| 摘要: |
| 风松弛导致亚潮尺度的水位低频波动是渤黄海秋冬季常见的海洋动力过程,这一过程的数值模拟要求模型空间范围要覆盖整个渤黄海区域甚至是整个东部陆架海区域。对于以渤海海峡为开边界的渤海模型,则由于风区过小无法再现这一过程。针对这一问题,本文在渤海模型上使用集合卡尔曼滤波(Ensemble Kalman Filter,ENKF)进行同化,成功再现了这一现象,并进一步分析了ENKF同化的作用及其影响因素。主要结论如下：渤海的水位低频波动与输入渤海的开边界水位有关,仅使用潮汐数据和风场数据无法准确地模拟出渤海水位的变化,然而通过ENKF同化则可以再现渤海内的水位低频波动,且同化效果优于两类不同开边界输入的结果。ENKF同化的准确性与集合数目以及观测数据采样位置有关。集合数目越多同化效果越强,但超过40个集合后,同化效果改善不明显。使用的观测数据应尽量均匀分布且要远离开边界。 |
| 关键词: 低频波动 数据同化 集合卡尔曼滤波 渤海 开边界 |
| DOI：10.11693/hyhz20240100010 |
| 分类号: |
| 基金项目:国家自然科学基金项目，U1706215号；山东省自然科学基金资助项目，ZR2019MD010号；泰山学者工程专项经费资助，sqn202211056号 |
附件 |
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| Numerical simulation of low-frequency water-level fluctuation in Bohai Sea based on ensemble Kalman filter |
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LI Xianghao1, XIA Yingying2, SONG Dehai1
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1.Key Laboratory of Physical Oceanography,Ocean University of China;2.National Marine Data and Information Service
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| Abstract: |
| The low-frequency fluctuation of water level at a subtidal scale caused by wind relaxation is a common marine dynamic process in the Bohai Sea and Yellow Sea in autumn and winter. It requires the spatial range of the numerical model cover the entire Bohai Sea and Yellow Sea region and even the East China Sea to reproduce this phenomenon. For the Bohai Sea model taking the Bohai Strait as the open boundary, this process cannot be reproduced due to limited wind fetch. To solve this problem, this paper employed the Ensemble Kalman Filter (ENKF) assimilation method, and successfully reproduced this phenomenon. Furthermore, the role of ENKF assimilation and its influencing factors was analyzed. It was found that the low-frequency fluctuation of water level in the Bohai Sea is driven by the water-levels at the open boundary. Only using tidal data and wind data cannot reproduce the subtidal water level variation in the Bohai Sea. However, the low-frequency fluctuation of water level can be reproduced by the ENKF assimilation; and the assimilation result is better than the results driven sole by the open boundary forcings. The accuracy of ENKF assimilation is related to the number of ensembles and the location of sampling stations. More ensembles will lead to better assimilation results; but over 40 ensembles will not improve the results significantly. The sampling stations selected should be evenly distributed in the Bohai Sea and kept far away from the boundary. |
| Key words: Low frequency fluctuation Data assimilation Ensemble Kalman filtering The Bohai Sea Open boundary |