Bayesian estimation of the likelihood of extreme hail sizes over the United States
Abstract Large hail causes significant economic losses in the United States each year. Despite these impacts, hail is not typically included in building and infrastructure design standards, and assessments of hazards from extreme hail size remain limited. Here, we use a novel approach and multiple h...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-12-01
|
| Series: | npj Natural Hazards |
| Online Access: | https://doi.org/10.1038/s44304-024-00052-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841559783800307712 |
|---|---|
| author | Subhadarsini Das John T. Allen |
| author_facet | Subhadarsini Das John T. Allen |
| author_sort | Subhadarsini Das |
| collection | DOAJ |
| description | Abstract Large hail causes significant economic losses in the United States each year. Despite these impacts, hail is not typically included in building and infrastructure design standards, and assessments of hazards from extreme hail size remain limited. Here, we use a novel approach and multiple hail size datasets to develop a new Generalized Extreme Value model through a Bayesian framework to identify large hail-prone regions across the country at 0.25° × 0.25°. This model is smoothed using Gaussian process regression for nationwide estimation of return likelihood. To contextualize local risk, hazard returns intersecting high-population exposure centers are compared. Fitted extreme value models suggest earlier work likely underestimates the hail hazard. Especially for higher return periods, the Bayesian approach is found to better model very rare hail occurrences than traditional approaches. This provides a framework for appreciating underlying risk from hail and motivates mitigative approaches through improving design standards. |
| format | Article |
| id | doaj-art-0ace3ad229b04190a8708c9596f436fd |
| institution | Kabale University |
| issn | 2948-2100 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Natural Hazards |
| spelling | doaj-art-0ace3ad229b04190a8708c9596f436fd2025-01-05T12:09:06ZengNature Portfolionpj Natural Hazards2948-21002024-12-011111510.1038/s44304-024-00052-5Bayesian estimation of the likelihood of extreme hail sizes over the United StatesSubhadarsini Das0John T. Allen1Department of Earth and Atmospheric Sciences, Central Michigan UniversityDepartment of Earth and Atmospheric Sciences, Central Michigan UniversityAbstract Large hail causes significant economic losses in the United States each year. Despite these impacts, hail is not typically included in building and infrastructure design standards, and assessments of hazards from extreme hail size remain limited. Here, we use a novel approach and multiple hail size datasets to develop a new Generalized Extreme Value model through a Bayesian framework to identify large hail-prone regions across the country at 0.25° × 0.25°. This model is smoothed using Gaussian process regression for nationwide estimation of return likelihood. To contextualize local risk, hazard returns intersecting high-population exposure centers are compared. Fitted extreme value models suggest earlier work likely underestimates the hail hazard. Especially for higher return periods, the Bayesian approach is found to better model very rare hail occurrences than traditional approaches. This provides a framework for appreciating underlying risk from hail and motivates mitigative approaches through improving design standards.https://doi.org/10.1038/s44304-024-00052-5 |
| spellingShingle | Subhadarsini Das John T. Allen Bayesian estimation of the likelihood of extreme hail sizes over the United States npj Natural Hazards |
| title | Bayesian estimation of the likelihood of extreme hail sizes over the United States |
| title_full | Bayesian estimation of the likelihood of extreme hail sizes over the United States |
| title_fullStr | Bayesian estimation of the likelihood of extreme hail sizes over the United States |
| title_full_unstemmed | Bayesian estimation of the likelihood of extreme hail sizes over the United States |
| title_short | Bayesian estimation of the likelihood of extreme hail sizes over the United States |
| title_sort | bayesian estimation of the likelihood of extreme hail sizes over the united states |
| url | https://doi.org/10.1038/s44304-024-00052-5 |
| work_keys_str_mv | AT subhadarsinidas bayesianestimationofthelikelihoodofextremehailsizesovertheunitedstates AT johntallen bayesianestimationofthelikelihoodofextremehailsizesovertheunitedstates |