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渤海风场的概率预测模型研究

Study on probabilistic forecasting model of wind field in the Bohai Sea

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【作者】 陈晓亮沈永明崔雷姜恒志石峰

【Author】 CHEN Xiao-liang;SHEN Yong-ming;CUI Lei;JIANG Heng-zhi;SHI Feng;State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology;Department of Planning and Construction,Jinzhou Port co.,LTD;Key Laboratory for Ecological Environment in Coastal Areas,State Oceanic Administration,National Marine Environmental Monitoring Center;School of Civil Engineering,Tianjin University;

【通讯作者】 崔雷;

【机构】 大连理工大学海岸和近海工程国家重点实验室锦州港股份有限公司规划建设部国家海洋环境监测中心国家海洋局近岸海域生态环境重点实验室天津大学建筑工程学院

【摘要】 风是海上溢油迁移扩散的关键动力因素之一,溢油区风场的精确预报是油膜漂移轨迹预测的基础。本文对渤海的历史风资料进行了相关分析,根据不同区域风的相关性和不同时段风的差异性,分别进行了渤海风的区域划分和时段划分;根据风在每两个指定方向转换的概率和风的平均持续时间,建立了渤海风场的概率预测模型。该预测模型生成的随机风时间序列能体现出历史风场的能量水平、周期性和方向变化,且与相应历史时期风资料的统计参数吻合良好,可为高精度海面溢油预报提供动力基础,也可为其他相关海洋动力学计算提供参考。

【Abstract】 Wind is one of the key dynamic factors for the drift and diffusion of oil spill in ocean.Accurate prediction of the wind field in the oil spill area is the basis of the forecast of oil slick transport. This paper analyzes the historical wind data of the Bohai Sea.According to the correlation of different regional wind and the difference of wind in different periods,the regional division and time division of Bohai wind are respectively carried out.According to the probability with which the wind changed between two specified directions and the mean duration of a wind event,the probability prediction model of wind field in Bohai Sea is established.The statistical parameters of the stochastic wind time series generated by the prediction model that contained a similar energy level,periodicity,and direction variability to the archived wind data are in good agreement with that of the wind data of corresponding historical period.It is a good foundation for increasing the accuracy of oi1 spill predicting and modeling,and is also a reference for other computing in ocean hydrodynamics.

【关键词】 随机风概率预测渤海溢油
【Key words】 stochastic windprobabilityforecastBohai Seaoil spill
【基金】 国家自然科学基金项目(51579030);国家重点基础研究发展计划项目(2013CB430403);国家海洋局海洋灾害预报技术研究重点实验室开放基金课题资助(LOMF1704);中国博士后科学基金面上资助项目(2015M581358)
  • 【文献出处】 海洋环境科学 ,Marine Environmental Science , 编辑部邮箱 ,2019年01期
  • 【分类号】X55
  • 【被引频次】1
  • 【下载频次】217
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