Adaptive Extraction and Quantification of Geophysical Vortices

• Published in: IEEE transactions on visualization and computer graphics Vol. 17; no. 12; pp. 2088 - 2095
• Main Authors: Williams, S., Petersen, M., Bremer, P.-T, Hecht, M., Pascucci, V., Ahrens, J., Hlawitschka, M., Hamann, B.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: United States IEEE 01.12.2011
• Subjects: Atmospheric modeling; Data mining; Data models; Data visualization; Feature extraction; GENERAL AND MISCELLANEOUS; Information analysis; statistical data analysis; Vortex extraction
• ISSN: 1077-2626; 1941-0506
• DOI: 10.1109/TVCG.2011.162

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.