北京航空航天大学学报 ›› 2017, Vol. 43 ›› Issue (9): 1757-1765.doi: 10.13700/j.bh.1001-5965.2016.0735

• 论文 • 上一篇    下一篇

临近空间38°N大气密度特性及建模技术

肖存英1, 胡雄1, 杨钧烽1, 闫召爱1,2, 刘涛1,2, 程旋1,2   

  1. 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
  • 收稿日期:2016-09-13 出版日期:2017-09-20 发布日期:2017-01-13
  • 通讯作者: 肖存英,E-mail:xiaocy@nssc.ac.cn E-mail:xiaocy@nssc.ac.cn
  • 作者简介:肖存英,女,博士,研究员,硕士生导师;主要研究方向:临近空间大气环境;胡雄,男,博士,研究员,博士生导师;主要研究方向:临近空间大气环境
  • 基金资助:
    国家重点研发计划(2016YFB0501503)

Characteristics of atmospheric density at 38°N in near space and its modeling technique

XIAO Cunying1, HU Xiong1, YANG Junfeng1, YAN Zhaoai1,2, LIU Tao1,2, CHENG Xuan1,2   

  1. 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2016-09-13 Online:2017-09-20 Published:2017-01-13
  • Supported by:
    National Key R&D Program of China (2016YFB0501503)

摘要: 针对临近空间大气环境复杂时空变化的定量表征和仿真建模,基于11年TIMED/SABER大气密度数据,采用网格划分和数学统计的方法,得到了38°N大气密度在20~100 km的气候平均值和标准差。定量结果用于表征和分析了静态缓变气候平均态以及动态瞬变大气扰动态的变化规律,结果表明,38°N大气平均密度随高度、季节、经度变化显著。在此基础上,提出了临近空间大气密度表征为气候平均量和大气扰动量之和的建模方法,并建立了大气随机扰动自回归模型,通过仿真试验及与激光雷达大气密度实测数据的比较,结果表明该建模方法可行。

关键词: 临近空间, 大气密度, 飞行器, 仿真, 建模

Abstract: The environment of near space atmosphere is very complex. Its spatial and temporal changes are hard to be characterized and modeled. With 11 years of TIMED/SABER atmospheric density data, the climate means and standard deviations at 38°N in 20-100 km were obtained by the method of global gridding and mathematical statistics. Quantitative results were used to represent and analyze the characteristics of static slow climate changes and dynamic transient atmospheric disturbances. The results show that the atmospheric density at 38°N varies remarkably with altitude, seasons and longitude. A modeling method was set up, where the atmospheric density in near space can be represented as the sum of the climate means and atmospheric disturbances. A self-regression model was established for the atmospheric random disturbances. Model simulations were taken and compared with the lidar-observed density data, showing that the modeling method is feasible.

Key words: near space, atmospheric density, aircraft, simulation, modeling

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