Nowcasting of kinetic energy of hail precipitation using radar

The detection of hail precipitation generated by a storm is a complicated task due to the limited spatial extension and the space-time irregularity of impacts generated on the ground. Some of the most extensive methods to create climatology of these impacts are observer networks or hailpad networks. Both methods are affected by numerous inconveniences, overall when it is necessary to work with an extensive area, in which it is necessary to maintain an operating network that has numerous maintenance costs.In this sense, there are numerous works done that have developed different models with the objective of detecting hail precipitation using meteorological radar. Some of these methods use discriminant statistic techniques that, through the combination of different radar parameters, can achieve very satisfactory results. On the other hand, it would be very interesting to know not only the probability of hail, but also some of the characteristics of the hailstones precipitated, such as the number or their kinetic energy, since these parameters are directly related to the damage generated in infrastructures and/or crops.The estimation of kinetic energy of hail precipitation using meteorological radar has caught the interest of some authors. In our case, we used the databases obtained by hailpad networks and the databases of C-band and S-Band radar to build an algorithm to estimate the vertical component of kinetic energy produced by a hail precipitation. In order to carry out this study, data on hail was gathered and analyzed from the hailpad networks in the province of Zaragoza (in the north-east of Spain) and the province of Mendoza (in Argentina, close to the Andes range on the border with Chile). These are two geographically distant regions, but which share a common characteristic: a high frequency of storms with hail precipitation, mainly during the summer months (Sánchez et al., 2009a).In order to compile the database, we have established two categories of kinetic energy: hail with low energy (< 20 J m− 2) and hail with high energy (> 20 J m− 2). With this information, we have looked to establish a differentiation between hail precipitation that hardly produces damage and, on the contrary, that which does (Dessens et al., 2007). Once these two categories were established, we constructed a logistic function that establishes a correspondence between radar variables and the two categories of kinetic energy.The results show great uncertainty in determining kinetic energy using C-band radar. However, for the S-band radar the results have shown that the probability of detection is 85.7% with a FAR of 14.3% and an explained variance of 61.2%. This result allows us, with corresponding caution, to make a first estimation of the areas in which a hailstorm could produce damage.With the objective of making a meteorological interpretation of the results obtained (achieved only using statistic criteria), we have previously done an Principal Components Analysis (PCA).