摘要
沿海声层析(Coastal Acoustic Tomography,简称CAT)是利用高频声信号实现近海大范围流场观测的有效手段,但其直接观测范围仍然有限。海洋数值模式提供了一种存在仿真误差的大范围海洋背景场,将CAT观测结果与海洋背景结果同化,可以提高流场结果的分辨率和准确度。本文提出一种利用流函数拟合海洋模式流场结果并使用集合卡尔曼滤波算法同化CAT数据的方法,获得更大范围的海洋水平二维流场结果。同化研究以非结构化网格有限体积海洋数值模式(Finite-Volume Community Ocean Model,简称FVCOM)作为背景场,以2016年6月1日至3日在印度尼西亚巴厘海峡(Bali Strait)进行的4站CAT实验作为观测数据。经过背景场流函数拟合和CAT数据同化,获得巴厘海峡二维流场。同化结果分别与同期观测结果和潮位数据对比,发现流函数拟合同化后的流场能更准确地描述巴厘海峡涨落潮和流量情况,通过引入CAT数据与流场的函数关系,可以有效地降低海洋模式的误差和原观测数据的稀疏性。
Coastal Acoustic Tomography(CAT)is an effective tool to observe the flow field in the large offshore range using high-frequency acoustic signals,of which direct observation range is still limited.The numerical ocean model provides a large-scale ocean background field with simulation errors,and the resolution and accuracy of the flow field results can be improved by assimilating the CAT data with the ocean background results.In this paper,we applied a method to obtain a larger range of two-dimensional ocean flow field results by fitting ocean-mode flow field results using Stream Function and assimilating CAT data using the Ensemble Kalman Filtering algorithm.The assimilation study used the unstructured grid Finite-Volume Community Ocean Model(FVCOM)as the background field,and the four CAT stations experiment conducted in Bali Strait,Indonesia,from 1st to 3rd June 2016 as the observational data.After fitting background field by Stream Function and assimilating CAT data,the two-dimensional flow field in Bali Strait is obtained.The assimilation results were compared with those of the same period of observation and tide level data,which is found that the flow function fitted and assimilated flow field can more accurately describe the high and low tides and flow conditions in the Bali Strait.By introducing the functional relationship between the CAT data and the flow field it can effectively reduce the error of the ocean model and the sparsity of the original observation data.
作者
于丰源
许世杰
谢心怡
高怡心
李光明
Arita Kaneko
Fadli Syamsudin
黄豪彩
Yu Fengyuan;Xu Shijie;Xie Xinyi;Gao Yixin;Li Guangming;Arata Kaneko;Fadli Syamsudin;Huang Haocai(Ocean College,Zhejiang University,Zhoushan 316021,China;National Innovation Institute of Defense Technology,Beijing 100071,China;Graduate School of Engineering,Hiroshima University,Hiroshima 739–8527,Japan;Agency for the Assessment and Application of Technology,Jakarta 10340,Indonesia)
出处
《海洋学报》
CAS
CSCD
北大核心
2024年第8期121-130,共10页
基金
国家自然科学基金(52071293)和国家自然科学基金(41576031)。
关键词
沿海声层析
数据同化
集合卡尔曼滤波
流函数有限体积海洋模式
Coastal Acoustic Tomography
Data assimilation
Ensemble Kalman Filter
Stream Function Finite-Volume Community Ocean Model
