Explicit Forecasts of Hail Occurrence and Expected Hail Size Using the GEM–HAILCAST System with a Rainfall Filter

Abstract

Abstract HAILCAST is a numerical model developed specifically to predict the size of the largest hail reaching the ground. It consists of a steady-state cloud model combined with a time-dependent hailstone growth model. The regional version of the Canadian Global Environmental Multiscale (GEM) model is used to provide prognostic model soundings that are used as input data for HAILCAST. A map of forecasted maximum hail size is thereby obtained. Because hail is typically accompanied by rain, it would be advantageous if the GEM–HAILCAST system were to predict the occurrence of hail only in those regions where the GEM model was predicting precipitation. Hence, the utility of applying a forecast rainfall mask from the GEM model to restrict hail forecasts to those areas where rainfall is forecast during a 12-h window centered on 0000 UTC was tested. The accumulated precipitation filter is objective and integrates both the thermodynamic and dynamic output from the GEM model over many time steps. To test the utility of applying the GEM forecast precipitation mask, the masking technique was applied to HAILCAST-predicted maximum hail size maps for the three Canadian prairie provinces between 1 June and 31 August 2000. Several case studies will be presented to illustrate the usefulness of adding the precipitation mask. Verification statistics confirm that applying the rainfall mask tends to slightly reduce the false alarm ratio while still identifying the majority of hail events within a special study area over southern Alberta. The performance of the precipitation masking technique was not as effective on severe hail days, especially when attempting to identify both the occurrence and location of severe hail swaths.