MASNUM-WAM海浪模式集合Kalman滤波同化研究——Ⅱ.集合样本对同化效果的影响
发布时间：2018-07-13 14:57
【摘要】：背景误差相关结构的确定是影响海浪同化效果的关键因素之一。集合Kalman滤波是一种较为成熟的同化方法,其可以对背景误差进行实时更新和动态估计,现已广泛应用于海洋和大气领域的研究。本文基于MASNUM-WAM海浪模式,分别采用静态样本集合Kalman滤波和EAKF方法,针对2014年全球海域开展海浪数据同化实验,同化资料为Jason-2卫星高度计数据,利用Saral卫星高度计资料对同化实验结果进行检验。结果表明,两组同化方案均有效提高了海浪模式的模拟水平,EAKF方案在风场变化较大的西风带区域表现显著优于静态样本集合Kalman滤波方案,但总体上两者相差不大。综合考虑计算成本和同化效果,静态样本集合Kalman滤波方案更适用于海浪业务化预报。
[Abstract]:The determination of background error correlation structure is one of the key factors affecting the wave assimilation effect. Ensemble Kalman filtering is a mature assimilation method, which can update and estimate background errors in real time. It has been widely used in the research of ocean and atmosphere. Based on the MASNUM-WAM wave model, the static sample set Kalman filter and EAKF method are used to carry out wave data assimilation experiments for the global sea area in 2014. The assimilation data are Jason-2 satellite altimeter data. The data of Saral satellite altimeter are used to test the results of assimilation experiment. The results show that both groups of assimilation schemes can effectively improve the simulation level of wave model and the performance of EAKF scheme is significantly better than that of the static sample set Kalman filtering scheme in the westerly zone where the wind field changes greatly, but there is no significant difference between the two schemes on the whole. Considering the computational cost and assimilation effect, the static sample set Kalman filtering scheme is more suitable for wave operational prediction.
【作者单位】： 中国海洋大学海洋与大气学院;国家海洋局第一海洋研究所海洋环境与数值模拟研究室;海洋国家实验室区域海洋动力学与数值模拟功能实验室;
【基金】：国家高技术研究发展计划-南海及周边海域风浪流耦合同化精细化数值预报与信息服务系统项目,2013AA09A506号 国家重点研发计划项目,2016YFC1402001号,2016YFC1402004号
【分类号】：P731.33
，
本文编号：2119783
[Abstract]:The determination of background error correlation structure is one of the key factors affecting the wave assimilation effect. Ensemble Kalman filtering is a mature assimilation method, which can update and estimate background errors in real time. It has been widely used in the research of ocean and atmosphere. Based on the MASNUM-WAM wave model, the static sample set Kalman filter and EAKF method are used to carry out wave data assimilation experiments for the global sea area in 2014. The assimilation data are Jason-2 satellite altimeter data. The data of Saral satellite altimeter are used to test the results of assimilation experiment. The results show that both groups of assimilation schemes can effectively improve the simulation level of wave model and the performance of EAKF scheme is significantly better than that of the static sample set Kalman filtering scheme in the westerly zone where the wind field changes greatly, but there is no significant difference between the two schemes on the whole. Considering the computational cost and assimilation effect, the static sample set Kalman filtering scheme is more suitable for wave operational prediction.
【作者单位】： 中国海洋大学海洋与大气学院;国家海洋局第一海洋研究所海洋环境与数值模拟研究室;海洋国家实验室区域海洋动力学与数值模拟功能实验室;
【基金】：国家高技术研究发展计划-南海及周边海域风浪流耦合同化精细化数值预报与信息服务系统项目,2013AA09A506号 国家重点研发计划项目,2016YFC1402001号,2016YFC1402004号
【分类号】：P731.33
，
本文编号：2119783
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