Spatiotemporal Variability of Nebraska Hail Events from 1990 - 2019
Advisor Information
Dr. Zachary Suriano
Location
MBSC Ballroom - Poster #406 - G
Presentation Type
Poster
Start Date
4-3-2022 9:00 AM
End Date
4-3-2022 10:15 AM
Abstract
Spatiotemporal Variability of Nebraska Hail Events
From 1990 – 2019
Jessica Edwards
Abstract
As a result of Anthropogenic climate change, there has been a great deal of interest in modeling future environmental responses. One such projected outcome is the likely increase in severe thunderstorm frequency capable of producing hail (Trapp et al., 2007). As any midwestern homeowner will attest, hail can cause extensive damage to homes and vehicles, as well as crops, and farm animals (Changnon et al., 2009). In Nebraska since 1981, hail has resulted in the greatest percentage of total crop loss (21.82%), second only to drought (34.95%) (Rain and Hail 2020). Large hail events are characterized by low predictability, making historical data the preferred method to generate hail insurance premiums (Walters et al., 2017) It is therefore pertinent to maintain an awareness of the patterns of empirically derived hail data as the climate continues to change. The purpose of this project is to organize and analyze hailstorm data to describe spatiotemporal hail characteristics in Nebraska on a smaller spatial scale than in previous studies. This will also serve as a starting point to consider the potential implications of climate change on local hail events.
Scheduling Link
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Spatiotemporal Variability of Nebraska Hail Events from 1990 - 2019
MBSC Ballroom - Poster #406 - G
Spatiotemporal Variability of Nebraska Hail Events
From 1990 – 2019
Jessica Edwards
Abstract
As a result of Anthropogenic climate change, there has been a great deal of interest in modeling future environmental responses. One such projected outcome is the likely increase in severe thunderstorm frequency capable of producing hail (Trapp et al., 2007). As any midwestern homeowner will attest, hail can cause extensive damage to homes and vehicles, as well as crops, and farm animals (Changnon et al., 2009). In Nebraska since 1981, hail has resulted in the greatest percentage of total crop loss (21.82%), second only to drought (34.95%) (Rain and Hail 2020). Large hail events are characterized by low predictability, making historical data the preferred method to generate hail insurance premiums (Walters et al., 2017) It is therefore pertinent to maintain an awareness of the patterns of empirically derived hail data as the climate continues to change. The purpose of this project is to organize and analyze hailstorm data to describe spatiotemporal hail characteristics in Nebraska on a smaller spatial scale than in previous studies. This will also serve as a starting point to consider the potential implications of climate change on local hail events.