Characterization of Arctic Mixed-Phase Cloudy

1
Characterization of Arctic Mixed-Phase
Cloudy Boundary Layers with the Adiabatic
Assumption
Paquita Zuidema, Janet Intrieri, Sergey
Matrosov, Matthew Shupe, Taneil Uttal
NOAA Environmental Technology Laboratory,
Boulder, CO
Height (km)
Brad Baker, Paul Lawson
SPEC, Boulder, CO
National Research Council
Temperature inversion
1.0 km
Aircraft path
Cloud radar reflectivity
Lidar cloud base
time
2
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)
3
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

4
Surface-based Instrumentation May 1-8 time series
8
dBZ
-5
-45
-20
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/m2
2
3
4
5
6
7
8
1
day
day
4X daily soundings. temperature inversions define
liquid cloud top
2 km
4
1
8
lidar cloud base
z
-30C
-10C
5
May 4, 7 NCAR C130
Research Flights
range (micron)
parameter
instrument

• FSSP-100 2-47
  liquid, ice size distribution
• 1D OAP-260X (May 4) 40-640 ice size
  distribution
• 2D OAP (May 7) 25-800 ice
  shape, size
• Cloud Particle Imager 5-2000 particle
  phase, shape, size
• King hot-wire probe liquid water
  content

6
May 4
Cloud radar reflectivity
dBZ
0
-50
-50
2
Height (km)
1
Temperature inversion
Aircraft path
Lidar cloud base
2400
UTC
2200
2300
time
7
Liquid Water Content Adiabatic Ascent
Calculation
May 4

• lidar-determined liquid cloud base parcel
• interpolated sounding temperature structure
• constrained w/ microwave radiometer-derived
  liquid water path

adiabatic LWC
1.0
King LWC
CB
0.6
Z (km)
excellent correspondence between adiabatic calc.
and King probe LWC
0
0.5
Liquid water content g/m3
8
Derivation of liquid volume extinction
coefficient b and effective particle radius re
May 4

• Lognormal droplet size distribution
• ltrkgt ltrokgtexp(k2s2/2) (Frisch et al.,
  95,98,02)
• cast b and re in terms of observables
• LWC (adiabatic calc.),
• Mean aircraft cloud droplet conc. N244 (4)
• Mean aircraft lognormal spread in droplet size
  distribution
• s 0.76 (0.04)

re
b
adiabatic
aircraft
9
Aircraft-adiabatic calc. optical depth comparison
10
Uses microwave LWP
May 4
6
tadiabatic
2
May 7
6
0
10
2
taircraft
10
Temperature inversion agrees well with the
location of the liquid cloud top
2 km
Cloud radar top
1 km
Temperature inversion
day
1
1
10
9
8
7
6
5
4
3
2
11
May 1 10 liquid b, re, t time series
2km
km-1
60
0
30
b
1km
micron
0
12
re
re
2
3
4
5
8
10
6
7
9
1
day
day
30
12
t
0
0
Mean liquid cloud optical depth 8
12
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

13
Robust conclusions
dBZ
1.2
b
radar
km

• Radar insensitive to liquid when ice is present
• Ice cloud optical depth almost insignificant
• Large error bars
• (4x ?)

Ice aircraft
0.6
liquid
-5
-40
km-1
10-3
1
102
IWC
Deff
150
0
g m-3
micron
1
10-4
14
Ice b, re, t

• Mean ice cloud optical depth 0.2
• Mean ice effective radius 30 micron
• gt main but indirect radiative effect is the
  uptake of the liquid

8
Km-1
3
0
b
Z (km)
0
0
40
re
0
4
re
t
0
15
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

16
Comparison of modeled to observed surface
downwelling radiative fluxes, May 1 -10

• Observed LW gt modeled LW by 13 (15) W m-2
• modeled SW gt observed SW by 37 (36) W m-2
• Clear-sky bias ½ of cloudy-sky bias
• gt modeled cloud t too low
• FSSP cloud droplet number N too low ?
• LWP too low ?

longwave
shortwave
300
600
observed
observed
0
modeled
modeled
100
600
300
W m-2
17
Main sensitivity of total optical depth is to LWP
error
SHEBA year MWR LWP frequency distribution (Shupe
and Intrieri, 2003)
Lidar, IR spectra retrievals
Microwave LWP
statistical
physical
Frequency
0.2
0
10
0
25
5
Microwave liquid water path g m-2
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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

19
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