One method of obtaining information about the nature of the atmosphere is to sample it remotely; so-called remote sensing. The idea behind remote sensing is fairly straightforward: electromagnetic radiation which has interacted with the atmosphere will bear the signature of this interaction. Remote sensing involves making measurements of this electromagnetic radiation and, from it, extracting useful information about the nature of the atmosphere. One of first examples of remote sensing was in 1881 when John Hartley deduced the presence of ozone in the upper atmosphere using the UV absorption bands he had measured earlier (Turco, 1997).
Radiative transfer and remote sensing can be thought of as a coupled set of problems with radiative transfer being the forward problem and remote sensing being the inverse. In radiative transfer, given a complete description of the atmosphere, the radiation field can be deduced. By contrast, in remote sensing, given a set of measurements of the radiation field, and using some type of model, an approximate state of the atmosphere can be extracted. Realistically, however, the entire state of the atmosphere at any single time can never be determined. Even a large set of measurements potentially may yield only a few independent pieces of information. The problem arises because the information contained in each measurement is not unique and therefore limits the retrieval potential. Even obtaining a few pieces of independent information is often quite difficult as the atmosphere is a highly complex, non-linear and variable system. An associated problem is estimating the uncertainties associated with a retrieved quantity. It is usually necessary to employ formal retrieval theories, the basic classes of which include linear, statistical, and iterative. Some of the more important atmospheric quantities which can be retrieved include: aerosol number densities, trace gas number densities, surface reflectivities, windspeed, temperature, and precipitation.
The source of the radiation measured can either be natural (passive remote sensing) or artificial (active remote sensing). Natural sources include sunlight, thermal radiation emitted from the atmosphere itself, moonlight, or light from other stars. Artificial sources are much more diverse and span a large portion of the electromagnetic spectrum. Two examples are lidar, or laser radar which is generally in the visible, and doppler radar which uses microwaves. There are also different types of remote sensing platforms with the most common being satellite, ground-based, aircraft-based, and balloon-borne. Active remote sensing instruments are usually ground-based with a few notable exceptions such as the Lidar-In-Space Technology Experiment (LITE).
One of the first examples of quantitative remote sensing was by the French physicist Charles Fabry who, in 1912, made regular measurements of ozone. In 1924 George Dobson built his first ozone spectrophotometer (later called the Dobson spectrometer), an instrument still used today. The first atmospheric observing satellite platform was TIROS (Television and Infrared Observations Satellite) I, launched into a polar orbit in 1960 (Houghton et al., 1984). The first platform to measure atmospheric composition was the Nimbus 7, carrying the first of several TOMS (Total Ozone Mapping Spectrometer) instruments.