Current Research Projects
Project: PREEVENTS Track 2: Collaborative Research: Improving High-Impact Hail Event Forecasts by Linking Hail Environments and Modeled Hailstorm Processes
Funded Period: August 2019 - July 2022
Project Details
The United States suffers billions of dollars in insured losses each year from damaging hail storms and the societal and economic costs of such storms have been increasing. Unfortunately, none of these events or their associated impacts were anticipated ahead of time. This project aims to identify what type of environments produce such high impact hail events, and how the physical processes that produce hail are affected by environmental processes. The improved understanding of hail growth will be incorporated into a hail forecasting system within national weather prediction models to improve hail forecasts. To advance predictability and reduce the increasingly significant impact of hail on society, the CMU component of this project will focus on identification of environmental controls on hail production for different hail threat classes (e.g., giant hail or >10 cm or 4 in, large amounts of small hail) and identify regime, seasonal and regional differences. These environmental controls will be used to the establish the physical relationship between hail threat class occurrence and environmental conditions via idealized modeling. This work is part of a broader collaboration involving the National Severe Storms Laboratory, Penn State University and Atmospheric Environment Research.
Group Members Involved
Dr. John T. Allen, Principal Investigator
Cameron Nixon, Graduate Research Assistant
Elizabeth Wawrzyniak, Former Undergraduate Research Assistant
Dennis Weaver, Former Undergraduate Research Assistant
Ethan O'Neill, Undergraduate Research Assistant
Project Deliverables & Outcomes
Initial deliverables for this project have focused on identifying the state of knowledge and testing of existing methods, while pushing to uncover the environmental connections. As part of this work, PI Allen lead a review of hail science published in Reviews of Geophysics (Allen et al. 2020a) and highlighted in EOS (Allen et al. 2020b). Results from this work have also been presented at the 10th European Conference on Severe Storms, 100th and 101st American Meteorology Society annual meetings showcasing the relationship between hail size and associated environment and the lack of predictability that can be inferred from existing parameters. Using the ERA5 reanalysis we explored existing parameters for hail prediction over both the United States and Europe in, finding many parameters to perform unexpected poorly. (Taszarek et al. 2020, Journal of Climate). To facilitate new and innovative methods we explored the relationship between hail and its associated environmental hodograph and compared this to the hodographs found for tornadoes (Nixon and Allen 2022. These results illustrated for the sample considered that while there isnt a hodograph only approach to characterize increasingly large hail size above severe thresholds, there is clear predictabilty between tornadic and hail cases. The hodographs in this work provide a forecasting and modeling reference framework for hail cases. New analysis of an extended environment dataset that includes all hail sizes from 0.10 inches to 8 inches with independent cases has shown promising signs of predictability.
Publications
Nixon*, C., Allen, J. T., Taszarek, M. 2023: Hodographs and Skew-Ts of Hail-Producing Storms. Conditionally Accepted, Weather and Forecasting. doi:
Nixon*, C. J., Allen, J. T., 2022: Distinguishing between Hodographs of Severe Hail and Tornadoes. In press, Weather and Forecasting. doi: 10.1175/WAF-D-21-0136.1 PDF
Allen, J. T., Q. Zhang, I. Giammanco, M. Kumjian, P. Groenemeijer, K. Ortega, M. Kunz, H. Punge 2020: Understanding Hail in the Earth System. Reviews of Geophysics, 57, doi: 10.1029/2019RG000665.PDF
Allen, J. T., I. M. Giammanco, M. R. Kumjian, H. J. Punge, M. Kunz, Q. Zhang, and P. Groenemeijer, 2020: Ice from above: Toward a better understanding of hailstorms, EOS, 101, Published 11th September 2020. doi:10.1029/2020EO148818.PDF
Taszarek, M., Allen, J. T., Pucik, T., Hoogewind, K., and H. E. Brooks, 2020: Severe Convective Storms Across Europe and the United States. Part 2: Environments accompanying lightning, large hail, severe wind and tornadoes. Journal of Climate, 33, 10263-10286. doi: 10.1175/JCLI-D-20-0346.1 PDF
Presentations
Allen, J. T., Nixon*, C., Kumjian, M., and M. Taszarek, 2023: Will hail be severe? Elusive Environmental Predictors generating large hail. 11th European Conference of Severe Storms, Bucharest, Romania.
Kumjian, D., Lombardo, K., Nixon*, C., and J. T. Allen, 2023: Does low-level vertical wind shear matter for hail production? 11th European Conference of Severe Storms, Bucharest, Romania. Audience Choice Best Oral Contribution.
Nixon*, C. J., and J. T. Allen, 2023: Hodographs and Skew-Ts of Hail Producing Supercells Using Self-Organizing Maps. 22nd Conference on Artificial Intelligence for Environmental Science, 103rd Annual Meeting of the American Meteorological Society, Denver, Colorado. AMS Student Presentation Award Winner (3rd Place)
Allen J. T., C. Nixon*, M. Kumjian, 2022: Searching for Predictability in the Environmental Conditions Preceding Large Hail. 2nd North American Hail Workshop, Boulder, Colorado.
Nixon, C. J.*, and J. T. Allen, 2022: Hodographs and Skew-Ts of Hail Producing Supercells Using Self-Organizing Maps. 2nd North American Hail Workshop, Boulder, Colorado.
Allen, J. T., C. Nixon*, M. Kumjian, R. Jewell, B. Smith, R. Thompson 2022: Predictors and Process Insights for the Generation of Large Hail. 31st Conference on Weather Analysis and Forecasting (WAF)/27th Conference on Numerical Weather Prediction (NWP), 102nd Annual Meeting of the American Meteorological Society, Virtual.
Nixon, C. J.*, and J. T. Allen, 2022: Hodographs and Skew Ts of Hail-Producing Supercells Using Self-Organizing Maps. 31st Conference on Weather Analysis and Forecasting (WAF)/27th Conference on Numerical Weather Prediction (NWP), 102nd Annual Meeting of the American Meteorological Society, Virtual.
Weaver#, D., and J. T. Allen, 2022: Understanding the Connection between Hail Size and Physical Damage Using Storm Report and CoCoRaHS Data.10th Symposium on Building a Weather-Ready Nation: Enhancing Out Nations Readiness, Responsiveness, and Resilience to High Impact Weather Events, 102nd Annual Meeting of the American Meteorological Society, Virtual.
Allen, J. T., C. Nixon, M. Kumjian, R. Jewell, B. Smith, R. Thompson 2021: Forecast parameters for hail occurrence and size. 3rd European Hail Workshop, Virtual.
Nixon, C. J.*, Allen, J. T., 2021: Hodographs for hailstorms in the United States. 3rd European Hail Workshop, Virtual.
Nixon, C. J.*, Allen J. T., 2021: Distinguishing between Hodographs of Severe Hail and Tornadoes. 11th Conference on Transition of Research to Operations, 101st Annual Meeting of the American Meteorological Society, Virtual.
Allen, J. T., M. R. Kumjian, C. J. Nixon*, R. E. D. Jewell, B. T. Smith, and R. L. Thompson, 2020: Forecast Parameters for U.S. Hail Occurrence and Size. 30th Conference on Weather Analysis and Forecasting (WAF)/26th Conference on Numerical Weather Prediction (NWP), AMS 100th Annual Meeting, Boston, MA.
Allen, J. T., M. R. Kumjian, R. E. D. Jewell, B. T. Smith, and R. L. Thompson, 2019: Forecast Parameters for U.S. Hail Occurrence and Size. 10th European Conference on Severe Storms, Kraków, Poland.
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