Abstract

Abstract. The Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission released version 4.00 of their lidar level 1 data set in April of 2014, and subsequently updated this to version 4.10 in November of 2016. The primary difference in the newly released version 4 (V4) data is a suite of updated calibration coefficients calculated using substantially revised calibration algorithms. This paper describes the revisions to the V4 daytime calibration procedure for the 532 nm parallel channel. As in earlier releases, the V4 daytime calibration coefficients are derived by scaling the raw daytime signals to the calibrated nighttime signals acquired within a calibration transfer region, and thus the new V4 daytime calibration benefits from improvements made to the V4 532 nm nighttime calibration. The V4 calibration transfer region has been moved upward from the upper troposphere to the more stable lower stratosphere. The identification of clear-air columns by an iterative thresholding scheme, crucial to selecting the observation regions used for calibration, now uses uncalibrated 1064 nm data rather than recursively using the calibrated 532 nm data, as was done in version 3 (V3). A detailed account of the rationale and methodology for this new calibration approach is provided, along with results demonstrating the improvement of this calibration over the previous version. Extensive validation data acquired by NASA's airborne high spectral resolution lidar (HSRL) shows that during the daytime the average difference between collocated CALIPSO and HSRL measurements of 532 nm attenuated backscatter coefficients is reduced from 3.3 %±3.1 % in V3 to 1.0 %±3.5 % in V4.

Highlights

  • The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), on-board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, has been providing a near-continuous record of high-resolution vertical profiles of clouds and aerosols since the summer of 2006

  • No effort was made to ensure a seamless transition from the version 3 (V3) 532 nm daytime calibration coefficients to the adjoining V3 nighttime calibration coefficients, and abrupt discontinuities frequently occur in the calibration time series at both terminators of the daytime orbit

  • In this paper we have described the new procedures implemented in CALIOP’s version 4 (V4) data release to better calibrate the 532 nm daytime measurements

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Summary

Introduction

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), on-board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, has been providing a near-continuous record of high-resolution vertical profiles of clouds and aerosols since the summer of 2006. Getzewich et al.: CALIPSO lidar calibration at 532 nm nique (Russell et al, 1979; Powell et al, 2009; Kar et al, 2018), in which calibration coefficients are determined by taking the ratio of the measured signal to the expected signal computed using an atmospheric model This approach assumes that all constituents of the nighttime normalization region (i.e., including aerosol loading) can be accurately modeled or characterized. The same technique cannot be used during daytime, because the SNR is substantially lower due to the influence of the reflected solar background radiation This is rectified by scaling the daytime to the nighttime calibration by using clear air attenuated scattering ratios, defined as the ratio between the measured attenuated backscatter and modeled molecular signal.

Version 3 532 nm daytime calibration
Version 4 532 nm daytime calibration
Signal adjustments
Revised calibration transfer region
Mitigation of reduced SNR
Identifying clear air attenuated scattering ratios
Derivation of attenuated scattering ratio and scattering ratio uncertainty
Derivation of calibration coefficient and calibration coefficient uncertainty
Accommodating missing data
Calculating profiles of total attenuated backscatter coefficients
Data latencies
Mission level performance
Zonal distributions of day and night attenuated scattering ratios
Probability of feature detection using 1064 nm
Comparisons to HSRL measurements
Findings
Concluding remarks
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