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Modified ICON-FUV O/N2 Datasets Corrected for Ionospheric Contamination

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DataCite Commons2023-03-31 更新2024-07-13 收录
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https://data.lib.vt.edu/articles/dataset/Modified_ICON-FUV_O_N2_Datasets_Corrected_for_Ionospheric_Contamination/21538380/2
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资源简介:
Data files containing modified data of the thermospheric column number density ratio of atomic oxygen to molecular nitrogen (O/N2) during two different ~ three week long time periods in 2020: one around March equinox and the other around September equinox. These data are retrieved from far ultraviolet brightness intensities observed by the Far Ultraviolet Imager (FUV) onboard the Ionospheric Connection Explorer (ICON) in Low Earth Orbit (https://icon.ssl.berkeley.edu/Data/Data-Product-Matrix). However, the datasets published here have been corrected for ionospheric contamination of the 135.6 nm emission by subtracting the estimated ionospheric contribution to emissions at 135.6 nm based on the Global Ionospheric Specification (GIS) ionosphere. Each file gives time series of location, time of retrieval, O/N2, and O/N2 uncertainty. <br> Associated Publication Citation: Krier, C. S., England, S. L., Meier, R. R., &amp; Frey, H. U. (2023). Reducing the ionospheric contamination effects on the column O/N2 ratio and its application to the identification of non-migrating tides. <em>Journal of Geophysical Research: Space Physics</em>, <em>128</em>, e2022JA031148. https://doi.org/10.1029/2022JA031148

本数据集收录了2020年两段各约三周时长的时间内,热层大气原子氧与分子氮柱数密度比(O/N₂)的修正后数据;两段时段分别对应春分前后的3月周期,以及秋分前后的9月周期。 这些数据由近地轨道(Low Earth Orbit, LEO)上的电离层连接探测器(Ionospheric Connection Explorer, ICON)搭载的远紫外成像仪(Far Ultraviolet Imager, FUV)所观测的远紫外亮度强度反演得到,数据源地址为https://icon.ssl.berkeley.edu/Data/Data-Product-Matrix。 本次发布的数据集已针对135.6 nm谱线发射的电离层污染完成校正:基于全球电离层规范(Global Ionospheric Specification, GIS)模型,估算135.6 nm发射的电离层贡献分量并将其扣除,以此消除污染影响。 每个数据文件均包含反演时刻、观测位置、O/N₂数值以及O/N₂不确定度的时间序列数据。 关联出版物引用:Krier, C. S., England, S. L., Meier, R. R., & Frey, H. U. (2023). 降低电离层污染对柱密度O/N₂比的影响及其在非迁移潮汐识别中的应用. 《地球物理研究杂志:空间物理学》, 128, e2022JA031148. https://doi.org/10.1029/2022JA031148
提供机构:
University Libraries, Virginia Tech
创建时间:
2023-03-31
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