Impacts of Sigma Coordinates on the Euler and Navier-Stokes Equations using Continuous Galerkin Methods

Abstract

In this thesis, the impacts of transforming the coordinate system of an existing x-z mesoscale model to x-sigma_z are analyzed and discussed as they were observed in three test cases. The three test cases analyzed are: A rising thermal bubble, a linear hydrostatic mountain, and a linear nonhydrostatic mountain. The methods are outlined for the transformation of two sets (set 1, the non-conservative form using Exner pressure, momentum, and potential temperature; and set 2, the non-conservative form using density, momentum, and potential temperature) of the x-z Navier-Stokes equations to x-sigma_z and their spatial (Continuous Galerkin) and temporal (Runge-Kutta 35) discretization methods are shown in detail. For all three test cases evaluated, the xsigma_ z models performed worse than their x-z counterparts, yielding higher RMS errors, which were observed predominantly in intensity values and not in placement of steady state features. Since the models did converge to a fairly representative steady-state solution the results found by this project are promising, even though they did indicate that x-sigma_z coordinates are not as accurate or efficient as x-z coordinates. With further fine-tuning of the model environment, these issues could be made minimal enough to warrant their utility with semi-implicit methods.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA496857

Entities

People

  • Sean L. Gibbons

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Air Force
  • Applied Mathematics
  • Atmospheric Sciences
  • Computational Fluid Dynamics
  • Computational Science
  • Computer Programs
  • Coordinate Systems
  • Equations
  • Euler Equations
  • Fluid Dynamics
  • Fungi
  • Mathematics
  • Navier Stokes Equations
  • Steady State
  • Stratified Fluids
  • Two Dimensional
  • United States

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Systems Analysis and Design