Comparative study of lidars for measuring atmospheric temperature and wind

Area of Science:

• Atmospheric remote sensing
• Optical physics
• Meteorology

Background:

• Atmospheric temperature and wind measurements are crucial for weather forecasting and climate studies.
• Lidar (light detection and ranging) systems offer remote sensing capabilities for atmospheric profiling.
• Measurement uncertainty in lidar systems is primarily influenced by the signal-to-noise ratio (SNR).

Purpose of the Study:

• To introduce and utilize single-photon measurement uncertainty as a key metric for evaluating lidar performance.
• To compare the practical efficacy of different lidar techniques: Cabannes scattering (CS), Rayleigh inversion (RI), rotational Raman (RR), and laser induced fluorescence (LIF).
• To guide the selection and receiver design of lidar systems for specific atmospheric measurement applications.

Main Methods:

• Calculating single-photon measurement uncertainty for temperature (T) and line-of-sight (LOS) wind (V) measurements.
• Analyzing the SNR of received photocounts for each lidar technique.
• Comparing the derived single-photon measurement uncertainties across CS, RI, RR, and LIF lidars.

Main Results:

• Single-photon measurement uncertainty quantifies the inherent efficacy of lidar measurement methods.
• Distinct practical differences in measurement efficacy exist between CS, RI, RR, and LIF lidars.
• The choice of lidar technique and receiver design significantly impacts measurement uncertainty.

Conclusions:

• Single-photon measurement uncertainty provides a standardized figure of merit for comparing lidar measurement techniques.
• Understanding these differences is essential for optimizing lidar system performance for atmospheric temperature and wind retrieval.
• This research aids in selecting appropriate lidar technologies and designing effective receiver systems for targeted applications.