Literature DB >> 33414857

Cloud Aerosol Transport System (CATS) 1064 nm Calibration and Validation.

Rebecca M Pauly1, John E Yorks2, Dennis L Hlavka1, Matthew J McGill2, Vassilis Amiridis3, Stephen P Palm1, Sharon D Rodier4, Mark A Vaughan5, Patrick A Selmer1, Andrew W Kupchock1, Holger Baars6, Anna Gialitaki3.   

Abstract

The Cloud-Aerosol Transport System (CATS) lidar on board the International Space Station (ISS) operated from 10 February 2015 to 30 October 2017 providing range-resolved vertical backscatter profiles of Earth's atmosphere at 1064 and 532 nm. The CATS instrument design and ISS orbit lead to a higher 1064 nm signal-to-noise ratio than previous space-based lidars, allowing for direct atmospheric calibration of the 1064 nm signals. Nighttime CATS Version 3-00 data were calibrated by scaling the measured data to a model of the expected atmospheric backscatter between 22 and 26 km above mean sea level (AMSL). The CATS atmospheric model is constructed using molecular backscatter profiles derived from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) re-analysis data and aerosol scattering ratios measured by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The nighttime normalization altitude region was chosen to simultaneously minimize aerosol loading and variability within the CATS data frame, which extends from 28 km to -2 km AMSL. Daytime CATS Version 3-00 data were calibrated through comparisons with nighttime measurements of the layer integrated attenuated total backscatter (iATB) from strongly scattering, rapidly attenuating opaque cirrus clouds. The CATS nighttime 1064 nm attenuated total backscatter (ATB) uncertainties for clouds and aerosols are primarily related to the uncertainties in the CATS nighttime calibration technique, which are estimated to be ~9%. Median CATS V3-00 1064 nm ATB relative uncertainty at night within cloud and aerosol layers is 7%, slightly lower than these calibration uncertainty estimates. CATS median daytime 1064 nm ATB relative uncertainty is 21% in cloud and aerosol layers, similar to the estimated 16-18% uncertainty in the CATS daytime cirrus cloud calibration transfer technique. Coincident daytime comparisons between CATS and the Cloud Physics Lidar (CPL) during the CATS-CALIPSO Airborne Validation Experiment (CCAVE) project show good agreement in mean ATB profiles for clear-air regions. Eight nighttime comparisons between CATS and the PollyXT ground based lidars also show good agreement in clear-air regions between 3-12 km, with CATS having a mean ATB of 19.7 % lower than PollyXT. Agreement between the two instruments (~7%) is even better within an aerosol layer. Six-month comparisons of nighttime ATB values between CATS and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) also show that iATB comparisons of opaque cirrus clouds agree to within 19%. Overall, CATS has demonstrated that direct calibration of the 1064 nm channel is possible from a space based lidar using the atmospheric normalization technique.

Entities:  

Year:  2019        PMID: 33414857      PMCID: PMC7786814          DOI: 10.5194/amt-12-6241-2019

Source DB:  PubMed          Journal:  Atmos Meas Tech        ISSN: 1867-1381            Impact factor:   4.176


  11 in total

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Authors:  Matthew McGill; Dennis Hlavka; William Hart; V Stanley Scott; James Spinhirne; Beat Schmid
Journal:  Appl Opt       Date:  2002-06-20       Impact factor: 1.980

2.  Examination of the traditional Raman lidar technique. I. Evaluating the temperature-dependent lidar equations.

Authors:  David N Whiteman
Journal:  Appl Opt       Date:  2003-05-20       Impact factor: 1.980

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Journal:  Appl Opt       Date:  1981-01-15       Impact factor: 1.980

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Authors:  M Del Guasta
Journal:  Appl Opt       Date:  1998-08-20       Impact factor: 1.980

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Authors:  J D Spinhirne; S Chudamani; J F Cavanaugh; J L Bufton
Journal:  Appl Opt       Date:  1997-05-20       Impact factor: 1.980

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Journal:  Appl Opt       Date:  1984-03-01       Impact factor: 1.980

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Journal:  Appl Opt       Date:  2008-12-20       Impact factor: 1.980

8.  The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2).

Authors:  Ronald Gelaro; Will McCarty; Max J Suárez; Ricardo Todling; Andrea Molod; Lawrence Takacs; Cynthia Randles; Anton Darmenov; Michael G Bosilovich; Rolf Reichle; Krzysztof Wargan; Lawrence Coy; Richard Cullather; Clara Draper; Santha Akella; Virginie Buchard; Austin Conaty; Arlindo da Silva; Wei Gu; Gi-Kong Kim; Randal Koster; Robert Lucchesi; Dagmar Merkova; Jon Eric Nielsen; Gary Partyka; Steven Pawson; William Putman; Michele Rienecker; Siegfried D Schubert; Meta Sienkiewicz; Bin Zhao
Journal:  J Clim       Date:  2017-06-20       Impact factor: 5.148

9.  Seasonally Transported Aerosol Layers over Southeast Atlantic are Closer to Underlying Clouds than Previously Reported.

Authors:  Chamara Rajapakshe; Zhibo Zhang; John E Yorks; Hongbin Yu; Qian Tan; Kerry Meyer; Steven Platnick; David M Winker
Journal:  Geophys Res Lett       Date:  2017-06-12       Impact factor: 4.720

10.  Increase in upper tropospheric and lower stratospheric aerosol levels and its potential connection with Asian pollution.

Authors:  J-P Vernier; T D Fairlie; M Natarajan; F G Wienhold; J Bian; B G Martinsson; S Crumeyrolle; L W Thomason; K M Bedka
Journal:  J Geophys Res Atmos       Date:  2015-02-16       Impact factor: 4.261

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  1 in total

1.  Assessment and Error Analysis of Terra-MODIS and MISR Cloud-Top Heights Through Comparison With ISS-CATS Lidar.

Authors:  Arka Mitra; Larry Di Girolamo; Yulan Hong; Yizhe Zhan; Kevin J Mueller
Journal:  J Geophys Res Atmos       Date:  2021-05-02       Impact factor: 4.261

  1 in total

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