Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Master of Science

Program

Physics

Supervisor

Hocking, Wayne K.

Abstract

MST (Mesosphere–Stratosphere–Troposphere) radars are powerful instruments for observing the differences in refractive indexes in the air. By tracking refractive index perturbations, these radars can determine wind speeds and turbulence strengths in the atmosphere from the ground up to 15 km altitude. In this project, we used 6 Doppler Radars to study the correlation between horizontal and vertical winds in the Troposphere to find scatterer tilts. However, instrumental effects due to small tilts in the radar beam can also cause such correlations, thus our studies cover that as well. Scatterers are best known for being the result of turbulence and waves in the Troposphere. Hence understanding the nature of scatterers leads to a better understanding of the gravity wave's effects in the Troposphere, as they can generate this turbulence. This thesis found the correlation between horizontal and vertical wind and discovers it changes due to season, month, height, and location. Therefore, it is concluded that this correlation results from the tilt of scatterers, and if there is a tilt in the vertical beam, it is minimal.

Summary for Lay Audience

Many geophysical features like sea-shores, lakes-shores, and mountains can generate gravity waves, which happen when the airflow fluctuates by hitting obstacles and is forced to move upward and downward. These gravity waves can be sources of turbulence in the Troposphere. This project aims to understand geophysical and seasonal effects on gravity waves by studying the scatterers induced by turbulence. For this goal, the correlation between horizontal and vertical wind, by using Doppler Radars, is investigated. Studying this correlation gives us valuable information about the scatterers' tilt. This tilt helps us understand the turbulence that they originate from while providing better information about our radars' accuracy. The ability to model and predict turbulence is one of the essential skills for weather forecasting.

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Creative Commons Attribution-Noncommercial 4.0 License
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