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Citation
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HERO ID
2627669
Reference Type
Journal Article
Title
Suspended particulate matter dynamics in a particle framework
Author(s)
Graewe, Ulf; Wolff, JO
Year
2010
Is Peer Reviewed?
0
Journal
Environmental Fluid Mechanics
ISSN:
1573-1510
Volume
10
Issue
1-2
Page Numbers
21-39
DOI
10.1007/s10652-009-9141-8
Web of Science Id
WOS:000274197800003
Abstract
Suspended particulate matter (SPM) dynamics in ocean models are usually treated with an advection-diffusion equation for one or more sediment size classes coupled to the hydrodynamical part of the model. Numerical solution of these additional partial differential equations unavoidably introduces numerical diffusion, i.e. in the case of sharp gradients the possible occurrence of artificial oscillations and non-positivity. A Lagrangian particle-tracking model has been developed to simulate short-term SPM dynamics. Modelling individual sediment particles allows a straightforward physical interpretation of the processes. The tracking of large numbers of individual and independent particles (up to 25 million in total in a single sediment class) can be achieved on high performance computer clusters, due to efficient parallelisation of particle tracking. The movement of the particles is described by a stochastic differential equation, which is consistent with the advection-diffusion equation. Here, the concentration profile is represented by a set of independent moving particles, which are advected according to the 3D velocity field, while the diffusive displacements of the particles are sampled from a random distribution, which is related to the eddy diffusivity field. To account for erosion a new parameterisation is proposed. Three numerical particle tracking schemes (EULER, MILSTEIN and HEUN) are presented and validated in idealised test cases. Finally, the particle tracking algorithms are applied to a realistic scenario, a severe winter storm in the East Frisian Wadden Sea (southern North Sea). The comparison with observations and an Eulerian SPM transport model seems to indicate a somewhat better fidelity of the Lagrangian approach.
Keywords
Lagrangian particles; Random walk; Stochastic processes; SPM transport
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