18.3 Radar and lidar applications in atmospheric science

Radar and lidar are powerful tools for probing the atmosphere. These remote sensing techniques use electromagnetic waves to detect and measure atmospheric properties, from precipitation and clouds to wind patterns and air pollution.

Both have unique strengths and limitations. Radar excels at long-range observations and penetrating clouds, while lidar offers high resolution and sensitivity to small particles. Together, they provide a comprehensive view of atmospheric structure and processes.

Radar and Lidar Principles and Applications

Principles of radar and lidar

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  AMT - Why we need radar, lidar, and solar radiance observations to constrain ice cloud microphysics View original

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• Radar (Radio Detection and Ranging) transmits electromagnetic waves in the radio or microwave spectrum and measures the backscattered signal from atmospheric targets like precipitation and clouds
  • Doppler radar measures the radial velocity of targets using the Doppler effect which determines the motion and turbulence within precipitation and clouds
• Lidar (Light Detection and Ranging) uses laser light to probe the atmosphere and measures the backscattered signal from atmospheric constituents like aerosols, trace gases, and clouds
  • Elastic backscatter lidar measures the intensity of backscattered light at the same wavelength as the transmitted laser to detect aerosol layers and mixing height
  • Differential absorption lidar (DIAL) uses two or more wavelengths to measure the concentration of specific atmospheric gases (ozone, nitrogen dioxide)
  • Raman lidar measures the inelastic scattering of light by atmospheric molecules to identify the composition of aerosols and trace gases
• Principles of atmospheric remote sensing
  • Range resolution determines the ability to distinguish between closely spaced targets and is affected by the pulse duration and bandwidth of the transmitted signal
  • Doppler velocity measures the radial velocity of atmospheric targets and is determined by the frequency shift of the backscattered signal
  • Polarization provides information about the shape, size, and orientation of atmospheric targets (hydrometeors)
    • Polarimetric radar uses horizontal and vertical polarizations to extract target characteristics

Applications in atmospheric science

• Precipitation and cloud studies
  • Radar reflectivity measures the intensity of precipitation and cloud droplets
  • Doppler velocity determines the motion and turbulence within precipitation and clouds
  • Polarimetric measurements provide information about the size, shape, and phase of hydrometeors (raindrops, ice crystals)
• Wind and turbulence measurements
  • Doppler lidar measures wind speed and direction profiles in clear air
  • Radar wind profilers provide continuous measurements of wind profiles
  • Turbulence detection using Doppler spectrum width and velocity variations indicate atmospheric turbulence
• Boundary layer and air pollution studies
  • Elastic backscatter lidar detects aerosol layers and mixing height
  • DIAL measures the concentration of specific pollutants (ozone, nitrogen dioxide)
  • Raman lidar identifies the composition of aerosols and trace gases
• Stratospheric and mesospheric observations
  • Temperature and density measurements using Rayleigh and Raman lidar techniques
  • Ozone and other trace gas measurements using DIAL and Raman lidar techniques
  • Polar stratospheric clouds (PSCs) and noctilucent clouds (NLCs) observations using backscatter lidar

Interpretation of radar and lidar data

• Radar reflectivity and precipitation
  • Reflectivity-rainfall rate relationships: $Z = aR^b$, where $Z$ is reflectivity, $R$ is rainfall rate, and $a$ and $b$ are empirical constants
  • Precipitation type identification using polarimetric variables (differential reflectivity, specific differential phase)
• Doppler velocity and wind retrieval
  • Velocity azimuth display (VAD) retrieves wind profiles from Doppler velocity measurements at different azimuth angles
  • Vertical profiles of horizontal wind by combining data from multiple Doppler radars or using a wind profiler
• Lidar backscatter and extinction profiles
  • Klett-Fernald inversion retrieves the atmospheric extinction coefficient from backscatter lidar measurements
  • Depolarization ratio indicates the sphericity of particles and helps identify particle types (ice crystals, dust)
• Combining radar and lidar data
  • Collocated measurements provide a comprehensive view of atmospheric structure and processes
  • Synergistic retrievals improve the accuracy and resolution of atmospheric parameters

Strengths vs weaknesses of observations

• Strengths of radar
  • Long-range observations can detect precipitation and clouds at distances up to hundreds of kilometers
  • High temporal resolution provides continuous monitoring of atmospheric phenomena
  • Ability to penetrate clouds and precipitation allows for observations in adverse weather conditions
• Weaknesses of radar
  • Limited sensitivity to small particles may not detect fine aerosols or cloud droplets
  • Attenuation in heavy precipitation weakens the signal when passing through intense rainfall or hail
  • Ground clutter and anomalous propagation can lead to false or misleading observations near the surface
• Strengths of lidar
  • High spatial resolution provides detailed vertical profiles of atmospheric properties
  • Sensitivity to small particles can detect fine aerosols, cloud droplets, and molecules
  • Multiple wavelengths and techniques allow for the measurement of various atmospheric constituents
• Weaknesses of lidar
  • Limited range due to attenuation of laser light restricts the observation range, especially in cloudy or polluted conditions
  • Inability to penetrate optically thick clouds as the signal is attenuated in dense cloud layers
  • Eye safety concerns as high-power lasers may pose risks to human eyes and require careful operation