Flow Kinematics and Dynamics of the Gulf Stream From Composite Imagery

• Main Author: Mullen, Caitlin Patrice
• Format: Text
• Language: unknown
• Published: ODU Digital Commons 1994
• Subjects: Image analysis; Remote sensing; Flow kinetics; Gulf Stream; Oceanography; Spatial Science; Bower; North Atlantic
• Online Access: https://digitalcommons.odu.edu/oeas_etds/137; https://digitalcommons.odu.edu/cgi/viewcontent.cgi?article=1146&context=oeas_etds

A unique set of contemporaneous satellite-tracked drifters and five-day composite satellite images of the North Atlantic is studied in order to infer the near-surface flow kinematics and dynamics of the Gulf Stream. Using fractal and spectral analyses, two kinematic models, and a potential vorticity model, detailed comparisons are made between these data sets. Fractal and spectral analyses show that the data set is not fractal, there is no geographic variability, and there is not a strong fractal scaling link between the drifter trajectories and composite temperature fronts as had been postulated by several investigators. These results indicate considerably more work needs to be performed before fractal analysis can relate surface flow characteristics with geometric properties of images. Kinematic analysis of the contemporaneous data set is used to infer kinematic properties of the flow field including flow along temperature fronts. This was achieved by using thermal field characteristics obtained from composite images in conjunction with kinematic feature models. Of the two kinematic models used for this phase of the study, it was found that Bower (1991) presents a better feature model than Dutkiewicz et al. (1993). A barotropic potential vorticity model was developed to incorporate some dynamics into the analysis of the meandering Gulf Stream. Results show that there is good correlation between the drifter data, composite images, and the model trajectories. There are two central results that have emerged from this study. The first is that considerable caution should be used in inferring fractal properties of both trajectories and images. This is a potentially powerful analysis tool, but, contrary to the claims of other scientists, there is little, if any scaling link between the flow and surface temperature fields. The other result is that composite imagery and a suitable feature model can be used to infer flow along temperature fronts. This should have major ramifications on the quantitative use of image data.