地球科学进展 ›› 2012, Vol. 27 ›› Issue (7): 747 -757. doi: 10.11867/j.issn.1001-8166.2012.07.0747

综述与评述 上一篇    下一篇

数据同化算法研究现状综述
马建文 1,秦思娴 1,2   
  1. 1.中国科学院对地观测与数字地球科学中心,北京100094;
    2.中国科学院研究生院,北京100049
  • 收稿日期:2012-01-04 修回日期:2012-05-14 出版日期:2012-07-10
  • 通讯作者: 马建文(1953-),男,河北献县人,研究员,主要从事遥感数据智能与自动化处理算法研究.  E-mail:jwma@ceode.ac.cn
  • 基金资助:

    国家重大科技基础设施项目“航空遥感系统——地球科学数据处理软件系统”(编号:ZGHG-2009-1-1)资助.

Recent Advances and Development of Data Assimilation Algorithms

Ma Jianwen 1, Qin Sixian 1,2   

  1. 1.Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing100094, China;
    2.Graduate University of the Chinese Academy of Sciences, Beijing100049, China
  • Received:2012-01-04 Revised:2012-05-14 Online:2012-07-10 Published:2012-07-10

近年来,全球环境变化对人类生存影响日益突出,为了加强对陆地—大气—海洋的监测,全球对地观测系统计划(GEOSS)和全球环境与安全监测计划(GMES)等相继被提出。数据同化算法作为连接观测数据与模型模拟预测的关键桥梁也得到了迅速发展,显著标志新的数学研究成果不断被引入数据同化算法中。在国家重大科技基础设施项目“航空遥感系统——地球科学数据处理软件系统”需求背景条件下,梳理遥感数据同化算法的国内外发展现状,明确数据同化算法开发的技术主线和重点内容,稳步推进数据同化算法理论研究和软件开发。

]In recent years, global environmental change has more and more affected the survival of human beings. In order to enhance the observation of the landatmospheric-ocean, the Global Earth Observation System of Systems (GEOSS) and Global Monitoring for Environment and Security (GMES) have been proposed. Data assimilation, the key connection between observation data and model simulations, also gets rapid development. The most significant signs are the continuous introductions of new mathematical achievements into the data assimilation fields. Under the background of the “National Airborne Remote Sensing System—The Earth Science Data Processing Software System”, we review the development of the data assimilation algorithms so as to determine the technical route and major contents of this project and promote the research on data assimilation theory and the development of the software.

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