A. Detection of hail within the cloud or on the ground (that is, hail yes/no), or an estimate of the probability of hail in the cell. The ability to discriminate rainstorms from hailstorms is valuable for many forecasting and scientific purposes. B. Quantitative estimation of hail at the ground either as a point estimate at a single time, or as some quantity integrated over area and time. Examples of such metrics are: Kinetic energy flux, Mass of hail, Hail rate. C. Hail metrics aloft that might be more sensitive to seeding effects.
The measurement of hail with conventional radar is a problem. The main difficulties are connected with the unknown contribution of rain to the total power that is backscattered to the radar, the size distribution of the hail, and to perhaps lesser extent the physical nature of the hailstone that affects its backscattering properties (existence of a water layer, spongy property, etc). For conventional radars, we are limited to reflectivity measurements alone, and not to various polarization or multi-wavelength measurements where the physical properties of the hail can be used to advantage for detection and measurement. Although highly accurate measurements of hailfall have been claimed by some authors using reflectivity alone (for example in Switzerland), such results have generally not been found in other locations.
The idea behind looking for hail metrics aloft, relates partly to the difficulties inherent in measuring hail at the surface in the presence of rain. In addition, if seeding in fact leads to the changes in the size distribution postulated by the seeding hypothesis (more stones of a smaller size), such changes must first be evident aloft in the hail growth zone. It might be much easier to detect a seeding effect by looking in this region.
There have been arguments made since the mid 1970s that hail growth in supercell storms can be inherently different than in other storms, and that hail suppression might be more difficult. Browning and Foote (1976) argued that the presence of a weak echo region, also called a vault, was strong evidence that the natural hail process was very inefficient, and that certain dominant growth trajectories could not be eliminated even by intense seeding. Given the possibility that storms of different types and different intensities might respond differently to seeding, it is important to be able to classify storms into groups where the response is expected to be more uniform. Objectively classifying storms based on their structural characteristics is very difficult and somewhat subjective. More recently, Abshaev in Russia has developed a scheme that uses only the maximum reflectivity and the height of the 45-dBZ echo, and has shown very intriguing results.
This paper will report on some work in progress using C-band radar data from the Mendoza, Argentina and Alberta, Canada hail suppression projects conducted by Weather Modification Inc. The sensitivity and variation with time of several radar hail parameters computed using the TITAN (Thunderstorm, Identification, Tracking, Analysis, and Now-casting) system will be presented. The hail parameters are: Probability of Hail, Hail Mass Aloft, Vertical Integrated Hail Mass, Hail Kinetic Energy Flux, and an exploratory storm severity index based on the Abshaev classification scheme. The usefulness of these parameters for real-time decision-making and the evaluation of the responses to seeding will also be discussed.