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Fast lagrangian particle tracking in unstructured ocean model grids

机译:非结构化海洋模型网格的快速拉格朗日粒子跟踪

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摘要

Lagrangian particle tracking, based on currents derived from hydrodynamic models, is an important tool in quantifying bio-physical transports in the ocean. Particle tracking in the unstructured grids typically used in coastal regions is computationally slow, limiting the number of particles and ranges of behaviours that can be modeled. Techniques used in a new offline particle tracker "OceanTracker" are shown to be two orders of magnitude faster than those used in an existing ocean particle tracker for unstructured grids when run on a single computer core. More significantly, its computational speed can exceed that achieved when particle tracking on a regular grid. The techniques for unstructured grids make it possible to routinely calculate the trajectories of millions of particles. This large number of particles allows much better estimates of dispersion and transport statistics, particularly when the probability of connection is low but the consequences are significant, e.g. the spread of invasive species. It also enables wider exploration of parameter sensitivity and particles' bio-physical behaviours to provide more robust results. The speed increases result largely from exploiting history and reuse within the spatial interpolation of the hydrodynamic model's output. Using multiple computer cores further increased the speed to track a given number of particles.
机译:拉格朗日粒子跟踪,基于来自流体动力学模型的电流,是量化海洋中生物物理运输的重要工具。在沿海地区通常使用的非结构化网格中的粒子跟踪是计算速度的,限制了可以建模的粒子的数量和行为的范围。新的离线粒子跟踪器“OceanTracker”中使用的技术显示为在单个计算机核心运行时的现有海洋粒子跟踪器中使用的速度快两个数量级。更显着,其计算速度可能超过常规网格上的粒子跟踪时实现的计算速度。非结构化网格的技术使得可以常规计算数百万颗粒的轨迹。这大量粒子允许更好的分散和运输统计估计,特别是当连接概率低但后果很大,例如后果很大。侵入物种的传播。它还可以更广泛地探索参数灵敏度和粒子的生物行为,以提供更强大的结果。速度增加到很大程度上来自利用历史和在流体动力学模型输出的空间插值内重用。使用多台计算机核心进一步提高了跟踪给定数量的粒子的速度。

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