基于拉格朗日视角的大亚湾及邻近海域表层水体输运特征研究

批准号:
42006177
项目类别:
青年科学基金项目
资助金额:
24.0 万元
负责人:
林丽茹
依托单位:
学科分类:
海洋灾害与防灾减灾
结题年份:
2023
批准年份:
2020
项目状态:
已结题
项目参与者:
林丽茹
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中文摘要
大亚湾是华南地区重要的石化工业基地和核电站所在地。认识大亚湾及周边海域的表层水体输运过程有助于准确预测污染物的迁移路径,对提高海上突发环境事件的应对能力具有重要意义。由于大亚湾水交换动力过程复杂,准确预测海表污染物路径和浓度需要在较广泛的时空尺度上了解相关海洋动力过程。本项目拟利用近同步释放的数百个GPS跟踪的海面漂流浮标的位置数据,获得大亚湾及邻近陆架区的中尺度和亚中尺度流速变化以及相应的能谱结构。根据浮标相对位置的变化,阐明从百米到数十公里的空间尺度上的表层离散特征。同时,开展不同分辨率的模型数值试验,探讨模型分辨率对能谱和离散特征的影响。进而选取与观测结果具有较高一致性的模拟结果,估算流场中的拉格朗日拟序结构,认识该海域关键的海表输运通道和屏障。上述动力学信息将有助于提升大亚湾周边海域污染物输运的预报能力,优化大亚湾环境治理方案和防灾减灾应急预案。
英文摘要
Daya Bay is an important location of the petrochemical industries and the nuclear power stations in the South China. The knowledge of surface water transport around the Daya Bay is essential for accurately predicting the pollutant pathways and improving the response capacity of marine environmental emergencies. Because of the complexity of the water exchange between Daya Bay and the adjacent waters, accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding the relevant ocean dynamics over a wide range of spatiotemporal scales. Using the position data provided by the near-simultaneous deployment of hundreds of GPS-tracked surface drifters, this proposal will estimate the surface velocities and the corresponding energy spectrum structures in Daya Bay and the adjacent continental shelf. The statistics of relative positions between drifter pairs will be used to unravel the surface dispersion rate on the spatial scales from several hundred meters to tens of kilometers. Meanwhile, numerical experiments with varying spatial resolutions will be carried out to explore the influence of model resolutions on the kinetic energy spectrum and the relative dispersion. Then the simulated results with better model performance will be selected to extract the Lagrangian coherent structures in the flow fields, which can well identify the key surface transport pathways and barriers in the study region. The above dynamic information will help to improve the prediction ability of pollutant transport in the surrounding waters of Daya Bay, optimize the environmental governance and the emergency response plans for disaster prevention and mitigation.
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DOI:10.31031/EIMBO.2024.06.000641
发表时间:2024
期刊:Examines in Marine Biology and Oceanography
影响因子:--
作者:Liru Lin;Changjian Liu
通讯作者:Changjian Liu
DOI:10.3390/rs15245652
发表时间:2023-12
期刊:Remote. Sens.
影响因子:--
作者:Yan Lin;Liru Lin;Dongxiao Wang;Xiao-Yi Yang
通讯作者:Yan Lin;Liru Lin;Dongxiao Wang;Xiao-Yi Yang
国内基金
海外基金
