Detection of vortices and saddle points in SST data

Q. Yang, B. Parvin, Arthur J Mariano

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

We extend the Horn-Schunck model of flow field computation to incorporate incompressibility for tracking fluid motion. This is expressed as a weak form of zero-divergence constraint in the variational problem and implemented with a multigrid approach for efficient computation. The resulting feature displacement velocity field provides the basis for higher level abstraction and representation of the data for data mining. A robust and efficient algorithm, based on the Jordan curve index, for detecting vortices and saddle points in feature displacement fields derived from sequences of satellite-derived SST fields is presented.

Original languageEnglish (US)
Pages (from-to)331-334
Number of pages4
JournalGeophysical Research Letters
Volume28
Issue number2
DOIs
StatePublished - Jan 15 2001

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saddle points
vortex
sea surface temperature
vortices
incompressibility
data mining
Jordan
flow field
divergence
flow distribution
velocity distribution
fluid
fluids
curves
detection
index

ASJC Scopus subject areas

  • Geophysics
  • Earth and Planetary Sciences(all)

Cite this

Detection of vortices and saddle points in SST data. / Yang, Q.; Parvin, B.; Mariano, Arthur J.

In: Geophysical Research Letters, Vol. 28, No. 2, 15.01.2001, p. 331-334.

Research output: Contribution to journalArticle

Yang, Q. ; Parvin, B. ; Mariano, Arthur J. / Detection of vortices and saddle points in SST data. In: Geophysical Research Letters. 2001 ; Vol. 28, No. 2. pp. 331-334.
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