whiteman

Scanning Raman Lidar Error Characteristics and Calibration For IHOP: 

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: 

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)

Scanning Raman Lidar : 

Scanning 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 Precision(Dryline May 22, 2002): 

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

ExampleJune 3-4 : 

Example June 3-4 The full dataset

June 19-20 Bore: 

June 19-20 Bore

Oscillations in the lower cirrus layer: 

Oscillations in the lower cirrus layer

Temperature Dependent Lidar Equations: 

Temperature Dependent Lidar Equations

Aerosol Scattering Ratio Equations: 

Aerosol Scattering Ratio Equations

Water Vapor Mixing Ratio Equations: 

Water Vapor Mixing Ratio Equations 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.

Calibration constants from Aqua validation measurements: 

Calibration constants from Aqua validation measurements SuomiNet GPS (PW) Sippican radiosonde (profile ~1-2 km)

Slide12: 

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 Calibration(Nighttime comparisons only): 

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: 

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