Date of Award
Master of Science
Department of Engineering Physics
Peter Saunders, PhD
This work explores the question as to whether lightning data can be generated synthetically using vector autoregressive-moving-average (VARMA) models. Geostationary Lightning Mapper (GLM) data is used as the basis for the study. Lightning climatology is examined and compared to previous research to gain insight into the targeted areas. Individual lightning ashes are analyzed to inspect how well the process works on a smaller scale. Then, entire regions are evaluated to simulate lightning creation in a larger setting. Results suggest that the VARMA process employed is sufficient in generating synthetic lightning observations, largely dependent on the time and location of lightning events.
DTIC Accession Number
Powers, Seth R., "Synthetic Lightning Generation Employing Autoregressive-Moving-Average (ARMA) Models" (2021). Theses and Dissertations. 5016.