Scanning Raman Lidar Error Characteristics 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

Outline

 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)

     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

Scanning Raman Lidar

Water Vapor Mixing Ratio Precision (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

Day Night

Example

June 3-4 The full dataset Night Day Night The June 4 bore

June 19-20 Bore

Oscillations in the lower cirrus layer

Temperature Dependent Lidar Equations

Aerosol Scattering Ratio Equations

Water Vapor Mixing Ratio Equations

<1% error in ratio 1-2% uncertainty for moderate aerosol loading <0.1% error with calibration lamp and N 2 fraction calibration is straightforward and can be done with indicates standard error of high accuracy

except

for the knowledge of the 0.04% over more than 1 year!

Raman cross sections

.

Calibration constants from Aqua validation measurements

0.015

0.01

0.005

260 280 300 320 GPS x 309.374, 0.014

VIZ x 338.188, 27.8469

0.012

0.01

31.7734

0.008

0.006

0.004

0.002

340 360 275 300 325 350 375 400 SuomiNet GPS (PW) Sippican radiosonde (profile ~1-2 km)

• • • (data courtesy L. Strow, S. Hannon) 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…

IHOP Specific Calibration

(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?

Summary

 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