The detection and measurement of precipitation has been pursued since the beginnings of radar, and the early history has been summarized by Atlas and Ulbrich (1990). Joss and Waldvogel (1990) have reviewed the use of reflectivity at a single polarization to estimate rainfall. Dual-wavelength radars have been used to measure attenuation from which rainfall is estimated (Eccles and Mueller 1973). More recently, attenuation-based methods have been evaluated both theoretically and experimentally for airborne and spaceborne radars (for example, see Meneghini and Kozu 1990). This chapter focuses on dual-polarization radar methods to estimate rainfall (Seliga and Bringi 1976; 1978) based on the microphysical properties of rain discussed in Chapter 7.

Rainfall measurement techniques can be broadly classified as: (i) physically based, and (ii) statistical/engineering based. Physically based rainfall algorithms (as defined here) rely on physical models of the rain medium without any feedback from rain gage observations, whereas statistical/engineering solutions are derived using such feedback either directly or indirectly. Both techniques are considered in this chapter.

The main advantage of using radar for precipitation estimation is that radars can obtain measurements over large areas (about 10 000 km2) with fairly high temporal and spatial resolution. Just substituting a gage for each radar spatial sample (150 m resolution in range and one-degree resolution in azimuth) would require more than one-quarter of a million gages over a 150-km radius. These measurements are sent to a central location at the speed of light by “natural” networks.