Characterization of Arctic Mixed-Phase Cloudy
Boundary Layers with the Adiabatic Assumption
Paquita Zuidema*, Janet Intrieri, Sergey Matrosov, Matthew Shupe, Taneil Uttal
Brad Baker, Paul Lawson
SPEC, Boulder, CO
*National Research Council
Temperature inversion
1.0 km
Aircraft path
Cloud radar reflectivity
Lidar cloud base
time
Height (km)
NOAA Environmental Technology Laboratory, Boulder, CO
MOTIVATION
•Mixed-phase clouds (i.e., liquid and ice coexisting near each
other) are common in Arctic (Uttal et al. 2002; Intrieri et al. 2002;
Shupe et al. 2001)
•Radiative forcing by liquid-containing clouds important to
Arctic climate and surface energy balance (Intrieri and Shupe, 2002)
•Recent decades have seen a rapid warming of the Arctic
Surface (Francis, 2002; Stone 1997)
• Mixed-phase microphysical processes may be necessary for
models to properly simulate the annual cycle of Arctic clouds
(S. Vavrus, 2003)
Difficult to characterize the liquid and ice components separately
Most retrievals best suited for low cloud optical depths (e.g., lidar,
IR spectra (Turner et al., 2002), near-IR spectra (Daniel et al., 2002)
Information from multiple sensors
can be combined to describe liquid
and ice cloud vertical structure
• May 1 – May 10 SHEBA example
• Derivation of liquid and ice cloud optical
depth structure and effective particle size
• Comparisons against aircraft
measurements (May 4 and May 7)
• Comparison of modeled surface radiative
fluxes to observed fluxes
Surface-based Instrumentation: May 1-8 time series
8
-20
-45
-5
dBZ
6
35 GHz cloud radar
ice cloud properties
km
4
2
depolarization lidar-determined liquid cloud base
Microwave radiometer-derived liquid water paths
100
g/m^2
2
1
3
4
day
day
5
6
7
8
4X daily soundings. temperature inversions define liquid cloud top
1
lidar cloud base
4
2 km
8
z
May 4, 7 NCAR C130
Research Flights
instrument
• FSSP-100
range (micron)
2-47
• 1D OAP-260X (May 4)
40-640
• 2D OAP (May 7)
25-800
• Cloud Particle Imager
5-2000
• King hot-wire probe
parameter
liquid, ice size distribution
ice size distribution
ice shape, size
particle phase, shape, size
liquid water content
May 4
Cloud radar reflectivity
dBZ
0
2
Height (km)
-50
-50
1
Temperature inversion
Aircraft path
Lidar cloud base
22:00
UTC
23:00
time
24:00
Liquid Water Content: Adiabatic
Ascent Calculation
• lidar-determined liquid
cloud base parcel
• interpolated sounding
temperature structure
• constrained w/ microwave
radiometer-derived liquid
water path
excellent correspondence
between adiabatic calc. and
King probe LWC
May 4
adiabatic LWC
1.0
King LWC
CB
0.6
Z
(km)
0
0.5
Liquid water content g/m^3
Derivation of liquid volume extinction
coefficient b and effective particle radius re
• Lognormal droplet size
distribution
<rk> = <rok>exp(k2s2/2) (Frisch et
al., ’95,’98,’02)
cast b and re in terms of
observables:
LWC (adiabatic calc.),
Mean aircraft cloud droplet
conc. N=244 (4)
Mean aircraft lognormal spread
in droplet size distribution
s =0.76 (0.04)
May 4
re
adiabatic
aircraft
b
Aircraft-adiabatic calc. optical depth
comparison
tadiabatic
10
Uses microwave LWP
May 4
6
2
May 7
0
2
taircraft
6
10
Temperature inversion agrees well with
the location of the liquid cloud top
2 km
Cloud radar top
1 km
Temperature inversion
1
2
3
4 day 5
6
7
8
9
10
May 1 – 10 liquid b, re, t time series
2km
km-1
0
b
60
30
1km
micron
12
0
rre
e
1
2
3
4 day5day 6
7
8
9
10
30
12
0
0
t
Mean liquid cloud optical depth ~ 8
Ice:
• Radar-only retrieval for all-ice clouds
extended to mixed-phase (Matrosov ’02, ’03)
• IWC, bi, retrieved from radar reflectivity
and Doppler velocity
• Define Deff = 1.5 IWC/riAp = 3 IWC/rib
(Mitchell et al., 2002, Boudala et al., 2002)
• Comparison to in situ data more uncertain:
• Complete size distributions difficult to form
• Another degree of freedom: Particle shape
Robust conclusions:
1.2
b
dBZ
radar
• Radar insensitive to
liquid when ice is
present
km
0.6 liquid
Ice aircraft
-5 10-3
-40
• Ice cloud optical
depth almost
insignificant
• Large error bars
(~4x ?)
IWC
10-4
g m-3
km-1 1
102
Deff
1
0
micron 150
Ice b, re, t
• Mean ice cloud
optical depth ~
0.2
• Mean ice
effective radius ~
30 micron
• => main but
indirect radiative
effect is the
uptake of the
liquid
8
0
Z (km)
-1
3 Km
b
0
0
40
re
0
4
t
0
re
Comparison of calculated surface
radiative fluxes to observed fluxes
• Streamer (Key and Schweiger)
• DISORT (Stamnes et al. )
• Parameterized shortwave ice cloud optical
properties for 7 particle habits
• Arctic aerosol profile
• Lowtran 3B gaseous absorption database
• SHEBA spectral surface albedo (Perovich et al.)
• Adapted for cloud radar vertical resolution
100
600
shortwave
observed
longwave
observed
300
Comparison of modeled to observed surface
downwelling radiative fluxes, May 1 -10
modeled 300
0
W m-2
modeled 600
• Observed LW > modeled
LW by 13 (15) W m-2
• modeled SW > observed
SW by 37 (36) W m-2
• Clear-sky bias ½ of
cloudy-sky bias
• => modeled cloud t too
low
• FSSP cloud droplet
number N too low ?
• LWP too low ?
Main sensitivity of total optical
depth is to LWP error
SHEBA year MWR LWP frequency distribution (Shupe and Intrieri, 2003)
Frequency
Lidar, IR spectra retrievals
Microwave LWP
statistical
physical
0.2
0
0 5 10
25
Microwave liquid water path g m-2
Summary & Conclusions
• Arctic mixed-phase clouds are common, radiatively and
climatically important
• Can characterize the liquid with an adiabatic ascent calculation
using a saturated air parcel from the lidar-determined liquid
cloud base, constrained with the microwave radiometer-derived
liquid water path
• The ice component can be characterized with cloud radar
retrievals, even when LWC is high
• This was applied to a May 1-10 time series with some success,
judging from comparison to aircraft data and comparison of
calculated radiative fluxes to those observed.
• For May 1-10: radiative flux behavior is practically that of a pure
liquid cloud
• The low ice water contents are consistent with what is required
for the maintenance of a long-lived super-cooled (~ -20 C) liquid
water cloud (e.g., Pinto, 1998, Harrington, 1999)
• Usefulness of the technique can be improved even further by
improving the microwave radiometer retrievals of liquid water
path