Rough Ocean Surface Effects on Evaporative Duct Atmospheric Refractivity Inversions Using Genetic Algorithms

Abstract

Radar performance is impacted by variations in atmospheric refractivity because it changes the direction of electromagnetic wave propagation. Because direct measurement and simulation of atmospheric refractivity at high resolution over large distances is challenging, inversion techniques have developed to address this knowledge gap in predicting refractivity. Here we use synthetic radar data to solve refractivity inversion problems, focusing on evaporation ducts. Unlike most prior “refractivity from clutter” studies, this study examines inversions based on point‐to‐point propagation rather than sea clutter. This approach removes complexities associated with uncertainties in surface reflection coefficients; however, the sea surface still plays a role in the forward scattering and reflection (multipath) of electromagnetic waves. Using synthetic data that permit quantitative evaluation of inverse solution accuracy and detailed knowledge regarding the sea state conditions used to produce the data, we evaluate the impact various representations of the sea surface have on the accuracy of refractivity inversions. These representations include neglect of the sea surface, use of the same phase‐resolved surface, and use of a statistically equivalent sea surface. Results show that neglect of the sea surface and use of a statistically equivalent sea surface significantly decreases the accuracy of inverse solutions, and this decrease primarily results from discrepancies in the multipath pattern that generate larger variations in the propagation than does the refractivity. We show that averaging propagation over several different phases of the sea surface aids in washing out the multipath pattern to increase sensitivity of the inversion to the features of the refractivity profile.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 01, 2018
Source ID
10.1029/2017rs006440

Entities

People

  • Erin E Hackett
  • Stephen Penton

Organizations

  • Coastal Carolina University
  • Office of Naval Research

Tags

Fields of Study

  • Environmental science
  • Physics

Readers

  • Computational Modeling and Simulation
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Biotechnology