基于 GOLD Nmax 数据的低纬度电离层日间变化的水平空间相关性

IF 3.7 2区 地球科学 Space Weather Pub Date : 2023-12-27 DOI:10.1029/2023sw003627
Jiawen Chen, Jiahao Zhong, Yongqiang Hao, Xin Wan, Qiaoling Li, Zijing Tang, Xingyan Song, Hao Han, Kang Wang, Jiawei Kuai, Aojun Ren
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引用次数: 0

摘要

利用2018-2022年期间GOLD测量得出的峰值电子密度数据分析低纬度电离层昼夜变化的幅度和相关性。相关距离描述了空间位置之间的相关性,本文将其定义为相关系数从1下降到0.7时的角间隔。本研究讨论了相关距离随当地时间、季节、磁纬度、太阳活动和地磁活动的变化。在低地磁纬度(磁纬度 <30°)地区,地带相关距离的平均值约为 8.55°,经向相关距离的平均值约为 3.56°。统计结果表明,日冕相关距离和经向相关距离随当地前夜时间的变化很小,但它们表现出明显的季节和纬度变化。日冕相关距离和子午相关距离都随太阳活动的增加而增加,随地磁活动的增强而减小。EIA强度和梯度主要调节与磁纬、季节和太阳通量水平相关的相关距离分布。建立了一个经验模型来描述低纬度地区相关距离的时空变化。对相关距离的研究将有助于更好地了解电离层的可变性和改进数据同化。
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Horizontal Spatial Correlation of the Ionospheric Day-To-Day Variations at Low Latitudes Based on GOLD Nmax Data
Peak electron density data derived from GOLD measurements during 2018–2022 are used to analyze the magnitudes and correlations of ionospheric diurnal variability at low latitudes. The correlation distance describes the correlations between spatial locations and is defined in this paper as the angular separation at which the correlation coefficient decreases from 1 to 0.7. Variations in correlation distance with local time, season, magnetic latitude, solar activity, and geomagnetic activity are discussed in this study. The average value of the zonal correlation distance is approximately 8.55° and 3.56° for the meridional direction at low geomagnetic latitudes (magnetic latitudes <30°). The statistical results indicate that both zonal and meridional correlation distances vary little with local time premidnight, while they show pronounced seasonal and latitudinal variations. Both zonal and meridional correlation distances increase with increasing solar activity and decrease with enhancing geomagnetic activity. The EIA strength and gradient mainly modulate the distributions of correlation distances related to magnetic latitude, season, and solar flux level. An empirical model is constructed to describe the temporal and spatial variations in the correlation distance at low latitudes. The study of correlation distances would contribute to a better understanding of ionospheric variability and improvements in data assimilation.
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