Lynnlee Rosolino1, Marwa Majdi1, Daniel Brothers2, Darin Langerud2
1 Department of Atmospheric Science, University of North Dakota
2 Atmospheric Resource Board, North Dakota Department of Water Resources
Hailstorms are one of the most frequent severe weather phenomena that can affect many regions of the world. Much of the mid-latitudes experience at least one hailstorm each year, and there are hail hot spots over several tropical landmasses. Hail damage often results in significant economic losses, especially when large hailstones fall, or in long duration hail events. Crops, vehicles, and homes are all affected by hailstorms. Global data records of hail losses are incomplete, but in the United States alone, losses from convective storms, mostly due to hail, total over $10 billion USD each year.
To help combat the significant damage that results from large hail, summertime cloud seeding projects such as the North Dakota Cloud Modification Project (NDCMP) have been established, with a goal of suppressing hail. Western North Dakota has a particularly high hail frequency compared to the Upper Great Plains/Midwest region. Convective initiation is more likely to occur in Western North Dakota during summer months, when there is a localized maximum in cold fronts and midlatitude cyclones. These two patterns frequently initiate quick-moving, powerful storms that are capable of producing significant hail. Geography also plays a role in the distribution of hail in North Dakota. Western North Dakota has a relatively lower freezing level, meaning hail has less time in above freezing temperatures to melt on descent, thus reaching the ground as a larger stone. Additionally, the semi-arid climate makes Western North Dakota more susceptible to damaging hail, as increased evaporative cooling within the sub-cloud layer makes it less likely that a hailstone will completely melt while falling.
Evaluating the effectiveness of hail suppression operations is important, however it can be challenging since there are not many reliable networks for observed hail nor accurate methods of hail measurements. This study will attempt to address the issues with ground-based hail observations by using a radar-based hail size retrieval algorithm (HRA) to determine observed hail size rather than ground-based hail observations. HRA output will be compared with forecasted hail size to determine the effectiveness of seeding operations in reducing hail size for each case day.
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