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引用本文:何恩业,季轩梁,高姗,赵亮,王玉衡,李云,杨静.黄海浒苔漂移输运和生长消亡过程的数值模拟与预测应用.海洋与湖沼,2021,52(1):39-50.
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黄海浒苔漂移输运和生长消亡过程的数值模拟与预测应用
何恩业1, 季轩梁1, 高姗1, 赵亮2, 王玉衡2, 李云1, 杨静1
1.国家海洋环境预报中心 自然资源部海洋灾害预报技术重点实验室 北京 100081;2.天津科技大学 海洋与环境学院 天津 300457
摘要:
本文在构建黄海浒苔漂移输运模型的基础上耦合了生长消亡过程的生态模块,利用CFSR(Climate Forecast System Reanalysis)再分析数据、国家海洋环境预报中心全球业务化海洋学预报系统(Chinese Global operational Oceanography Forecasting System,CGOFS)黄东海再分析数据和CFS(Climate Forecast System products)预报数据,结合国家卫星海洋应用中心黄海绿潮遥感资料,选取浒苔灾害在时空动态演变过程方面存在明显差异的2016年和2019年,开展了黄海浒苔漂移输运和生长消亡过程的数值模拟,进行敏感实验和年度预测检验。结果表明,该模型可以有效刻画2016年黄海浒苔发展趋势的显著特征,对浒苔的漂移路径、影响范围和相对生物量变化特征的数值模拟结果与监测实况较为吻合。在2019年的年度预测应用上,针对浒苔漂移输运路径的方向、影响海域的时间、生物量较往年的变化等方面,模拟效果也都比较理想,体现出该模型在实际业务化预报应用中的可靠性和有效性。
关键词:  浒苔  生态动力学  浒苔预报  数值模拟  黄海
DOI:10.11693/hyhz20200300090
分类号:X55
基金项目:国家重点研发计划海洋环境安全保障专项,2016YFC1401605号,2016YFC1401800号。
附件
NUMERICAL SIMULATION AND FORECASTING OF DRIFT, GROWTH, AND DEATH OF ENTEROMORPHA IN THE YELLOW SEA
HE En-Ye1, JI Xuan-Liang1, GAO Shan1, ZHAO Liang2, WANG Yu-Heng2, LI Yun1, YANG Jing1
1.National Marine Environmental Forecasting Center, Key Laboratory of Research on Marine Hazards Forecasting, Ministry of Natural Resources of the People's Republic of China, Beijing 100081, China;2.College of Marine and Environmental Sciences, Tianjin University of Science and Technology, Tianjin 300457, China
Abstract:
A model of Enteromorpha drifting in the Yellow Sea (YS) was proposed, which is coupled with the life cycle of Enteromorpha. Using the Climate Forecast System Reanalysis (CFSR) reanalysis data, the Chinese Global operational Oceanography Forecasting System (CGOFS) reanalysis data, and the Climate Forecast System (CFS) data, combined with green tide remote sensing data of the National Satellite Ocean Application Service (NSOAS), the drifting path and relative biomass of Enteromorpha in the YS in 2016 and 2019 were simulated. The modeled drifting path, coverage area, and relative biomass of Enteromorpha in the YS were consistent with the monitoring results in 2016, indicating that the model was able to depict the significant features of the Enteromorpha development trend. The model was applied to predict the trend of Enteromorpha in 2019 using CFS forecast data. The forecast results indicate the Enteromorpha in 2019 would last longer with wider coverage, and drift more northerner by easterly than those of other years. The results in 2019 show a reasonable agreement with the satellite observed results, which means the model has good applicability for real case forecast Enteromorpha bloom in the YS.
Key words:  Enteromorpha  ecosystem dynamics  Enteromorpha forecast  numerical simulation  Yellow Sea
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