集合卡尔曼滤波在浅水模式数据同化中的应用  

Application of shallow water model by use of ensemble Kalman filter data assimilation

作　　者：黄勇[1] 王颖[2] 

机构地区：[1]解放军理工大学气象学院,江苏南京211101 [2]总参气象水文局,北京100081

出　　处：《解放军理工大学学报（自然科学版）》2008年第1期85-90,共6页Journal of PLA University of Science and Technology(Natural Science Edition)

基　　金：国家自然科学基金资助项目(40175012)

摘　　要：为了研究集合Kalman滤波同化技术应用于非线性动力学模式的同化效果,通过利用集合Kalman滤波技术对浅水理论中均质不可压流体运动的动力学模式进行理想的数据同化试验。分析集合Kalman滤波同化方法应用于动力学系统的计算方法和步骤。比较三维变分和集合Kalman滤波的同化效果,讨论了集合Kalman滤波数据同化方法的基本性质和同化观测的频率对集合Kalman滤波同化效果的影响。通过试验证明,集合Kalman滤波数据同化方法能够成功地应用于浅水均质不可压流体的动力学系统,可有效地抑制估计误差的增长,为模式预报提供更加理想的初值,改善预报效果。In order to research the effect of ensemble Kalman filter,some desirable data assimilation experiments were made,the calculational methods and steps were analyzed with shallow model systems.The Kalman filter data assimilation methods were applied in dynamical systems,the result of ensemble Kalman filter was compared with three dimension variational data assimilation,and the elementary properties of the ensemble Kalman filter data assimilation techniques were discussed.The assimilation frequency on the result of the ensemble Kalman filter data assimilations was calculated.The experiments show that the data assimilation techniques on the ensemble Kalman filter are successfully applied in shallow water model dynamical systems,the abandoned develpment of the estimation error variances for the model varibles controlled, and the forecast of model states improved.

关 键 词：集合Kalman滤波同化 浅水模式 数值试验 

分 类 号：P456[天文地球—大气科学及气象学]