Abstract
Hail is a significant weather hazard in Canada, but its spatial and temporal distribution is poorly understood. We compiled a Canadian hail report database for 2005-2022, containing 7000 unique entries with estimates of the timing and location of the hail reports and estimated hail diameter. We developed a methodology to construct an estimate of the hail climatology across Canada using manual hail observations at airports and a lightning proxy. First, we estimated the probability of hail occurrence at airport locations across the country at any given hour using Bayesian inference. Next, we interpolated in space the probabilities to obtain smooth prior probabilities of hail occurrence at any location in Canada. Then, we refined these probabilities using lightning flash density as a proxy for the likelihood of hail, severe hail (diameter greater than 20 millimeters) or significant severe hail (diameter greater than 50 millimeters). Finally, we aggregated the posterior probabilities of hail, severe hail and significant severe hail over time and space and compared them with the number of reports found in the 2005-2022 Canadian hail database. Our results indicate that the posterior probabilities of hail are not consistent with the observed hail reports, and suggest that there are many gaps in hail reporting in Canada.
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