Estimating the travel time and the most likely path from Lagrangian drifters
| Autor: | Michael O'Malley, Romuald Laso-Jadart, Mohammed-Amin Madoui, Adam M. Sykulski |
|---|---|
| Přispěvatelé: | Engineering and Physical Sciences Research Council |
| Rok vydání: | 2020 |
| Předmět: |
Surface (mathematics)
FOS: Computer and information sciences Technology Atmospheric Science 010504 meteorology & atmospheric sciences Computer science DIVERSITY 01 natural sciences GLOBAL OCEAN physics.data-an Engineering Meteorology & Atmospheric Sciences 0405 Oceanography Statistical techniques Physics::Atmospheric and Oceanic Physics Computation (stat.CO) Contrast (statistics) Physics - Fluid Dynamics Geodesy Travel time Physics - Atmospheric and Oceanic Physics Physical Sciences symbols Ocean Optimization ATLANTIC Lagrangian circulation Transport FOS: Physical sciences physics.ao-ph Ocean Engineering Statistics - Applications Statistics - Computation symbols.namesake Applications (stat.AP) Engineering Ocean stat.AP 0105 earth and related environmental sciences stat.CO Science & Technology 010505 oceanography Fluid Dynamics (physics.flu-dyn) Probability and statistics Euclidean distance Drifter physics.flu-dyn 0911 Maritime Engineering Physics - Data Analysis Statistics and Probability Path (graph theory) Atmospheric and Oceanic Physics (physics.ao-ph) SCALES 0401 Atmospheric Sciences Lagrangian Data Analysis Statistics and Probability (physics.data-an) |
| DOI: | 10.48550/arxiv.2002.07774 |
| Popis: | We provide a novel methodology 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 modelling the transport of ocean-borne 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 methodology 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. Comment: 27 pages, 10 figures in the main text. 13 pages, 8 figures in the supplemental material |
| Databáze: | OpenAIRE |
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