TC Science Objectives for CALIPSO · CALIPSO 1064 Calibration Issues 532 nm attenuated backscatter...

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 1 TC 4  Science Objectives for CALIPSO Chip Trepte NASA Langley Research Center with contributions from: M. Vaughan, M. Pitts, Y. Hu, J. Mace, M. McGill, D. Hlavka, B. Hart, and D. Winker

Transcript of TC Science Objectives for CALIPSO · CALIPSO 1064 Calibration Issues 532 nm attenuated backscatter...

Page 1: TC Science Objectives for CALIPSO · CALIPSO 1064 Calibration Issues 532 nm attenuated backscatter profiles calibrated against molecular backscatter profiles 532 nm channel calibration

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TC4 Science Objectives for CALIPSO

Chip TrepteNASA Langley Research 

Center

with contributions from:

M. Vaughan, M. Pitts, Y. Hu, J. Mace, M. McGill, D. Hlavka, B. Hart, and D. Winker

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Laser   Nd: YAG, 2x110 mJ Wavelength  532 nm, 1064 nm Repetition rate  20.16 Hz Receiver telescope   1.0 m diameter Polarization  532 

 

Wavelength  645 nm Spectral bandwidth  50 nm IFOV / Swath  125 m / 61 km 

  

Wavelength  8.65, 10.6,12.05 µ µ

CALIOP

Imaging Infrared Radiometer (IIR)

Wide­Field Camera (WFC)

Payload Specifications

Wide Field Camera

Imaging InfraredRadiometerLidar 

Transmitter

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Clear­air Profiles

Page 4: TC Science Objectives for CALIPSO · CALIPSO 1064 Calibration Issues 532 nm attenuated backscatter profiles calibrated against molecular backscatter profiles 532 nm channel calibration

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532­parallel calibration

scale factor = 3.3872 x 10­

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Thermal Effect?

532­parallel channel calibrated by normalization of high­altitude returns (30­34 km) to molecular density

Stratospheric Aerosol?

Calibration coefficients during a 2­week period, derived from 30­34 km signal averaged 6000 km along­track

RMS variability of calibration coefficients slightly larger than expected from signal noise alone

(RMS ~ 1%)

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Validation Intercomparisons: CloudsAugust 12, 2006

532 nm Calibrated Attenuated BackscatterCoincidence

Coincidence

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Validation Intercomparisons: Aerosols

August 10, 2006

Coincidence

532 nm Attenuated Backscatter (km­1 sr­1)

1064 nm Attenuated Backscatter (km­1 sr­1)

Coincidence

CALIPSOHSRL

CALIPSOHSRL

CALIPSO

LaRC HSRL

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Aerosol Subtypes

Cloud­Aerosol Mask

Cloud Phase

CALIPSO Data Products

Level 1: 532 nm total atten. backscatter

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Information from Depolarization

532 nm total attenuated backscatter

532 nm volume depolarization

Arctic cloudsidentification of water, 

and both random and oriented ice crystals

Sahara dust with embedded water clouds

Liquid cloud

Ice cloud

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CALIPSO Scenes over Panama Region

July 25

Aug 8

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CALIPSO Geographical Cloud Occurrence

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CALIPSO Zonal Cloud OccurrenceJuly 2006 Day­Night Cloud Fraction September 2006 Day­Night Cloud Fraction

January 2007 Day­Night Cloud FractionNovember 2006 Day­Night Cloud Fraction

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Verification of CloudSat/CALIPSO Joint Cloud Products

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CALIPSO 1064 Calibration Issues532 nm attenuated backscatter profiles calibrated against molecular backscatter profiles

532 nm channel calibration is transferred to 1064 channel at the top of high altitude clouds where assumed backscatter color ratio (1064/532) = 1.

CPL observations, however, indicate that at times a shift of color ratios to lower values (mode near 0.8).

 

0.5 0.6 0.7 0.8 0.9 1.0Layer­Integrated Attenuated Total Color Ratio

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Frequency

CPL TX­2002 12 December 2002, High Clouds

0 10 20 30 40 50 60 70 80Mean Attenuated Scattering Ratio

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Layer­Integrated Attenuated Total Color Ratio

CPL TX­2002 12 December 2002, High Clouds

Courtesy of CPL Team

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Color Ratio Frequency Distribution

July 2007

Departure from unity suggests erroneous application of color ratio assumption

Courtesy of Y. Hu

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CALIPSO Validation Issues for TC4

Clouds examine detection sensitivity of thin cirrus validate backscatter and extinction profiles verify multiple scattering correction and lidar ratio validate cirrus extinction profiles and examine IWC relationships validate cirrus habit and emissivity examine microphysical interpretation of backscatter color ratio verify cloud feature mask

Aerosols verify aerosol lidar ratio and extinction profiles verify aerosol typing algorithmMuch can be achieved through vicarious 

comparisons using combined aircraft observations

Direct comparisons are not essential