NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
CALIPSO Lidar Calibration at 532 nm: Version 4 Nighttime AlgorithmData products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP’s other radiometric calibration procedures – i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime – depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30-34 km to 36-39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. As well, an enhanced strategy for filtering the radiation-induced noise from high energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved MERRA-2 model. An aerosol scattering ratio of 1.01 ± 0.01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2-3% lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne high spectral resolution lidar (HSRL) are reduced from 3.6% ± 2.2% in the version 3 data set to 1.6% ± 2.4 % in the version 4 release.
Document ID
20190026625
Acquisition Source
Langley Research Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Jayanta Kar ORCID
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Mark A. Vaughan ORCID
(Langley Research Center Hampton, Virginia, United States)
Kam-Pui Lee
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Jason L. Tackett
(Science Systems & Applications, Inc. Hampton, VA, USA)
Melody A. Avery ORCID
(Langley Research Center Hampton, Virginia, United States)
Anne Garnier
(Science Systems & Applications, Inc. Hampton, VA, USA)
Brian J. Getzewich
(Science Systems & Applications, Inc. Hampton, VA, USA)
William H. Hunt
(Science Systems & Applications, Inc. Hampton, VA, USA)
Damien Josset
(Science Systems & Applications, Inc. Hampton, VA, USA)
Zhaoyan Liu ORCID
(Langley Research Center Hampton, Virginia, United States)
Patricia L. Lucker
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Brian Magill
(Science Systems & Applications, Inc. Hampton, VA, USA)
Ali H. Omar
(Langley Research Center Hampton, Virginia, United States)
Jacques Pelon
(Institut Pierre-Simon Laplace Paris, France)
Raymond R. Rogers
(Langley Research Center Hampton, Virginia, United States)
Travis D. Toth
(Langley Research Center Hampton, Virginia, United States)
Charles R. Trepte
(Langley Research Center Hampton, Virginia, United States)
Jean-Paul Vernier
(Science Systems & Applications, Inc. Hampton, VA, USA)
David M. Winker
(Langley Research Center Hampton, Virginia, United States)
Stuart A. Young ORCID
(Science Systems & Applications, Inc. Hampton, VA, USA)
Date Acquired
June 25, 2019
Publication Date
March 14, 2018
Publication Information
Publication: Atmospheric Measurement Techniques
Publisher: European Goesciences Union
Volume: 11
Issue Publication Date: March 14, 2018
ISSN: 1867-1381
e-ISSN: 1867-8548
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
NF1676L-29299
Funding Number(s)
WBS: 653967.04.12.01
PROJECT: SCMD-EarthScienceSystem_653967
Distribution Limits
Public
Copyright
Public Use Permitted.
No Preview Available