Results 81 to 90 of about 2,463,978 (199)

Thermospheric density variations during extreme geomagnetic storms and their potential impact on the orbit of the China space station

Frontiers in Astronomy and Space Sciences
Temporal variation and spatial distribution of the thermospheric density can change significantly during geomagnetic storms. These variations in thermospheric density enhance atmospheric drag, posing risks to Low-Earth-Orbit (LEO) spacecraft.
Kun Zhang, Kun Zhang, Yanshi Huang, Yanshi Huang, Fengsi Wei, Fengsi Wei, Pingbing Zuo, Pingbing Zuo, Hao Yang, Jinlong Ji, Zehao Chen   +10 more
doaj   +1 more source

Uncertainty quantification techniques for data-driven space weather modeling: thermospheric density application. [PDF]

Sci Rep, 2022
Licata RJ, Mehta PM.
europepmc   +1 more source

Modulation of Thermospheric Circulation by Lower‐Thermospheric Winter‐to‐Summer Circulation: The Atmosphere Gear Effect

Geophysical Research Letters
This study investigates the impact of the lower‐thermospheric winter‐to‐summer circulation on the thermosphere's thermal structure and meridional circulation. Using NCAR TIE‐GCM, we compare simulations with and without the lower‐thermospheric circulation,
Jack C. Wang, Jia Yue, Wenbin Wang, Liying Qian   +3 more
doaj   +1 more source

Flying Through Uncertainty

Space Weather, 2020
Space weather is the main source of uncertainty in the position of all objects in low Earth orbit (LEO) below about 1,000 km. The main impact is strong variation in the neutral density of the thermosphere as it responds to radiative inputs from the Sun ...
T. E. Berger, M. J. Holzinger, E. K. Sutton, J. P. Thayer   +3 more
doaj   +1 more source

Near-Real-Time Global Thermospheric Density Variations Unveiled by Starlink Ephemeris

Remote Sensing
Previous efforts to retrieve thermospheric density using satellite payloads have been limited to a small number of satellites equipped with GNSS (Global Navigation Satellite System) receivers and accelerometers.
Zhuoliang Ou, Jiahao Zhong, Yongqiang Hao, Ruoxi Li, Xin Wan, Kang Wang, Jiawen Chen, Hao Han, Xingyan Song, Wenyu Du, Yanyan Tang   +10 more
doaj   +1 more source

Thermospheric Mass Density

如果您有任何问题,欢迎您联系第一作者。(电子邮件:panqian@whu.edu.cn) 本文重点介绍了使用62列特征参数作为MLP和BiLSTM积分获得的模型的输入来预测热层质量密度。只有 Swarm 卫星数据用于模型的训练、验证和测试。 一、数据集 或者,您可以创建自己的数据集,该数据集由 62 列输入参数和 1 列输出参数(热层质量密度)组成,如文中所述,所有参数的分辨率线性插值为 10 秒均匀。总体时间范围为2014.02.01-2020.09.30。我们也提供生成的数据集,但由于数据集较大,因此将其拆分为多个文件(subset_i),使用时可以自行合并。 二、守则 模型框架在“模型framework.bmp”中进行了描述,有关详细说明,请参阅本文的模型构造部分,有关具体代码 ...
openaire   +2 more sources

Thermospheric density from Starlink TLE: data analysis and preliminary results

Earth, Planets and Space
This study examines the feasibility of utilizing Two-Line Element (TLE) data from Starlink satellites to estimate thermospheric density. TLE data for satellites in orbital decay were collected from September 19 to November 6, 2024.
Mamoru Yamamoto, Takuya Sori
doaj   +1 more source

An index description of the general characteristics of thermospheric density based on the Two-Line-Element datasets and the Spectral Whitening Method

<p>Data and code used in "An index description of the general characteristics of thermospheric density based on the Two-Line-Element datasets and the Spectral Whitening Method"</p ...
Wu, Yihan
core   +1 more source

In situ and ground-based intercalibration measurements of plasma density at l = 2.5 [PDF]

, 2003
[1] Two independent ground-based experiments and two satellite-borne experiments are used to interpret the changes in plasmaspheric composition at the same point in space during moderate geomagnetic activity on 22 January and 14 February 2001.
Bailey, G.J., Menk, F.W., Mann, I.R., Rose, M.C., Wilford, C.R., Milinevski, G., Reinisch, B.W., Thomson, N.R., Goldstein, J., Clilverd, M.A., Yearby, K.H., Carpenter, D.L., Sandel, B.R.   +12 more
core   +1 more source

A Global Thermospheric Density Prediction Framework Based on a Deep Evidential Method

Space Weather
Thermospheric density influences the atmospheric drag and is crucial for space missions. This paper introduces a global thermospheric density prediction framework based on a deep evidential method. The proposed framework predicts thermospheric density at
Yiran Wang, Xiaoli Bai
doaj   +1 more source