2018
DOI: 10.1002/2017jc013363
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Surface Connectivity and Interocean Exchanges From Drifter‐Based Transition Matrices

Abstract: Global surface transport in the ocean can be represented by using the observed trajectories of drifters to calculate probability distribution functions. The oceanographic applications of the Markov Chain approach to modeling include tracking of floating debris and water masses, globally and on yearly‐to‐centennial time scales. Here we analyze the error inherent with mapping trajectories onto a grid and the consequences for ocean transport modeling and detection of accumulation structures. A sensitivity analysi… Show more

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Cited by 38 publications
(58 citation statements)
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“…More specifically, van Sebille et al () compared global particle tracking simulations forced by a hydrodynamic model by Lebreton et al () to drifter transport matrix simulations by Maximenko et al (). On the basin scale the results were similar and the drifter transport matrix method is therefore considered adequate to represent the large spatial and temporal scale transport (McAdam & van Sebille, ).…”
Section: Data Sets and Methodsmentioning
confidence: 78%
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“…More specifically, van Sebille et al () compared global particle tracking simulations forced by a hydrodynamic model by Lebreton et al () to drifter transport matrix simulations by Maximenko et al (). On the basin scale the results were similar and the drifter transport matrix method is therefore considered adequate to represent the large spatial and temporal scale transport (McAdam & van Sebille, ).…”
Section: Data Sets and Methodsmentioning
confidence: 78%
“…Depending on the position of the Argos or Global Positioning System satellites, drifter locations are accurate within 15‐m to 1‐km (Lumpkin & Pazos, ). These errors are negligible for transport between 1° grid cells (see section ) that we are interested in here (McAdam & van Sebille, ). The spatial coverage of the drifters spans most of the global oceans (Figure a).…”
Section: Data Sets and Methodsmentioning
confidence: 99%
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“…We do not model variation of the advection‐diffusion dynamics as a function of initial time. This statistical stationarity assumption, commonly made in turbulence studies (Orszag, ), has been considered in prior transfer operator analyses of drifter data (Maximenko et al, ; McAdam & van Sebillet, ; Miron et al, ). In particular, Miron et al () show that random reductions of the data set do not substantially affect the connectivity results.…”
Section: Transfer Operator Approachmentioning
confidence: 99%