Stratus Cloud parameters Stratus Cloud parameters retrieval from Doppler radarretrieval from Doppler radar

Virendra P. GhateVirendra P. Ghate

OutlineOutline IntroductionIntroduction Radar spectra and DSDRadar spectra and DSD Model setupModel setup Observations & ResultsObservations & Results SHEBA dataSHEBA data Model Observation comparisonsModel Observation comparisons ConclusionConclusion

Cloud Radar Spectra Cloud Radar Spectra

Reflectivity dBZ=10*log10(Z)Doppler VelocityDoppler Spectrum Width

Lognormal DSDLognormal DSD

202xx

(x x )Nn exp22 r

x=loge(r)x0=loge(r0)

ParametersParameters

KnownKnown ReflectivityReflectivity Doppler VelocityDoppler Velocity Doppler Spectrum Doppler Spectrum

widthwidth

UnknownUnknown Total Number of Total Number of

DropletsDroplets Modal RadiusModal Radius Lognormal WidthLognormal Width

Moments are relatedMoments are related

2k k 2

0 xkr r exp2

k6f

k6D

r V rV

r

2x

0 D

13r a V b exp2

DSD Moment Doppler Moment

2x

6 60

Zexp( 18 )N2 r

σx=0.35???

Cloud Vs DrizzleCloud Vs Drizzle

Cloud Vs DrizzleCloud Vs Drizzle

ObservationsObservations

Atlantic Stratocumulus Transition Atlantic Stratocumulus Transition Experiment (ASTEX)Experiment (ASTEX)

Porto Santo, Portugal; June 1992Porto Santo, Portugal; June 1992

InstrumentInstrument ProductProduct

35 GHz cloud Doppler 35 GHz cloud Doppler radarradar

Reflectivity, Doppler Reflectivity, Doppler velocity, spectrum velocity, spectrum widthwidth

3 channel Radiometer3 channel Radiometer Liquid Water path, Liquid Water path, Water vapor pathWater vapor path

Observations on 6 June 1992Observations on 6 June 1992

Northcomp

Eastcomp

RetrievalsRetrievals

LWC RetrievalLWC Retrieval

Cooling Rate RetrievalCooling Rate Retrieval

ConclusionsConclusions Technique to derive cloud and drizzle Technique to derive cloud and drizzle

DSD, LWC from first three Doppler DSD, LWC from first three Doppler moments.moments.

Need to average long enough to Need to average long enough to compensate for turbulent vertical compensate for turbulent vertical velocity, horizontal homogeneity etc.velocity, horizontal homogeneity etc.

Potential for surface based remote Potential for surface based remote sensors to do long-term monitoring.sensors to do long-term monitoring.

Frisch Model TestFrisch Model Test

Get Known DSD

Compute radar Moments Apply Frisch Model

Calculate Bulk Parameters

SHEBA/FACESHEBA/FACE Surface Heat Budget of the Arctic OceanSurface Heat Budget of the Arctic Ocean

• 1995-1996; 1997-1999; 2000-20021995-1996; 1997-1999; 2000-2002 FIRE Arctic Cloud Experiment (FACE) FIRE Arctic Cloud Experiment (FACE)

• April – July 1998April – July 1998

InstrumentationInstrumentation

InstrumentInstrument CharacteristicsCharacteristics

Forward Scattering Forward Scattering Spectrometer Probe Spectrometer Probe (FSSP)(FSSP)

16 Channel, 16 Channel, 2–47 µm,2–47 µm,~3 µm binwidth~3 µm binwidth

1D Optical Array Probe 1D Optical Array Probe (OAP)(OAP)

64 Channel, 64 Channel, 40-600 µm,40-600 µm,10 µm binwidth10 µm binwidth

DataData 18 July 1998 2230 UTC to 19 July 0300 18 July 1998 2230 UTC to 19 July 0300

UTCUTC

Calculated dBZ and VCalculated dBZ and VDD

Frisch derived DFrisch derived D00 and N and N

DSD ComparisonDSD Comparison

Liquid Water ContentLiquid Water Content

ConclusionsConclusions

Frisch technique can be applied to Frisch technique can be applied to retrieve cloud/drizzle characteristics retrieve cloud/drizzle characteristics under Stratiform conditions.under Stratiform conditions.

The DSD obtained from the The DSD obtained from the technique might not fit the observed, technique might not fit the observed, but the bulk parameter (LWC etc.) but the bulk parameter (LWC etc.) are reasonably retrieved.are reasonably retrieved.