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Polarimetric radar are shown to be capable of tornado detection through the recognition of tornadic debris signatures that are characterized by the anomalously low cross-correlation coefficient [[rho].sub.hv] and differential reflectivity [Z.sub.DR]. This capability is demonstrated for three significant tornadic storms that struck the Oklahoma City, Oklahoma, metropolitan area. The first tornadic debris signature, based on the measurements with the National Severe Storms Laboratory's Cimarron polarimetric radar, was reported for a storm on 3 May 1999. Similar signatures were identified for two significant tornadic events during the Joint Polarization Experiment (JPOLE) in May 2003. The data from these storms were collected with a polarimetric prototype of the Next-Generation Weather Radar (NEXRAD). In addition to a small-scale debris signature, larger-scale polarimetric signatures that might be relevant to tornadogenesis were persistently observed in tornadic supercells. The latter signatures are likely associated with lofted light debris (leaves, grass, dust, etc.) in the inflow region and intense size sorting of hydrometeors in the presence of strong wind shear and circulation.

Compelling in situ and polarimetric radar observations from a severe Oklahoma supercell storm are presented. The in situ observations are from an aircraft that entered the storm above the main inflow region, sampling the embryo curtain, main updraft, its western fringe (very close to the center of mesocyclonic circulation), and the hail cascade region. At the same time, the Cimarron polarimetric radar observed enhanced signatures in specific differential phase [K.sub.dp] and differential reflectivity [Z.sub.dr] straddling the main updraft and extending several kilometers above the melting layer. The distance of the storm from the radar balances the novelty of this dataset, however, which is on the order of 100 km. The authors therefore rely heavily on the in situ data, including calculation of polarimetric variables, on comparisons with other in situ datasets, and on accepted conceptual models of hail growth in supercell storms to clarify hydrometeor processes in light of the intriguing polarimetric signatures near the updraft. The relation of enhanced [K.sub.dp] tO the main updraft, to the [Z.sub.dr] 'column,' and to precipitation is discussed. Strong evidence points to melting ice particles (>3 mm) below the aircraft height as the origin of the [K.sub.dp] column in the region where an abundant number of small (

An analysis of drop size distributions (DSDs) measured in four very different precipitation regimes is presented and is compared with polarimetric radar measurements. The DSDs are measured by a 2D video disdrometer, which is designed to measure drop size, shape, and fall speed with unprecedented accuracy. The observations indicate that significant DSD variability exists not only from one event to the next, but also within each system. Also, despite having vastly different storm structures and maximum rain rates, large raindrops with diameters greater than 5 mm occurred with each system. By comparing the occurrence of large drops with rainfall intensity, the authors find that the largest median diameters are not always associated with the heaviest rainfall, but are sometimes located either in advance of convective cores or, occasionally, in stratiform regions where rainfall rates are relatively low. Disdrometer and polarimetric radar measurements of radar reflectivity Z, differential reflectivity [Z.sub.DR], specific differential phase [K.sub.DP], and R(Z) and R([K.sub.DP]) rain-rate estimators are compared in detail. Overall agreement is good, but it is found that both R(Z) and R([K.sub.DP]) underestimate rain rate when the DSD is dominated by small drops and overestimate rain rate when the DSD is dominated by large drops. The results indicate that a classification of different rain types (associated with different DSDs) should be an essential part of polarimetric rainfall estimation. Furthermore, observations suggest that [Z.sub.DR] is a key parameter for making such a distinction. Last, the authors compute and compare maximum and average of gamma shape, slope, and intercept parameters for all four precipitation events. Potential measurement errors with the 2D video disdrometer are also discussed.

A new synthesis of information forming the foundation for rule-based systems to deduce dominant bulk hydrometeor types and amounts using polarimetric radar data is presented. The information is valid for a 10-cm wavelength and consists of relations that are based on an extensive list of previous and recent observational and modeling studies of polarimetric signatures of hydrometeors. The relations are expressed as boundaries and thresholds in a space of polarimetric radar variables. Thus, the foundation is laid out for identification of hydrometeor types (species), estimation of characteristics of hydrometeor species (size, concentrations, etc.), and quantification of bulk hydrometeor contents (amounts). A fuzzy classification algorithm that builds upon this foundation will be discussed in a forthcoming paper.