...
首页> 外文期刊>Journal of Geophysical Research, C. Oceans: JGR >Evaluation of trajectory modeling in different dynamic regions using normalized cumulative Lagrangian separation
【24h】

Evaluation of trajectory modeling in different dynamic regions using normalized cumulative Lagrangian separation

机译:使用归一化累积拉格朗日分离法评估不同动态区域中的轨迹建模

获取原文
获取原文并翻译 | 示例
           

摘要

The Lagrangian separation distance between the endpoints of simulated and observed drifter trajectories is often used to assess the performance of numerical particle trajectory models. However, the separation distance fails to indicate relative model performance in weak and strong current regions, such as a continental shelf and its adjacent deep ocean. A new skill score is proposed based on the cumulative Lagrangian separation distances normalized by the associated cumulative trajectory lengths. This skill score is used to evaluate surface trajectories implied by Global HYCOM hindcast surface currents as gauged against actual satellite‐tracked drifter trajectories in the eastern Gulf of Mexico during the 2010 Deepwater Horizon oil spill. It is found that the new skill score correctly indicates the relative performance of the Global HYCOM in modeling the strong currents of the Gulf of Mexico Loop Current and the Gulf Stream and the weaker currents of the West Florida Shelf. In contrast, the Lagrangian separation distance alone gives a misleading result. The proposed dimensionless skill score is particularly useful when the number of drifter trajectories is limited and neither a conventional Eulerian‐based velocity nor a Lagrangianbased probability density function may be estimated.
机译:模拟和观察到的漂移轨迹的端点之间的拉格朗日分离距离通常用于评估数值颗粒轨迹模型的性能。但是,分隔距离无法指示在弱海和强海当前区域(例如大陆架及其邻近的深海)中的相对模型性能。基于通过关联的累积轨迹长度归一化的累积拉格朗日分离距离,提出了新的技能得分。此技能得分用于评估2010年“深水地平线”漏油事件中,全球HYCOM后播地表电流隐含的地表轨迹,以墨西哥湾东部实际的卫星跟踪漂流轨迹为准。结果发现,新技能得分正确地表明了全球HYCOM在模拟墨西哥湾环流和墨西哥湾流的强流以及西佛罗里达架的弱流中的相对性能。相反,仅拉格朗日分隔距离会产生误导性的结果。当漂移轨迹的数量有限并且既不能估计传统的基于欧拉速度的速度也不可以估计基于拉格朗日的概率密度函数时,建议的无量纲技能得分特别有用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号