大气数据同化方法的研究与应用进展  

The Developments and Applications of Atmosphereic Data Assimilation

作　　者：林行[1] 高山红[2] 黄容 

机构地区：[1]青岛市气象台,山东青岛266001 [2]青岛海洋大学物理海洋研究所,山东青岛266003

出　　处：《山东气象》2004年第4期16-18,共3页Journal of Shandong Meteorology

摘　　要：简要介绍了大气数据同化的基本思想与方法 ,阐述了松弛逼近法。Atmospheric data assimilation techniques are motivated forward by the advance of numerical weather prediction models and the increasing rapidly observations, including the great amount of unconventional data obtained by remote sensing. There are mainly three general concepts that have been discussed repeatedly for data assimilation in meteorology. The variational (especially adjoint variational) method has been a popular and fully studied scheme, which, however, has a drawback that model errors (system noise) are not taken into account due to the imperfection of the numerical model. The second class of methods are those described as sequential data assimilation, which are represented by Kalman filters. The third class is nudging method, which is simple but efficient and used widely. The above three methods are discussed in this paper after a brief introduction of atmospheric data assimilation. The last section of the paper presents the applications of atmospheric data assimilation.

关 键 词：数据同化 松弛逼近 KALMAN滤波 变分约束 

分 类 号：P435[天文地球—大气科学及气象学]