Temperature Retrievals for a Three-Channel Rayleigh Lidar System

We present the performance of a middle atmosphere Rayleigh lidar system that employs three receiver channels. We characterize the biases in the density and temperature profiles retrieved from each of the receiver channels as well as the combined receiver signal. We associate these biases with pulse pile-up, gain switching, and variations in the detector gain due to signal amplitude. We use a top-down temperature convergence methodology to determine the upper altitude up to which the signals should be compensated for the variations in detector gain. We find that the channels have warm biases in their temperatures of 2–8 K at 40 km. These biases decrease to between 1 K and 3 K at 60 km. Uncertainty estimates derived from the photon-counting statistics indicate temperature uncertainties on the order of 2–5 K in the 40–70 km region, which are consistent with the observed level of inter-channel variability after correction. A comparison with MERRA-2 reanalysis indicates an overall agreement in temperatures and differences that are consistent with the comparisons between the Rayleigh lidars and MERRA-02 at other sites. These results demonstrate that the proposed approach proves reliable for processing the multi-channel Rayleigh lidar data, particularly for systems employing more than two detection channels, and improves the fidelity and accuracy of the temperature retrievals.

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Publication Details

Journal
Atmosphere
Published
2026-04-15
DOI
https://doi.org/10.3390/atmos17040400
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Temperature Retrievals for a Three-Channel Rayleigh Lidar System

Jintai Li, Satyaki Das, Richard Collins
Atmosphere
Atmospheric aerosols and clouds
article

Temperature Retrievals for a Three-Channel Rayleigh Lidar System

Jintai Li, Satyaki Das, Richard Collins
article en

Abstract

We present the performance of a middle atmosphere Rayleigh lidar system that employs three receiver channels. We characterize the biases in the density and temperature profiles retrieved from each of the receiver channels as well as the combined receiver signal. We associate these biases with pulse pile-up, gain switching, and variations in the detector gain due to signal amplitude. We use a top-down temperature convergence methodology to determine the upper altitude up to which the signals should be compensated for the variations in detector gain. We find that the channels have warm biases in their temperatures of 2–8 K at 40 km. These biases decrease to between 1 K and 3 K at 60 km. Uncertainty estimates derived from the photon-counting statistics indicate temperature uncertainties on the order of 2–5 K in the 40–70 km region, which are consistent with the observed level of inter-channel variability after correction. A comparison with MERRA-2 reanalysis indicates an overall agreement in temperatures and differences that are consistent with the comparisons between the Rayleigh lidars and MERRA-02 at other sites. These results demonstrate that the proposed approach proves reliable for processing the multi-channel Rayleigh lidar data, particularly for systems employing more than two detection channels, and improves the fidelity and accuracy of the temperature retrievals.

AtmosphereVol. 17(4)
University of Alaska Fairbanks (US)
National Science Foundation, National Aeronautics and Space Administration
Openalex Percentile: Top 17%
Atmospheric aerosols and clouds
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Temperature Retrievals for a Three-Channel Rayleigh Lidar System — Jintai Li, Satyaki Das, et al. · Atmosphere (2026) | TGRS Research Map | TGRS