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临近空间大气密度时空扰动规律及建模研究

曾丹丹 万田 李帅辉

曾丹丹, 万田, 李帅辉. 临近空间大气密度时空扰动规律及建模研究. 力学学报, 2022, 54(10): 1-9 doi: 10.6052/0459-1879-22-231
引用本文: 曾丹丹, 万田, 李帅辉. 临近空间大气密度时空扰动规律及建模研究. 力学学报, 2022, 54(10): 1-9 doi: 10.6052/0459-1879-22-231
Zeng Dandan, Wan Tian, Li Shuaihui. Study of the temporal-spatial fluctuations and empirical model of near space atmospheric density. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(10): 1-9 doi: 10.6052/0459-1879-22-231
Citation: Zeng Dandan, Wan Tian, Li Shuaihui. Study of the temporal-spatial fluctuations and empirical model of near space atmospheric density. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(10): 1-9 doi: 10.6052/0459-1879-22-231

临近空间大气密度时空扰动规律及建模研究

doi: 10.6052/0459-1879-22-231
详细信息
    作者简介:

    李帅辉, 研究员, 主要研究方向: 流体力学. E-mail: lee@imech.ac.cn

  • 中图分类号: 

STUDY OF THE TEMPORAL-SPATIAL FLUCTUATIONS AND EMPIRICAL MODEL OF NEAR SPACE ATMOSPHERIC DENSITY

  • 摘要: 大气密度是飞行器能源动力设计、飞行控制中的重要输入参数. 近年来, 多项研究发现, 对于临近空间高层大气, 常用经验模型如USSA-76, NRLMSISE-00的密度预示值偏大. 另外, 随着飞行器精细化设计趋势, 要求经验模型可预示不同纬度、昼夜和季节条件下的密度特性. 基于此, 本文利用卫星观测数据全面分析了临近空间大气密度随纬度、地方时、日期的变化规律, 包括变化模式和变化幅度. 纬度、日期引起的变化幅度大于地方时引起的变化幅度. 纬度、日期引起的密度变化在不同高度范围表现出不同模式; 变化幅度在78 km附近达最大值, 在22 km和92 km附近达局部极小值. 地方时引起的密度变化随高度递增. 根据大气密度的时空变化特性, 本文提出了临近空间大气密度的时空扰动模型, 该模型能描述临近空间大气密度及其随纬度、地方时、日期的变化规律. 与以往经验模型相比, 时空扰动模型可更好地描述不同高度下密度的时空变化规律. 在相同误差带条件下, 本文模型的置信度明显优于NRLMSISE-00. 本文建模方法合理, 模型结果对临近空间飞行器设计有应用价值.

     

  • 图  1  卫星观测的14-108 km纬度(a)、地方时(b)和日期(c)对大气密度的影响规律

    Figure  1.  Variations of atmospheric density with latitude (a), local time (b), date (c) observed by satellite at altitudes from 14 to 108 km

    图  2  高度70 km(a)、100 km (b), (ϕ,d)平面内的大气密度变化规律

    Figure  2.  Variations of atmospheric density with ϕ and d at altitudes of 70 km(a) and 100 km (b)

    图  3  纬度、日期、地方引起的密度扰动幅度随高度的变化规律

    Figure  3.  Profiles of variation amplitudes caused by latitude, local time and date

    图  4  卫星测量平均大气密度及其与USSA-76、本文模型的相对偏差

    Figure  4.  Profiles of averaged atmospheric density observed by satellite and its relative deviation from USSA-76 and present model

    图  5  14~108 km高度, 卫星测量的密度时空扰动项的特征分布范围

    Figure  5.  Range of temporal-spatial fluctuations of density observed by satellite at altitudes of 14~108 km

    图  6  时空扰动测量值与模型值之差在高度14~108 km内的变化. (a)均值及特征分布范围, (b)均方根

    Figure  6.  Difference of temporal-spatial fluctuations of density between observed values and modeled values at altitudes of 14-108 km. (a) mean value and range (b) root of mean square

    图  7  本文模型描述的纬度(a)、地方时(b) 和日期(c)对大气密度的影响在高度14~108 km内的变化

    Figure  7.  Variations of atmospheric density with latitude (a), local time (b) and date (c) calculated by present model at altitudes from 14 to 108 km

    图  8  80 km (a)、90 km (b)、100 km (c)高度, SABER数据与三种模型预测结果对比. 红点: SABER, 绿点: NRLMSISE–00模型, 蓝点: 时空扰动模型, 黑线: USSA–76模型

    Figure  8.  Comparison of three atmospheric density models and observed data from 2002 to 2014 at altitudes 80 (a), 90 (b) and 100 km (c). red symbol: SABER,green symbol: NRLMSISE-00, blue symbol: temporal-spatial variation model, black line: USSA-76

    表  1  80, 90, 100 km高度, 太阳活动强(2002)、弱(2008)年份的密度 (kg/m3)

    Table  1.   At altitudes 80, 90, 100 km , the global mean density (kg/m3) for years with higher solar activity (2002) and lower solar activity (2008)

    Altitude/kmGlobal mean density in 2002Global mean density in 2008
    801.64 × 10−51.56 × 10−5
    903.01 × 10−62.79 × 10−6
    1005.36 × 10−74.67 × 10−7
    下载: 导出CSV

    表  2  高度80, 90和100 km, 3种大气模型, 不同误差带要求下, 对比SABER数据的置信度

    Table  2.   altitudes 80, 90 and 100 km, under different error bands, confidence coefficients of the three atmospheric models compared to SABER data

    Altitude/kmError band ± 30% ± 50% ± 80%
    80USSA–7666.1%85.2%96.5%
    80NRLMSISE–0088.6%98.9%99.9%
    80Present model99.0%99.9%99.99%
    90USSA–7668.3%92.1%99.1%
    90NRLMSISE–0076.5%95.9%99.7%
    90Present model98.7%99.9%99.98%
    100USSA–7673.0%87.7%95.2%
    100NRLMSISE–0075.4%90.8%97.7%
    100Present model93.2%98.5%99.7%
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-05-29
  • 录用日期:  2022-07-24
  • 网络出版日期:  2022-07-25

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