• DocumentCode
    1365451
  • Title

    Adaptive Extraction and Quantification of Geophysical Vortices

  • Author

    Williams, S. ; Petersen, M. ; Bremer, P.-T. ; Hecht, M. ; Pascucci, V. ; Ahrens, J. ; Hlawitschka, M. ; Hamann, B.

  • Author_Institution
    Inst. for Data Anal. & Visualization, Univ. of California, Davis, CA, USA
  • Volume
    17
  • Issue
    12
  • fYear
    2011
  • Firstpage
    2088
  • Lastpage
    2095
  • Abstract
    We consider the problem of extracting discrete two-dimensional vortices from a turbulent flow. In our approach we use a reference model describing the expected physics and geometry of an idealized vortex. The model allows us to derive a novel correlation between the size of the vortex and its strength, measured as the square of its strain minus the square of its vorticity. For vortex detection in real models we use the strength parameter to locate potential vortex cores, then measure the similarity of our ideal analytical vortex and the real vortex core for different strength thresholds. This approach provides a metric for how well a vortex core is modeled by an ideal vortex. Moreover, this provides insight into the problem of choosing the thresholds that identify a vortex. By selecting a target coefficient of determination (i.e., statistical confidence), we determine on a per-vortex basis what threshold of the strength parameter would be required to extract that vortex at the chosen confidence. We validate our approach on real data from a global ocean simulation and derive from it a map of expected vortex strengths over the global ocean.
  • Keywords
    digital simulation; geometry; geophysics computing; oceanography; turbulence; vortices; discrete two dimensional vortex extraction; geometry; geophysical vortices quantification; global ocean simulation; physics; reference model; turbulent flow; vortex strengths; Atmospheric modeling; Data mining; Data models; Data visualization; Feature extraction; Information analysis; Vortex extraction; feature extraction; statistical data analysis.;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/TVCG.2011.162
  • Filename
    6064973