Publication Date
2024
Document Type
Dissertation/Thesis
First Advisor
Gensini, Vittorio A.
Degree Name
Ph.D. (Doctor of Philosophy)
Legacy Department
Department of Earth, Atmosphere, and Environment
Abstract
Severe convective storms (SCSs) are responsible for billions of dollars of losses in the United States each year through hazards such as large hail, damaging convective wind gusts, and tornadoes. While techniques for forecasting these SCSs have improved over the years, a majority of these improvements focus on short term forecasting and nowcasting techniques. Little work has been done to analyze the recent advances in numerical weather prediction techniques, and to leverage these advances to the prediction of SCSs at the medium range (defined herein as lead-day 4--8). The primary objectives of this dissertation research are to: 1) explore the forecast skill changes provided by stochastic perturbation, a bias capture methodology, in forecasts of a SCS event, 2) explore targeted initialization, an alternative numerical weather prediction (NWP) modelling approach, and 3) compare stochastic perturbation against two dynamical cores not using stochastic perturbation in a medium-range SCS forecast. Results demonstrate that: 1) stochastic perturbation schemes promote a diverse ensemble of solutions of a historical SCS event at the medium range, 2) targeted initialization of model data at lead days four and eight are more skillful than continuous integration, although not significantly so, offering a potential avenue of significant savings in computational resources, and 3) a combination of stochastic perturbation schemes alone is not sufficient to improve forecast skill at the medium range, but the use of stochastic perturbation and additional dynamical model cores should be considered in the deployment of large-scale convection-allowing model (CAM) ensembles for a better overall representation of event outcomes.
Recommended Citation
Fritzen, Robert, "Medium Range Prediction of U.S. Severe Convective Storms" (2024). Graduate Research Theses & Dissertations. 8020.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/8020
Extent
168 pages
Language
en
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
