Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Geoscientific Model Development Pub Date : 2023-11-14 DOI:10.5194/gmd-16-6515-2023
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, Øyvind Breivik
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Abstract

Abstract. Lateral changes in the group velocity of waves propagating in oceanic or coastal waters cause a deflection in their propagation path. Such refractive effects can be computed given knowledge of the ambient current field and/or the bathymetry. We present an open-source module for solving the wave ray equations by means of numerical integration in Python v3. The solver is implemented for waves on variable currents and arbitrary depths following the Wentzel–Kramers–Brillouin (WKB) approximation. The ray tracing module is implemented in a class structure, and the output is verified against analytical solutions and tested for numerical convergence. The solver is accompanied by a set of ancillary functions such as retrieval of ambient conditions using OPeNDAP, transformation of geographical coordinates, and structuring of data using community standards. A number of use examples are also provided.
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海浪追踪v.1:任意深度变流海浪射线方程的数值求解器
摘要在海洋或沿海水域中传播的波群速度的横向变化引起其传播路径的偏转。这种折射效应可以在已知环境电流场和/或水深的情况下计算出来。我们在Python v3中提供了一个用数值积分方法求解波浪方程的开源模块。求解器是根据WKB近似对变流和任意深度的波浪进行求解的。光线追踪模块在类结构中实现,输出结果与解析解进行了验证,并进行了数值收敛性测试。求解器还附带了一系列辅助功能,如使用OPeNDAP检索环境条件、转换地理坐标以及使用社区标准构建数据。还提供了一些使用示例。
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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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