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Weather and climate numerical algorithms: An efficient, parallel solution scheme for the shallow water equations.

机译:天气和气候数值算法:浅水方程组的高效并行解决方案。

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The rapid growth in the complexity of climate and weather simulation problems, combined with a paradigm shift from uniprocessor to parallel computing platforms, make the design of new numerical algorithms for climate and weather simulation essential. In this thesis, a numerical algorithm is developed that maps the global meteorological simulation problem onto massively parallel computer platforms efficiently and accurately through an understanding of the inter-relationships among the physics, the algorithm and the computing platform. The standard and well-accepted two dimensional nonlinear shallow water equation system is used as a model test problem. As part of the sequential algorithm, a conservative semi-implicit, Weak Lagrange-Galerkin (WLG) Finite Element (FE) scheme along with a novel quasi-uniform unstructured spherical triangular grid is designed and implemented. After a systematic evaluation of the true parallel complexity of meteorological simulation problems, an efficient, portable, scalable, parallel algorithm is developed. Sequential and parallel results from several benchmark problems of increasing complexity are presented and compared with published results. The present algorithm handles the pole problem, advection, Rossby waves and inertia-gravity waves accurately and efficiently. It achieves good parallel efficiencies on a range of parallel platforms. For these reasons, the present algorithm is a viable alternative to the currently popular spectral schemes.
机译:气候和天气模拟问题复杂性的快速增长,再加上从单处理器向并行计算平台的转变,使得设计新的气候和天气模拟数值算法至关重要。本文研究了一种数值算法,通过了解物理,算法和计算平台之间的相互关系,将全球气象模拟问题有效,准确地映射到大规模并行计算机平台上。使用标准的和公认的二维非线性浅水方程组作为模型测试问题。作为顺序算法的一部分,设计并实现了一种保守的半隐式,弱Lagrange-Galerkin(WLG)有限元(FE)方案以及一种新颖的拟均匀非结构化球形三角网格。在对气象模拟问题的真正并行复杂性进行系统评估之后,开发了一种高效,可移植,可扩展的并行算法。提出了一些复杂性不断增加的基准问题的顺序和并行结果,并将其与已发布的结果进行了比较。本算法准确有效地处理了极点问题,对流,罗斯比波和惯性重力波。它在各种并行平台上均具有良好的并行效率。由于这些原因,本算法是当前流行的频谱方案的可行替代方案。

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