Characterization of Arctic Mixed-Phase CloudyBoundary Layers with the Adiabatic Assumption

Paquita Zuidema*, Janet Intrieri, Sergey Matrosov, Matthew Shupe, Taneil Uttal

NOAA Environmental Technology Laboratory, Boulder, CO

Brad Baker, Paul Lawson SPEC, Boulder, CO

Aircraft path

Lidar cloud base

Temperature inversion

Cloud radar reflectivity

time

Hei

ght

(km

)

1.0 km

*National Research Council

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)

Difficult to characterize the liquid and ice components separatelyMost retrievals best suited for low cloud optical depths (e.g., lidar,IR spectra (Turner et al., 2002), near-IR spectra (Daniel et al., 2002)

• Mixed-phase microphysical processes may be necessary for models to properly simulate the annual cycle of Arctic clouds (S. Vavrus, 2003)

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

35 GHz cloud radarice cloud properties

depolarization lidar-determined liquid cloud base

Microwave radiometer-derived liquid water paths

4X daily soundings. temperature inversions define liquid cloud top

lidar cloud base

-5-45 -20

1 2 3 4 5 6 7 8day

z

2 km

-30C

41 8

2

4

6

8

km

100g/m^2

day

-10C

May 4, 7 NCAR C130 Research Flights

• 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

range (micron) parameterinstrument

Aircraft path

Lidar cloud base

Temperature inversion

Cloud radar reflectivity

time

Hei

gh

t (k

m)

1

2

dBZ0-50-50

May 4

24:0022:00 23:00UTC

Liquid Water Content: Adiabatic Ascent Calculation

• lidar-determined liquid cloud base parcel

• interpolated sounding temperature structure

• constrained w/ microwave radiometer-derived liquid water path

King LWC

adiabatic LWC

CB

excellent correspondencebetween adiabatic calc. andKing probe LWC

May 4

Z(km)

Liquid water content g/m^3

0 0.5

0.6

1.0

Derivation of liquid volume extinction coefficient and effective particle radius re

• Lognormal droplet size distribution

<rk> = <rok>exp(k22/2) (Frisch et

al., ’95,’98,’02)

cast 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

0.76 (0.04)

May 4

re

adiabatic

aircraft

Aircraft-adiabatic calc. optical depth comparison

aircraft

adia

bat

ic May 4

May 7

10620

2

10

6

Uses microwave LWP

Temperature inversion agrees well with the location of the liquid cloud top

Cloud radar top

Temperature inversion

11 1098765432 day

1 km

2 km

May 1 – 10 liquid re, time series

re

day2

re

600 30km-1

micron0 12

3 4 5 8 106 7 91 day

0

30

0

12

Mean liquid cloud optical depth ~ 8

1km

2km

Ice:

• Radar-only retrieval for all-ice clouds extended to mixed-phase (Matrosov ’02, ’03)

• IWC, i, retrieved from radar reflectivity and Doppler velocity

• Define Deff = 1.5 IWC/iAp = 3 IWC/i(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:

• Radar insensitive to liquid when ice is present

• Ice cloud optical depth almost insignificant

• Large error bars

(~4x ?)

dBZ

liquid

radar

Ice aircraft

-40 -5 10-3 1 102km-1

IWC Deff

01 15010-4 g m-3 micron

0.6

1.2

km

Ice , re,

• Mean ice cloud optical depth ~ 0.2

• Mean ice effective radius ~ 30 micron

• => main but indirect radiative effect is the uptake of the liquid

30 Km-1

re

40

0

re

0

0

0

8

Z (km)

4

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

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

• 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 too low

• FSSP cloud droplet number N too low ?

• LWP too low ?

shortwave

modeled

longwave

modeled

ob

serv

ed

ob

serv

ed

0100 300

300

600

600

W m-2

Main sensitivity of total optical depth is to LWP error

Microwave liquid water path g m-2

Fre

quen

cy

0 25

0.2

0105

Lidar, IR spectra retrievals Microwave LWP

statisticalphysical

SHEBA year MWR LWP frequency distribution (Shupe and Intrieri, 2003)

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