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  • Lagrangian analysis  (1)
  • Optimal smoothing  (1)
  • Particle models  (1)
  • Particle tracking  (1)
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  • 1
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 4 (1990), S. 105-119 
    ISSN: 1436-3259
    Schlagwort(e): Kalman filtering ; Optimal smoothing ; Shallow water equations ; Wind stress ; On-line prediction
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: Abstract Using the state space approach, an on-line filter procedure for combined wind stress identification and tidal flow forecasting is developed. The stochastic dynamic approach is based on the linear twodimensional shallow water equations. Using a finite difference scheme, a system representation of the model is obtained. To account for uncertainties, the system is embedded into a stochastic environment. By employing a Kalman filter, the on-line measurements of the water-level available can be used to identify and predict the shallow water flow. Because it takes a certain time before a fluctuation in the wind stress can be noticed in the water-level measurements, an optimal fixed-lag smoother is used to identify the stress.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Digitale Medien
    Digitale Medien
    Springer
    Stochastic environmental research and risk assessment 7 (1993), S. 109-130 
    ISSN: 1436-3259
    Schlagwort(e): Particle models ; transport equations ; parameter identification ; adjoint modelling ; cost function ; gradient
    Quelle: Springer Online Journal Archives 1860-2000
    Thema: Architektur, Bauingenieurwesen, Vermessung , Energietechnik , Geographie , Geologie und Paläontologie
    Notizen: Abstract For the simulation of the transport of dissolved matter particle models can be used. In this paper a technique is developed for the identification of uncertain parameters in these models. This model calibration is formulated as an optimization problem and is solved with a gradient based algorithm. Here adjoint particle tracks are used for the calculation of the gradient of the cost function. The performance of the calibration method is illustrated by simulations and an application to a river Rhine water quality calamity in November 1986.
    Materialart: Digitale Medien
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
    Publikationsdatum: 2022-05-26
    Beschreibung: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ocean Modelling 121 (2018): 49-75, doi:10.1016/j.ocemod.2017.11.008.
    Beschreibung: Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing.
    Beschreibung: EvS has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No 715386). This research for PJW was supported as part of the Energy Exascale Earth System Model (E3SM) project, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. Funding for HFD was provided by Grant No. DE-SC0012457 from the US Department of Energy. PB acknowledges support for this work from NERC grant NE/R011567/1. SFG is supported by NERC National Capability funding through the Extended Ellett Line Programme.
    Schlagwort(e): Ocean circulation ; Lagrangian analysis ; Connectivity ; Particle tracking ; Future modelling
    Repository-Name: Woods Hole Open Access Server
    Materialart: Article
    Standort Signatur Erwartet Verfügbarkeit
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