Scattering and Propagation of Polarimetric Radar Signals in Storms and Clouds

The introduction of differential reflectivity (Z_dr) and propagation differential phase (Phi_dp) was originally intended for improving radar estimates of rainfall rate. These parameters together with the effective reflectivity factor (Z_h) proved to be very useful for other applications as well. They have been shown to produce significant improvements over conventional single polarization radars in discriminating liquid and ice phase hydrometeors and, with the aid of several other polarimetric parameters (linear depolarization ratio and co-polar correlation coefficient), for classifying different hydrometeor types. Radar techniques developed for these purposes are being used in research applications and will soon become operational tools. The classification of ice phase hydrometeors and the quantitative estimation of their bulk parameters (e.g., median size, ice mass content, etc.) are necessary for better understanding storms and clouds. As methodologies are developed for extracting more information about hydrometeors using polarimetric radars, it becomes increasingly important to model the hydrometeors more accurately. Their shape, size, fall behavior, and composition must be represented with sufficient detail, capturing the dominant features that influence the measured radar parameters. This paper reviews developments in hydrometeor modeling for dual-polarization radar remote sensing applications. The use of these modeling results in various applications such as rainfall rate estimation and hydrometeor classification are illustrated with the aid of experimental measurements. The first application of the "self-consistency" principle is discussed using dual-frequency polarimetric radar parameters (S-band Z_h and Z_dr with X-band Z_h and specific attenuation A_h).