Using statistical learning approaches to understand trends and variability of tornadoes across the continental United States

• Main Author: Nouri, Niloufar
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: CUNY Academic Works 2020
• Subjects: Statistical Learning; Hierarchical Bayesian Models; Tornado Data; ENSO; Machine Learning; Trend Analysis; Tornado Clusters; Spatio-temporal Analysis; Civil Engineering; Other Civil and Environmental Engineering; Arctic; Pacific; Soi; North Atlantic; North Atlantic oscillation
• Online Access: https://academicworks.cuny.edu/cc_etds_theses/940; https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1947&context=cc_etds_theses

The annual frequency of tornadoes during 1950-2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detect...