Estimating the travel time and the most likely path from lagrangian drifters
Author(s)
O'Malley, Michael
Sykulski, Adam M
Laso-Jadart, Romuald
Madoui, Mohammed-Amin
Type
Journal Article
Abstract
We provide a novel method for computing the most likely path taken by drifters between arbitrary fixed locations in the ocean. We also provide an estimate of the travel time associated with this path. Lagrangian pathways and travel times are of practical value not just in understanding surface velocities, but also in modeling the transport of oceanborne species such as planktonic organisms and floating debris such as plastics. In particular, the estimated travel time can be used to compute an estimated Lagrangian distance, which is often more informative than Euclidean distance in understanding connectivity between locations. Our method is purely data driven and requires no simulations of drifter trajectories, in contrast to existing approaches. Our method scales globally and can simultaneously handle multiple locations in the ocean. Furthermore, we provide estimates of the error and uncertainty associated with both the most likely path and the associated travel time.
Date Issued
2021-05-01
Date Acceptance
2021-03-15
Citation
Journal of Atmospheric and Oceanic Technology, 2021, 38 (5), pp.1059-1073
ISSN
0739-0572
Publisher
American Meteorological Society
Start Page
1059
End Page
1073
Journal / Book Title
Journal of Atmospheric and Oceanic Technology
Volume
38
Issue
5
Copyright Statement
This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).
© 2021 American Meteorological Society.
© 2021 American Meteorological Society.
License URL
Sponsor
Engineering and Physical Sciences Research Council
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000660815200010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
EP/R01860X/1
Subjects
Science & Technology
Technology
Physical Sciences
Engineering, Ocean
Meteorology & Atmospheric Sciences
Engineering
Ocean
Lagrangian circulation
transport
Transport
Optimization
Statistical techniques
GLOBAL OCEAN
DIVERSITY
ATLANTIC
SCALES
Publication Status
Published