RADAR STORM MOTION ESTIMATION AND BEYOND : A SPECTRAL ALGORITHM AND RADAR OBSERVATION BASED DYNAMIC MODEL

Storm motion tracking using a temporal sequence of radar images is an important step in computeraided operational nowcasting (Browning and Collier, 1989; Chornoboy et al, 1994; Wilson et al, 1998). There exist three commonly used approaches for radar storm tracking. The first approach is based on motion field that is identified by employing crosscorrelation technique over two local blocks in two successive radar images (Rinehart and Garvey, 1978; Chornoboy et al, 1994). The second approach is referred to as “centroid tracking” (Austin and Bellon, 1982), such as the storm cell identification and tracking (SCIT) algorithm developed by Johnson et al (1998). The third approach is based on identification of storm’s position, size, mergers and splits that was implemented in the TITAN algorithm, referring to thunderstorm identification, tracking, analysis and nowcasting, developed by Dixon and Wiener (1993). Various improved methods have been developed based on local pattern matching and cross-correlation techniques. For example, Wolfson et al (1999) recently have developed a technique commonly referred as “growth-decay storm tracker”. The “growth-decay storm tracker” employs an elliptically shaped spatial filter such as to enable tracking systematic growth-decay propagations of the larger scale component in storms. In this paper we present the development of a new algorithm developed in spectral domain for estimating the motion field of