Particles in the Coastal Ocean Theory and Applications

Lynch, Daniel R.; Greenberg, David A.; Bilgili, Ata; McGillicuddy, Dennis J.; Manning, James P.; Aretxabaleta, Alfredo L.

doi:10.1017/cbo9781107449336

Cited by 36 publications

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“…Computing power, observation data, and our understanding of ocean dynamics have vastly increased over the past few decades, and ocean circulation models can now produce accurate, high resolution predictions of circulation patterns (Lynch et al, 2015). The output from these circulation models may then be used to force Lagrangian particletracking models, which numerically integrate the trajectories of many small particles as they move through the circulation fields.…”

Section: Chapter 1 Introductionmentioning

confidence: 99%

“…Higher trophic levels, including many invertebrates and fish, are transported as planktonic larvae . Oil and other chemical pollutants often assemble into droplets that are transported as small particles (Lynch et al, 2015). Understanding the movement of these particles is critical to understanding marine ecosystems.…”

Section: Introductionmentioning

confidence: 99%

“…Accurately describing the movement of plankton, pollutants, and other materials in the ocean is an important component of effectively managing marine resources and responding to disasters (Lynch et al, 2015). However, in many cases, the nature of the material being transported or the desired management objective inhibits using field observations alone to describe transport patterns.…”

Section: Introductionmentioning

confidence: 99%

“…Bleck et al, 2002;Shchepetkin and McWilliams, 2005;Chen et al, 2006). However, many materials that are transported through the ocean are impacted by their local environment, and Lagrangian descriptions of their movements may be better able to capture important local scale processes (Grimm and Railsback, 2005;Lynch et al, 2015). Particle-tracking models that track the position of Lagrangian particles as they move through an Eulerian circulation field are an effective way to explore transport processes in the ocean (Lynch et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…However, many materials that are transported through the ocean are impacted by their local environment, and Lagrangian descriptions of their movements may be better able to capture important local scale processes (Grimm and Railsback, 2005;Lynch et al, 2015). Particle-tracking models that track the position of Lagrangian particles as they move through an Eulerian circulation field are an effective way to explore transport processes in the ocean (Lynch et al, 2015). Individual-based models (IBMs) extend particle-tracking models to simulate not only the location of each individual in time and space, but also biological traits such as age and swimming behaviors (Grimm and Railsback, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Trait-based modeling of larval dispersal in the Gulf of Maine

Jones¹

2017

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Section: Chapter 1 Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Trait-based modeling of larval dispersal in the Gulf of Maine

Jones¹

2017

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Arbitrarily complex chemical reactions on particles

Benson

Bolster

2016

Water Resources Research

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Previous particle‐tracking (PT) algorithms for chemical reaction conceptualize each particle being composed of one species. Reactions occur by either complete or partial birth/death processes between interacting particles. Here we extend the method by placing any number of chemical species on each particle. The particle/particle interaction is limited to mass exchange. After exchange, reactions of any sort are carried out independently on each particle. The novel components of the algorithms are verified against analytic solutions where possible.

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Model-aided Lagrangian interpretation of non-synoptic estuarine observations

Shcherbina

McNeil

Baptista

2016

Limnol. Oceanogr. Methods

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We propose a novel method for constructing a pseudo-synoptic view of estuarine features from nonsynoptic observations captured by mobile platforms. The model-aided Lagrangian interpretation (MALI) method is based on relocating observations to a common reference moment in time along three-dimensional Lagrangian trajectories derived from a numerical model of estuarine circulation. The method relies on the model skill to capture large-scale circulation features, and on high-resolution in situ observations to characterize small-scale hydrographic structure. We demonstrate our technique by applying MALI to autonomous underwater vehicle observations in the Columbia River estuary, with the aid of a validated unstructured-grid finite-element numerical simulation. The method can be readily adapted to a broader range of environments, observational platforms, and model-data combinations.Hydrographic transects conducted with mobile platforms are invaluable to understanding the distribution and exchange of salt, sediments, nutrients, biota, and pollutants in estuaries. In the environments characterized by strong tidal and riverine flows, such as the Columbia River, transect surveys are rarely synoptic: As the speeds of the surveying platform and the natural flow are typically of the same order of magnitude, scalar and circulation features typically change drastically during the time window of the transect.The conventional presentation of results of estuarine surveys in the form of transects along geographic coordinates gives a false impression of synoptic "snapshots" of the tracer fields ( Fig. 1a-c). Even though the non-synopticity of the transects is typically acknowledged, the implied distorting effects of the concurrent advection is visually difficult to ascertain. As a result, distortions can be easily overlooked or dismissed, potentially leading to misinterpretation of the observed features or miscalculation of their spatial relationships, extent, and propagation speed.To alleviate the distorting effects of estuarine advection during surveys, we propose relocation of the observations along the model-derived three-dimensional (3D) Lagrangian particle trajectories to a common reference time, thus obtaining a synthetic pseudo-synoptic view (Fig. 1d,e).

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Particles in the Coastal Ocean Theory and Applications

Cited by 36 publications

References 0 publications

Trait-based modeling of larval dispersal in the Gulf of Maine

Trait-based modeling of larval dispersal in the Gulf of Maine

Arbitrarily complex chemical reactions on particles

Model-aided Lagrangian interpretation of non-synoptic estuarine observations

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