Tc
Tc
Tg  Tc
Ta
Tc  Ta
Tg
SW cloud forcing dominates
LW cloud forcing dominates
In GCMs, clouds are not resolved and have to be
parameterized empirically in terms of resolved
variables.
water vapor (WV)
cloud
surface albedo
lapse rate (LR) WV+LR
ALL
Issues
LS Forcing
Cloud evolution and maintenance.
Cloudiness .
Radiation
Turbulence
Microphysics
Radiative and microphysical
properties.
Cloud entraining processes and
cloud
mass transport.
Cloud mesoscale organizations.
Surface Processes
Cloud-aerosol-drizzle interactions
Mesoscale
cellular
convection
(MCC)
Pockets of
open cell
(POCS)
Variations of MCCs and POCs are much larger than the
individual variations within the structures (Jensen et al. 2008)
Aerosol feedback
Direct aerosol effect: scattering, reflecting, and absorbing solar radiation by
particles.
Primary indirect aerosol effect (Primary Twomey effect): cloud reflectivity is
enhanced due to the increased concentrations of cloud droplets caused by
anthropogenic cloud condensation nuclei (CNN).
Secondary indirect aerosol effect (Second Twomey effect):
1. Greater concentrations of smaller droplets in polluted clouds reduce cloud
precipitation efficiency by restricting coalescence and result in increased cloud
cover, thicknesses, and lifetime.
2. Changed precipitation pattern could further
affect CCN distribution and the coupling between diabatic processes
and cloud dynamics.
Parameterization Development and Testing Strategy
GCM
/NW
P
PAR
CRMS
LES
OBS
Hi-Res simulation s and 3-D Observations
Traditional LES: idealized initial profiles and prescribed horizontal
homogeneous large-scale forcings.
Representativeness of clean cloud cases?
Clouds
Liquid water mixing ratio
Liquid water density of clouds
l  wl  air
Cloud droplet distribution
Number density N (D):
the number of droplets per nit
volume (concentration) in an
interval D + ΔD
wl 
mass liquid
mass dry air
l 
mass liquid
volume of dry air
mass of a droplet  l 6 D 3
Liquid water content
L  6  l N i ( Di ) Di3
Variables that are useful for cloud research
Mixing ratio, saturated mixing ratio, liquid water mixing ratio, total mixing ratio
r , rs , rl , rt

v   (1  0.608r  rl )
e  
Lv

r
C pT
l    CLT rl
p
es  
Lv

rs
C pT
Equivalent potential temperature
Liquid water potential temperature
Saturated quivalent potential temperature
Instrumentation
Latest version W-band (95 GHz)cloud radar
Millimeter Wave Cloud Radar (35 GHz)
X-band scanning ARM precipitation radar
Vaisala Ceilometer
Mechanisms of maintaining cloud-topped boundary layer
1. Surface forcing
2. Cloud top radiative cooling
3. Cloud top evaporative cooling
Cloud parameterization
1. Cloud fraction parameterization
Shallow cumulus parameterization:
Mass-flux approach
Fcu   w    M c (c  e ) ,
M c   (1   )(w c  w e ),
  c  (1   )c
Entraining plume model
c
  (c   )
z
1 M c
  
Mc  z
1. How to close the system?
2. How to determine entrainment and detrainment rates?
Stratocumulus parameterization
Cloud top entrainment parameterization
Eddy viscosity
A1, A2: empirical coefficients. V: turbulent velocity scale. ΔF:
cloud-top radiative flux divergence. ΔB: buoyance jump
across the inversion.