数据同化在空间天气学中的应用  

Application of Data Assimilation in Space Weather

作　　者：张晗可 沈芳 ZHANG Hanke;SHEN Fang(National Space Science Center,Chinese Academy of Sciences,Beijing 100190;University of Chinese Academy of Sciences,Beijing 100049)

机构地区：[1]中国科学院国家空间科学中心,北京100190 [2]中国科学院大学,北京100049

出　　处：《空间科学学报》2022年第3期422-436,共15页Chinese Journal of Space Science

基　　金：国家自然科学基金项目(41774184,41974202);中国科学院战略性先导科技专项(XDB 41000000);中国科学院国家空间科学中心“攀登计划”项目共同资助。

摘　　要：由太阳活动引起的耀斑和日冕物质抛射等短时间尺度变化的空间天气事件会影响并危害地球磁层、电离层、中高层大气、卫星运行安全以及人类健康,因此对这些空间天气事件的预测显得尤为重要。数据同化在稀疏观测和异步采集的情况下能够增加模型的预测能力,对模型变量进行自洽分析。在数值预报中引入数据同化方法,能够提高预测可信度。本文从数据同化方法的角度出发,主要分析了数据同化目前在大气、电离层、磁层、太阳及其他行星科学研究中的应用,并初步讨论了数据同化未来在空间天气方面的应用。Space weather events caused by solar activities such as flares and Coronal Mass Ejections(CMEs)can affect the magnetosphere of the Earth,the middle and upper atmosphere,ionosphere,the safety of satellite operation and human health directly or indirectly.Therefore,the prediction of space weather events is particularly important.In the case of sparse observation and asynchronous sampling,data assimilation can increase the prediction ability of the model,self-consistent analysis of model variables can be carried out,and the introduction of data assimilation method in numerical prediction can improve the reliability of the prediction.This paper mainly introduces the application of data assimilation in the atmosphere,ionosphere,magnetosphere,the Sun and other planets from the perspective of data assimilation methods.The potential applications of data assimilation in space weather in the future are also discussed.

关 键 词：数据同化 卡尔曼滤波 空间天气 太阳风 

分 类 号：P353[天文地球—空间物理学]