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首页> 外文期刊>Journal of Geodesy >Temporal and spatial variations of global ionospheric total electron content under various solar conditions
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Temporal and spatial variations of global ionospheric total electron content under various solar conditions

机译:不同太阳条件下全球电离层总电子含量的时空变化

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By utilizing the numerical technique of principal component analysis (PCA), this work analyses temporal and spatial variations of the ionosphere under various solar conditions during the period 1999-2013. Applying the PCA technique to the time series of the global ionospheric total electron content (TEC) maps provides an efficient method for analyzing the main ionospheric variability on a global scale that is able to decompose periodic variations (e.g., annual and semiannual oscillations) while retaining the asymmetry in the temporal and spatial domains (e.g., seasonal and equator anomalies). The TEC series of different local times are processed separately at two time scales: (1) the whole 15 years of the period of study and (2) the individual years. In contrast with previous studies, the analysis of the dataset of the 15 years shows that dawn (e.g., LT4-6) and late morning (LT10-12) are the more remarkable characteristic times for ionospheric variability. This study also reveals a cyclic trend of the variability with respect to local times. The first two modes, which contain 80-90% of the total variance, represent spatial distributions and temporal variations with respect to the different stages of the solar cycle and local times. Annual and semiannual variations are demodulated from the first two modes, and the results show that these variations evidently have distinct trends for daytime and nighttime. An exception is that, under active solar conditions, extremely strong solar irradiance during the daytime has a residual effect on the variability of the nighttime.
机译:利用主成分分析(PCA)的数值技术,这项工作分析了1999-2013年期间各种太阳条件下电离层的时空变化。将PCA技术应用于全球电离层总电子含量(TEC)图的时间序列可提供一种有效的方法,用于在全球范围内分析主要电离层的变化性,从而能够分解周期性变化(例如,年度和半年度振荡),同时保留时空域中的不对称性(例如,季节和赤道异常)。不同地方时间的TEC系列在两个时间尺度上分别处理:(1)学习期的整个15年和(2)各个年。与之前的研究相比,对这15年的数据集的分析表明,黎明(例如LT4-6)和清晨(LT10-12)是电离层变化最明显的特征时间。这项研究还揭示了当地时间变化的周期性趋势。前两种模式占总方差的80-90%,代表相对于太阳周期和当地时间不同阶段的空间分布和时间变化。从前两种模式对年度和半年度变化进行了解调,结果表明,这些变化显然在白天和夜间具有明显的趋势。一个例外是,在活跃的阳光条件下,白天极强的太阳辐照度会对夜间的变化性产生残留影响。

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