Date of Award

12-10-2022

Document Type

Thesis

Degree Name

Master of Science in Coastal Marine and Wetland Studies

Department

Coastal and Marine Systems Science

College

College of Science

First Advisor

Erin E. Hackett

Second Advisor

Craig Gilman

Third Advisor

Roi Gurka

Abstract

This study utilizes in-situ measurements and numerical weather prediction datasets collected during the Coupled Air-Sea Processes Electromagnetic Ducting Research East field campaign to assess how thermodynamic properties in the marine atmospheric surface layer influence evaporation duct shape and to develop a simple near-surface modified refractivity estimation method. This study utilizes a logarithmic linear parametric model, which describes evaporation ducts via three main parameters: evaporation duct height, evaporation duct curvature, and mixed layer slope. Notably, most studies utilizing this type of model assume the curvature, C0, to be a theoretical value derived assuming neutral atmospheric stability; a thermodynamic regime that is rarely observed precisely. Prior studies suggest varying C0 to represent a wider range of ED shapes. Unfortunately, the physical significance of C0 is poorly understood so this approach is not commonly adopted. This study investigates relationships between C0 and near surface thermodynamic properties. The relationship between C0 and the air-sea temperature difference (ASTD) reveal, during unstable periods, that C0 are generally greater than in near-neutral or stable environments. C0 in near-neutral environments are generally close to the theoretical value. The linear relationship between the near surface specific humidity gradient (NSSHG) and C0 is stronger than that with ASTD thus, it is concluded that C0 variations are primarily driven by NSSHG. Modified refractivity profiles are modeled using C0 based on a NSSHG empirical linear model (termed, EDS model) and compared to other common methods of near surface estimation such as Monin-Obukhov similarity theory (MOST) and extrapolation from ~3m to the surface. Refractivity estimated from the EDS model was similar to in-situ refractivity measurements. Linearly or non-linearly (i.e., polynomials) extrapolating refractivity to the surface resulted in closer agreement between measured and modeled propagation loss, indicating that measured data better predicted PL than either model. Notably, the EDS model predicted PL that is statistically similar to that predicted by MOST implying this novel empirical method is a practical alternative to MOST in applications such as propagation modeling and requires significantly less environmental measurements.

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