基于遥感数据与数值模式的浒苔漂移输运预报:以江苏近海为例

林连杰; 董昌明; 嵇宇翔; LIM KAM SIAN Kenny Thiam Choy; 李兆鑫; 蒋星亮; 曹玉晗; 高慧; 王胜强; 曹茜

doi:10.3969/j.issn.1001-909X.2024.01.007

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海洋学研究 ›› 2024, Vol. 42 ›› Issue (1) : 69-82. DOI: 10.3969/j.issn.1001-909X.2024.01.007

研究论文

基于遥感数据与数值模式的浒苔漂移输运预报:以江苏近海为例

林连杰 ¹ ,
董昌明 ¹^,^* ,
嵇宇翔 ² ,
LIM KAM SIAN Kenny Thiam Choy ³ ,
李兆鑫 ⁴ ,
蒋星亮 ⁵ ,
曹玉晗 ⁶ ,
高慧 ¹ ,
王胜强 ¹ ,
曹茜 ¹

作者信息 +

Prediction of UIva prolifera drift and transportation based on remote sensing data and numerical models: A case study in the offshore area of Jiangsu Province

Author information +

文章历史 +

摘要

浒苔暴发是影响全球近岸海域最为严重的海洋灾害之一,引起了社会各方的重视。该研究基于大气-波浪-海洋集合模式,根据卫星遥感数据提取浒苔位置,采用拉格朗日漂流模式对浒苔进行追踪并预报其漂移路径。与卫星观测结果对比表明,该集合模式能够较好地预报浒苔的位置、分布及其漂移路径。此外,该研究还讨论了Stokes漂流对于模式预报的影响,结果表明考虑Stokes漂流可以修正浒苔漂移路径,有效提高预报的准确性。

Abstract

UIva prolifera outbreak is one of the most serious marine disasters affecting the global offshore waters, which has attracted the attention of all sectors of society. According to the location of UIva prolifera extracted from satellite data, the Lagrangian drift model was used to track and predict the drift path of UIva prolifera based on the sea-air-wave set model. Compared with satellite observation, this prediction model can better predict the position, distribution and drift transport of UIva prolifera. In addition, this study also discussed the impact of Stokes Drift on the model prediction. The results show that adding Stokes Drift can correct the drift path of UIva prolifera and effectively improve the accuracy of prediction.

导出引用

林连杰, 董昌明, 嵇宇翔, 等. 基于遥感数据与数值模式的浒苔漂移输运预报:以江苏近海为例[J]. 海洋学研究. 2024, 42(1): 69-82 https://doi.org/10.3969/j.issn.1001-909X.2024.01.007

LIN Lianjie, DONG Changming, JI Yuxiang, et al. Prediction of UIva prolifera drift and transportation based on remote sensing data and numerical models: A case study in the offshore area of Jiangsu Province[J]. Journal of Marine Sciences. 2024, 42(1): 69-82 https://doi.org/10.3969/j.issn.1001-909X.2024.01.007

中图分类号： X55

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