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1. A Na density lidar method and measurements of turbulence to 105 km at the Andes Lidar Observatory

   https://doi.org/10.1016/j.jastp.2021.105642  

   Philbrick, Channing P.; Yang, Fan; Vargas, Fabio A.; Swenson, Gary R.; Liu, Alan Z. (August 2021, Journal of Atmospheric and Solar-Terrestrial Physics)

   null (Ed.)
2. Lidar remote sensing of the aquatic environment: invited

   https://doi.org/10.1364/AO.59.000C92  

   Churnside, James_H; Shaw, Joseph_A (March 2020, Applied Optics)

   This paper is a review of lidar remote sensing of the aquatic environment. The optical properties of seawater relevant to lidar remote sensing are described. The three main theoretical approaches to understanding the performance of lidar are considered (the time-dependent radiative transfer equation, Monte Carlo simulations, and the quasi-single-scattering assumption). Basic lidar instrument design considerations are presented, and examples of lidar studies from surface vessels, aircraft, and satellites are given. 

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3. Probing the Analytical Cancellation Factor of Short Scale Gravity Waves Using Na Lidar and Nightglow Data from the Andes Lidar Observatory

   https://doi.org/10.3390/atmos11121311  

   Vargas, Fabio; Fuentes, Javier; Vega, Pedro; Navarro, Luis; Swenson, Gary (December 2020, Atmosphere)

   null (Ed.)

   The cancellation factor (CF) is a model for the ratio between gravity wave perturbations in the nightglow intensity to those in the ambient temperature. The CF model allows us to estimate the momentum and energy flux of gravity waves seen in nightglow images, as well as the divergence of these fluxes due to waves propagating through the mesosphere and lower thermosphere region, where the nightglow and the Na layers are located. This study uses a set of wind/temperature Na lidar data and zenith nightglow image observations of the OH and O(1S) emissions to test and validate the CF model from the experimental perspective. The dataset analyzed was obtained during campaigns carried out at the Andes Lidar Observatory (ALO), Chile, in 2015, 2016, and 2017. The modeled CF was compared with observed CF values calculated using the ratio of wave amplitude in nightglow images to that seen in lidar temperatures for vertically propagating waves. We show that, in general, the modeled CF underestimates the observed CF results. However, the O(1S) emission line has better agreement with respect to the modeled value due to its supposedly simpler nightglow photochemistry. In contrast, the observed CF for the OH emission deviates by a factor of two from the modeled CF asymptotic value. 

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4. First Arrival Differential LiDAR

   https://doi.org/10.1109/ICCP54855.2022.9887683  

   Zhang, Tianyi; White, Mel J.; Dave, Akshat; Ghajari, Shahaboddin; Raghuram, Ankit; Molnar, Alyosha C.; Veeraraghavan, Ashok (August 2022, IEEE International Conference on Computational Photography (ICCP).)
5. Quantum-enhanced Doppler lidar

   https://doi.org/10.1038/s41534-022-00662-9  

   Reichert, Maximilian; Di Candia, Roberto; Win, Moe Z.; Sanz, Mikel (December 2022, npj Quantum Information)

   Abstract We propose a quantum-enhanced lidar system to estimate a target’s radial velocity, which employs squeezed and frequency-entangled signal and idler beams. We compare its performance against a classical protocol using a coherent state with the same pulse duration and energy, showing that quantum resources provide a precision enhancement in the estimation of the velocity of the object. We identify three distinct parameter regimes characterized by the amount of squeezing and frequency entanglement. In two of them, a quantum advantage exceeding the standard quantum limit is achieved assuming no photon losses. Additionally, we show that an optimal measurement to attain these results in the lossless case is frequency-resolved photon counting. Finally, we consider the effect of photon losses for the high-squeezing regime, which leads to a constant factor quantum advantage higher than 3 dB in the variance of the estimator, given a roundtrip lidar-to-target-to-lidar transmissivity larger than 50%. 

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