基于动态模态分解的长江口海表温度时空分布特征重构研究  

Reconstruction of temporal and spatial distribution characteristics of sea surface temperature in the Yangtze River Estuary based on dynamic mode decomposition method

作　　者：陈嘉星 江迪 张霄宇[1,3,4] CHEN Jiaxing;JIANG Di;ZHANG Xiaoyu(School of Earth Sciences,Zhejiang University,Hangzhou 310027,China;College of Information Science&Electronic Engineering,Zhejiang University,Hangzhou 310027,China;Hainan Institute of Zhejiang University,Sanya 572000,Hainan Province,China;Ocean Academy,Zhejiang University,Zhoushan 316000,Zhejiang Province,China)

机构地区：[1]浙江大学地球科学学院,浙江杭州310027 [2]浙江大学信息与电子工程学院,浙江杭州310027 [3]浙江大学海南研究院,海南三亚572000 [4]浙江大学海洋研究院,浙江舟山316000

出　　处：《浙江大学学报（理学版）》2022年第1期76-84,共9页Journal of Zhejiang University（Science Edition）

基　　金：国家自然科学基金资助项目(40706057);国家重点研发计划重点专项(2018YFC1406600);浙江省重点研发计划择优委托项目(2021C01017);上海航天科技创新基金项目(SAST2019-047).

摘　　要：河口近海海域的海表温度分布特征对于深入理解海洋热力、动力过程及海气相互作用等自然过程及综合效应具有重要意义。卫星数据重构是精确获取动态大面积海表温度数据的重要手段,采用非线性系统的动态模态分解(dynamic mode decomposition,DMD)数据分析方法,利用2003年1月至2016年7月的MODIS\SST数据,经剔除异常数据、填补空白数据后,重构了2016年8月至2019年12月长江口海洋表面温度数据,并评估了重构效果。研究结果表明,在时序数据充足的情况下,DMD算法能很好地解决动态系统的采样问题。DMD结合正交三角(orthogonal right triangular,QR)分解算法能有效重构长江口的海表温度数据,平均均方根误差(root mean square error,RMSE)为0.0076。进一步分析发现,无论是DMD算法还是DMD结合QR分解算法,还原结果精度都较高。The characteristics of sea surface temperature distribution in the estuarine and offshore areas are of great significance for understanding natural processes such as ocean thermal and dynamic processes and air sea interaction,as well as the comprehensive results under the influence of human activities.Satellite data reconstruction is an important means to obtain dynamic and accurate sea surface temperature data.This study adopted a dynamic mode decomposition(DMD)for nonlinear systems with sufficient data,It took MODIS\SST data from January 2003 to July 2016,after eliminating the abnormal data and filling in the blank data,the ocean surface temperature data of the Yangtze River Estuary from August 2016 to December 2019 were reconstructed,and the reconstruction effect was evaluated.The research shows that DMD algorithm can solve the sampling problem of dynamic system well provided that the time series data is sufficient.Our results show that DMD algorithm combined with orthogonal right triangular(QR)decomposition can effectively reconstruct the sea surface temperature data of the Yangtze River Estuary,and the average root mean square error(RMSE)is 0.0076.Further analysis shows that both DMD algorithm and DMD algorithm combined with QR decomposition have high precision.

关 键 词：长江口 海洋表面温度 动态模态分解 数据重构 

分 类 号：P731.11[天文地球—海洋科学]