A typhoon-induced storm surge numerical model with GPU acceleration based on an unstructured spherical centroidal Voronoi tessellation grid

IF 1.4 3区 地球科学 Q3 OCEANOGRAPHY Acta Oceanologica Sinica Pub Date : 2024-03-12 DOI:10.1007/s13131-023-2175-9
Yuanyong Gao, Fujiang Yu, Cifu Fu, Jianxi Dong, Qiuxing Liu
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Abstract

Storm surge is often the marine disaster that poses the greatest threat to life and property in coastal areas. Accurate and timely issuance of storm surge warnings to take appropriate countermeasures is an important means to reduce storm surge-related losses. Storm surge numerical models are important for storm surge forecasting. To further improve the performance of the storm surge forecast models, we developed a numerical storm surge forecast model based on an unstructured spherical centroidal Voronoi tessellation (SCVT) grid. The model is based on shallow water equations in vector-invariant form, and is discretized by Arakawa C grid. The SCVT grid can not only better describe the coastline information but also avoid rigid transitions, and it has a better global consistency by generating high-resolution grids in the key areas through transition refinement. In addition, the simulation speed of the model is accelerated by using the openACC-based GPU acceleration technology to meet the timeliness requirements of operational ensemble forecast. It only takes 37 s to simulate a day in the coastal waters of China. The newly developed storm surge model was applied to simulate typhoon-induced storm surges in the coastal waters of China. The hindcast experiments on the selected representative typhoon-induced storm surge processes indicate that the model can reasonably simulate the distribution characteristics of storm surges. The simulated maximum storm surges and their occurrence times are consistent with the observed data at the representative tide gauge stations, and the mean absolute errors are 3.5 cm and 0.6 h respectively, showing high accuracy and application prospects.

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基于非结构化球心 Voronoi 网格的台风诱发风暴潮数值模型与 GPU 加速
风暴潮通常是对沿海地区的生命和财产构成最大威胁的海洋灾害。准确及时地发布风暴潮警报,以便采取适当的应对措施,是减少风暴潮相关损失的重要手段。风暴潮数值模式对风暴潮预报非常重要。为了进一步提高风暴潮预报模型的性能,我们开发了一种基于非结构化球心 Voronoi tessellation(SCVT)网格的风暴潮数值预报模型。该模型基于矢量不变形式的浅水方程,并采用荒川 C 网格进行离散。SCVT 网格不仅能更好地描述海岸线信息,而且避免了刚性过渡,并通过过渡细化在关键区域生成高分辨率网格,具有更好的全局一致性。此外,利用基于开放式ACC的GPU加速技术,加快了模型的模拟速度,满足了业务集合预报的时效性要求。在中国沿海海域模拟一天仅需 37 秒。新开发的风暴潮模型被用于模拟台风引起的中国近海风暴潮。对选定的有代表性的台风诱发风暴潮过程的后报试验表明,该模式能合理地模拟风暴潮的分布特征。模拟的最大风暴潮及其出现时间与代表性验潮站的观测数据一致,平均绝对误差分别为 3.5 cm 和 0.6 h,具有较高的精度和应用前景。
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来源期刊
Acta Oceanologica Sinica
Acta Oceanologica Sinica 地学-海洋学
CiteScore
2.50
自引率
7.10%
发文量
3884
审稿时长
9 months
期刊介绍: Founded in 1982, Acta Oceanologica Sinica is the official bi-monthly journal of the Chinese Society of Oceanography. It seeks to provide a forum for research papers in the field of oceanography from all over the world. In working to advance scholarly communication it has made the fast publication of high-quality research papers within this field its primary goal. The journal encourages submissions from all branches of oceanography, including marine physics, marine chemistry, marine geology, marine biology, marine hydrology, marine meteorology, ocean engineering, marine remote sensing and marine environment sciences. It publishes original research papers, review articles as well as research notes covering the whole spectrum of oceanography. Special issues emanating from related conferences and meetings are also considered. All papers are subject to peer review and are published online at SpringerLink.
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