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The three-dimensional ionospheric electron density imaging in Japan using the approximate Kalman filter algorithm
Journal of Atmospheric and Solar-Terrestrial Physics ( IF 1.8 ) Pub Date : 2021-03-28 , DOI: 10.1016/j.jastp.2021.105628
Rui Song , Katsumi Hattori , Xuemin Zhang , Chie Yoshino

The three-dimensional ionospheric electron density (Ne) over Japan is retrieved by assimilating the ground-based total electron content (TEC) datasets into the International Reference Ionosphere (IRI) background model. To reduce the computational burdens encountered in the full Kalman filter (KF) algorithm, the simplified KF (SKF), a time-independent data assimilation scheme with no recursion, is adopted. The spatial resolution is 1°, 1°, and 30 km in latitude, longitude, and altitude, and the temporal resolution is 1 h. Regarding the quite geomagnetic condition, seasonal variations in the ionosphere were investigated firstly. The results show that the reconstructed Ne could well capture the seasonal ionospheric characteristics and semiannual anomaly. Subsequently, NmF2 (F2 layer peak electron density) values during April 3–9, 2013 (high solar activity) and 2018 (low solar activity) were reproduced and simulated by the SKF and IRI model, respectively. In contrast with the ionosonde data, the results indicated the reconstructed NmF2 was apt to capture the underlying trends of diurnal and annual variations more accurately. For the efficiency under the disturbed geomagnetic condition, we took a great geomagnetic storm that happened on August 26, 2018 as an example. The reproduced results also provided better imaging for Ne distributions by analyzing the vertical slices and profiles provided by SKF and IRI. It is suggested that the SKF algorithm is promising for ionospheric researches and practical applications in Japan.



中文翻译:

使用近似卡尔曼滤波算法的日本三维电离层电子密度成像

通过将基于地面的总电子含量(TEC)数据集同化为国际参考电离层(IRI)背景模型,可以检索日本的三维电离层电子密度(Ne)。为了减少在完整卡尔曼滤波器(KF)中遇到的计算负担,采用了简化的KF(SKF),即无递归的与时间无关的数据同化方案。在纬度,经度和海拔上,空间分辨率为1°,1°和30 km,时间分辨率为1 h。关于相当的地磁条件,首先研究了电离层的季节变化。结果表明,重建的Ne能很好地捕获季节电离层特征和半年度异常。随后,在4月3日至9日,NmF2(F2层峰值电子密度)值 通过SKF和IRI模型分别复制并模拟了2013年(太阳活动高)和2018年(太阳活动低)。与离子探空仪数据相反,结果表明,重建的NmF2易于更准确地捕获日变化和年变化的潜在趋势。为了提高受干扰地磁条件下的效率,我们以2018年8月26日发生的一次大地磁风暴为例。通过分析SKF和IRI提供的垂直切片和剖面,再现的结果还为Ne分布提供了更好的成像。SKF算法在日本电离层研究和实际应用中具有广阔的前景。结果表明,重建的NmF2易于更准确地捕获日变化和年变化的潜在趋势。为了提高受干扰地磁条件下的效率,我们以2018年8月26日发生的一次大地磁风暴为例。通过分析SKF和IRI提供的垂直切片和剖面,再现的结果还为Ne分布提供了更好的成像。SKF算法在日本电离层研究和实际应用中具有广阔的前景。结果表明,重建的NmF2易于更准确地捕获日变化和年变化的潜在趋势。为了提高受干扰地磁条件下的效率,我们以2018年8月26日发生的一次大地磁风暴为例。通过分析SKF和IRI提供的垂直切片和剖面,再现的结果还为Ne分布提供了更好的成像。SKF算法在日本电离层研究和实际应用中具有广阔的前景。通过分析SKF和IRI提供的垂直切片和剖面,再现的结果还为Ne分布提供了更好的成像。SKF算法在日本电离层研究和实际应用中具有广阔的前景。通过分析SKF和IRI提供的垂直切片和剖面,再现的结果还为Ne分布提供了更好的成像。SKF算法在日本电离层研究和实际应用中具有广阔的前景。

更新日期:2021-04-09
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