Date of Award
2026
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Atmospheric and Earth Science
Committee Chair
Udaysankar Nair
Committee Member
Michael Newchurch
Committee Member
Sundar Christopher
Research Advisor
Udaysankar Nair
Subject(s)
Numerical weather forecasting, Atmospheric turbulence, Meteorological optics
Abstract
Optical turbulence plays a critical role in electromagnetic wave propagation through the atmosphere, directly affecting imaging systems, wireless communications, and high-energy laser (HEL) performance. Realistic three-dimensional characterization of atmospheric turbulence is essential for understanding these impacts, particularly within the atmospheric surface layer, where turbulence is often strongest. The refractive index structure parameter, Cn2, is used to quantify optical turbulence. This thesis evaluates the capability of the High Resolution Rapid Refresh (HRRR) model to characterize surface layer Cn2. As the highest resolution and most frequently updated numerical weather prediction model covering the continental US, HRRR offers strong potential for operational HEL testing and engineering applications requiring reliable climatological turbulence data. A long-term observational climatology of surface layer Cn2 is developed using measurements from the Persistent Data Collection Site in Hazel Green, Alabama. Existing estimation methods are implemented with HRRR variables and evaluated against observations to determine relative performance and operational reliability.
Recommended Citation
Minor, Richard, "Optical turbulence estimation from numerical weather prediction models: methods and error analysis" (2026). Theses. 829.
https://louis.uah.edu/uah-theses/829