The photon signal-to-noise ratio (SNR) is defined in terms of statistical quantities, and the Poisson and Gaussian probability distribution functions are defined and described. Those distributions are applied to lidar measurements, and the effect of background light on lidar SNR is quantified. The signal-limited and background-limited SNR regimes are defined. The lidar equation is then introduced as a model of the range-dependent lidar signal, and the background model is a constant additional term. All the variables in both models are introduced and defined. They include the number of photons in each laser pulse, the optical efficiencies of the transmitter and receiver, the geometrical function, the receiver solid angle, the range bin length, the volume backscatter coefficient, the extinction coefficient, the spectral radiance of the background, the receiver field of view, the receiver optical bandpass, and the sampling interval of the data system. Finally, a lidar system known as the Eye safe Atmospheric Research Lidar (EARL) is introduced because it is used as an example throughout the rest of the book.

This chapter covers some applications of the atmospheric optics and the engineering principles in the previous chapters as they are employed in operational and proposed lidars. Many of the previous examples involved elastic backscatter aerosol lidars, so this chapter also includes many of the other most common types: wind lidars of several kinds; Rayleigh temperature lidar; differential absorption lidar (DIAL); Raman lidar for profiling trace gases, aerosols, and temperature; high spectral resolution lidar (HSRL); and resonance fluorescence lidar. Descriptions of these techniques are presented here with appropriate references, along with comments on the engineering challenges of these various types of lidars and the ways that they illustrate the principles laid out in the previous chapters. The data analysis algorithms for most of these types of lidar are derived. The laser remote sensing technique known as integrated path differential absorption (IPDA) is also described, along with its data analysis.

An overview of optical scattering in the atmosphere includes the sizes and concentration of scatterers, the mathematical formalism of scattering, and definitions of the lidar scattering and extinction coefficients. The Rayleigh, Mie, and geometric scattering regimes are defined by the scattering parameter, and implications of Rayleigh scattering on lidar measurements are elucidated for both signals and background. Molecules store energy in translational, rotational, and vibrational motions, and atoms store energy in electronic excitations. These energy storage mechanisms cause the lidar observables of Doppler shifts, molecular and Raman spectra, and atomic spectra, which, along with Rayleigh scattering, enable lidar measurements of temperatures and winds; water vapor and trace gas concentrations; and aerosol extinction coefficients at altitudes from the surface up to the mesosphere and lower thermosphere. The lidar techniques that exploit all these phenomena operate over a range of wavelengths from the long wave infrared to the ultraviolet and the reasons for the differing wavelengths of the various techniques are explained with a graphic that summarizes the chapter.

A brief overview and description of the atmospheric lidar measurement technique is followed by the structure of the atmosphere in terms of the troposphere, stratosphere, and mesosphere, as it is usually presented in atmospheric science and meteorology. The atmosphere is then described in terms of lidar observables at all altitudes, including water vapor; trace gases; clouds; several other kinds of particulate matter; and metal atoms, as well as density, temperature, and winds. Examples of lidar measurements include tropospheric and stratospheric ozone, greenhouse gases, other pollutants, tropospheric and stratospheric aerosols, polar stratospheric clouds, and atoms of sodium, potassium, calcium, and iron in the mesosphere. Finally, the structure and contents of the book are described, and suggestions for further reading are given.

This chapter begins with a brief review of electronic circuitry and terminology because optical detection and signal processing are in the realm of electrical engineering. A detailed discussion of analog detection follows, with circuitry including transimpedance amplifiers and equivalent circuits for analyzing noise and bandwidth. Two electronic noise sources are introduced, Johnson noise and amplifier noise, and their effects on SNR are modeled. Photon counting is then discussed in terms of its instrumentation, advantages, and limitations. The basic principles of coherent detection are elucidated through a mathematical derivation, and the advantages of coherent detection are shown: high SNR, optical background discrimination, and the measurement of Doppler shifts to sense winds. The main types of detectors used in lidar systems are then discussed, including intrinsic and PIN photodiodes, photomultipliers, avalanche photodiodes, and single-photon avalanche diodes. The advantages of internal detector gain for optimizing SNR are quantified.