Quantifying dispersal and connectivity of surface waters using observational lagrangian measurements
Document Type
Article
Date of Original Version
8-1-2012
Abstract
Probability distribution functions of displacement are central to Lagrangian statistics and the study of fluid dispersal. A method for computing marginal probability distributions of passive tracer dispersal from Lagrangian observations is developed. Using a pseudotrack approach, probability distributions for the domain of occupation and transit time are developed, complimenting more frequently used bulk statistics for average transit time and overall crossing probability. To demonstrate application of this technique to observations, likelihoods and time scales of dispersal from the Gulf Stream to the Azores are quantified using World Ocean Circulation Experiment (WOCE) Surface Velocity Program (SVP) near-surface drifter data for the years 1992-2008. Over observable time scales, the transit of a particle in the near-surface ocean from the Gulf Stream to the Azores occurs across a spectrum of time scales, from tens to hundreds of days, with an overall likelihood of 42% ±4%and a mean time scale of 321 ±41 days. The exclusion of measurements from drifters released after 1 January 2004 (which have been shown to potentially exhibit bias) slightly increases the overall likelihood of connection (49% ± 6%), consistent with recent surface current shifts in the northern North Atlantic, and increases the mean connection time scale (371 ± 52 days), potentially reflecting spurious acceleration of drifters in recent years. The method presented is general and applicable to a wide range of applications in physical and ecological oceanography. © 2012 American Meteorological Society.
Publication Title, e.g., Journal
Journal of Atmospheric and Oceanic Technology
Volume
29
Issue
8
Citation/Publisher Attribution
Piecuch, Christopher G., and Tatiana A. Rynearson. "Quantifying dispersal and connectivity of surface waters using observational lagrangian measurements." Journal of Atmospheric and Oceanic Technology 29, 8 (2012). doi: 10.1175/JTECH-D-11-00172.1.