Scanning Raman Lidar Error Scanning Raman Lidar Error Characteristics and Calibration For IHOPCharacteristics and Calibration For IHOP

David N. Whiteman/NASA-GSFC, Belay Demoz/UMBC

Paolo Di Girolamo/Univ. of Basilicata, Igor Veselovskii/General Physics Institute,

Keith Evans/UMBC, Zhien Wang/UMBC, Ruei-Fong Lin/UMBC, Joe Comer/SSAI,

Gerry McIntire/Raytheon

Acknowledgement: Interdisciplinary Research, Jim Dodge, NASA/HQ

OutlineOutline

SRL random error characterization– May 22 dryline case

Examples Water Vapor Lidar Calibration

– Temperature dependent lidar equations Aerosol scattering ratio Water vapor mixing ratio

Raman Lidar water vapor calibration– Aqua validation (Sept – Nov, 2002)– IHOP (May – June, 2002)

Scanning Raman LidarScanning Raman Lidar Telescopes: 0.76 and 0.25 m Nd:YAG (9W @ 355 nm) Windows 12 channel AD/PC IHOP Accomplishments

– >200 hours – Factor of 10 increase in water vapor

signal 0.25 nm filter, 0.25 mrad fov

– 36 hour measurement period Toward an automated, eye-safe

configuration– Aerosol depolarization

Cirrus cloud studies – RR Temperature (DiGirolamo et. al.)

Demonstration of eye-safe concept– Liquid water

Cloud droplet retrieval studies

Water Vapor Mixing Ratio PrecisionWater Vapor Mixing Ratio Precision

(Dryline May 22, 2002)(Dryline May 22, 2002)

• Full Resolution (1 minute, 30 meters)• Less than 10% to beyond 2 km.

• As Distributed (2 min, 60-210 meters)• day <10% in BL• night <2% in BL, <10% to 6km

Measurement improvements

permit convective

processes to be studied

throughout the diurnal cycle

NightDay

ExampleExampleJune 3-4 June 3-4

The full dataset

DayNight Night

The June 4 bore

June 19-20 BoreJune 19-20 Bore

Evidence of wave action in several locationsDay Night

Oscillations in the lower cirrus layerOscillations in the lower cirrus layer

Temperature Dependent Lidar EquationsTemperature Dependent Lidar Equations

Aerosol Scattering Ratio EquationsAerosol Scattering Ratio Equations

Water Vapor Mixing Ratio EquationsWater Vapor Mixing Ratio Equations

<0.1% error with calibration lamp

10% uncertainty (1976)!!=1.0 in far fieldRatio of MWs

and N2 fraction

<1% error in ratio Ratio of lidar signals

Differential transmission1-2% uncertainty for moderate aerosol loading

A first principles Raman water vapor lidar calibration is straightforward and can be done with

high accuracy except for the knowledge of the Raman cross sections.

Analysis of CARL data indicates standard error of

0.04% over more than 1 year!

Calibration constants from Aqua Calibration constants from Aqua validation measurementsvalidation measurements

260 280 300 320 340 360

0.005

0.01

0.015 GPS x 309.374, 27.8469

275 300 325 350 375 400

0.002

0.004

0.006

0.008

0.01

0.012

0.014

VIZ x 338.188, 31.7734

SuomiNet GPS (PW) Sippican radiosonde(profile ~1-2 km)

• Comparison of AIRS observations and Fast Model calculations (February, 2003)• SRL water vapor + sonde T, P (GSFC)• RS-90s at the ARM SGP site

• Implication is a wet bias of the lidar of 5-15% with respect to RS-90s (rule of thumb 1K ~ 12% RH in UT)

• Previous work would have implied a 3-4% dry bias instead…

(data courtesy L. Strow, S. Hannon)

IHOP Specific CalibrationIHOP Specific Calibration(Nighttime comparisons only)(Nighttime comparisons only)

Use of the Aqua-validation-derived SRL calibration constant during IHOP yields results ~4% wet of nighttime GPS measurements from IHOP.Is there a meteorologically dependent bias in the SuomiNet retrievals?

SummarySummary Water vapor random error less than 10% throughout

the boundary layer during the daytime– <2% less at night

Raman water vapor lidar could be calibrated with high accuracy from first principles– Raman cross sections limit – State of the art measurement of cross sections could permit

calibration with absolute accuracy of 5-7% Implementing calibration of aerosol and water vapor

data that accounts for temperature dependence of Raman spectra

Current analysis indicates an IHOP specific calibration constant ~4% dry of that used for the preliminary data release