...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Ocean Dynamics >Validation and application of an ensemble Kalman filter in the Selat Pauh of Singapore
【24h】

Validation and application of an ensemble Kalman filter in the Selat Pauh of Singapore

机译：集成卡尔曼滤波器在新加坡Selat Pauh的验证和应用

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The effectiveness of an ensemble Kalman filter (EnKF) is assessed in the Selat Pauh of Singapore using observing system simulation experiment. Perfect model experiments are first considered. The perfect model experiments examine the EnKF in reducing the initial perturbations with no further errors than those in the initial conditions. Current velocity at 15 observational sites from the true ocean is assimilated every hour into the false ocean. While EnKF reduces the initial velocity error during the first few hours, it fails after one tidal cycle (approximately 12 h) due to the rapid convergence of the ensemble members. Successively, errors are introduced in the surface wind forcing. A random perturbation ε is applied independently to each ensemble member to maintain the ensemble spread. The assimilation results showed that the success of EnKF depends critically on the presence of ε, yet it is not sensitive to the magnitude of ε, at least in the range of weak to moderate perturbations. Although all experiments were made with EnKF only, the results could be applicable in general to all other ensemble-based data assimilation methods.
机译：使用观测系统仿真实验，在新加坡的Selat Pauh中评估了集成卡尔曼滤波器（EnKF）的有效性。首先考虑完美的模型实验。完美的模型实验检查了EnKF在减少初始扰动中的误差，没有比初始条件下的误差更大的误差。每小时从真实海洋吸收15个观测地点处的当前速度到虚假海洋中。尽管EnKF在最初的几个小时内减小了初始速度误差，但由于合奏成员的快速收敛，它在一个潮汐周期（约12小时）后失败了。继而，在表面风强迫中引入了误差。随机扰动ε独立地应用于每个合奏成员，以保持合奏散布。同化结果表明，EnKF的成功关键取决于ε的存在，但至少在弱到中度扰动范围内，它对ε的大小并不敏感。尽管所有实验仅使用EnKF进行，但该结果通常可应用于所有其他基于集合的数据同化方法。

著录项

  • 来源
    《Ocean Dynamics》 |2010年第2期|p.395-401|共7页
  • 作者

    Jun Wei; Paola Malanotte-Rizzoli;

  • 作者单位

    Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;

    Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    ocean modeling; data assimilation; ensemble Kalman filter;

    机译：海洋建模;数据同化集成卡尔曼滤波器;

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