Interplanetary shocks and sudden impulses during solar maximum (2000) and solar minimum (1995–1996)

In this work a study is performed on the correlation between fast forward interplanetary shock parameters at 1 Astronomical Unit and sudden impulse (SI) amplitudes in the H-component of the geomagnetic field, for periods of solar activity maximum (year 2000) and minimum (year 1995–1996). Solar wind temperature, density and speed, and total magnetic field, were taken to calculate the static pressures (thermal and magnetic) both in the upstream and downstream sides of the shocks. The variations of the solar wind parameters and pressures were then correlated with SI amplitudes. The solar wind speed variations presented good correlations with sudden impulses, with correlation coefficients larger than 0.70 both in solar maximum and solar minimum, whereas the solar wind density presented very low correlation. The parameter better correlated with SI was the square root dynamic pressure variation, showing a larger correlation during solar maximum (r = 0.82) than during solar minimum (r = 0.77). The correlations of SI with square root thermal and magnetic pressure were smaller than with the dynamic pressure, but they also present a good correlation, with r > 0.70 during both solar maximum and minimum. Multiple linear correlation analysis of SI in terms of the three pressure terms have shown that 78% and 85% of the variance in SI during solar maximum and minimum, respectively, are explained by the three pressure variations. Average sudden impulse amplitude was 25 nT during solar maximum and 21 nT during solar minimum, while average square root dynamic pressure variation is 1.20 and 0.86 nPa^1/2 during solar maximum and minimum, respectively. Thus on average, fast forward interplanetary shocks are 33% stronger during solar maximum than during solar minimum, and the magnetospheric SI response has amplitude 20% higher during solar maximum than during solar minimum. A comparison with theoretical predictions (Tsyganenko’s model corrected by Earth’s induced currents) of the coefficient of sudden impulse change with solar wind dynamic pressure variation showed excellent agreement, with values around 17 nT/nPa^1/2.     

太阳能飞行器能源昼夜闭环仿真分析

以能量为核心，建立太阳能飞行器的获能模型；通过对太阳能飞行器飞行剖面特点的分析，设计飞行过程中各个阶段的飞行方案，并建立相应的耗能模型；考虑目前储能电池技术水平，根据产能和耗能模型，建立储能模型，完成了能源闭环模型的设计；参照Zephyr 7太阳能无人机的结构参数对论文建立的模型进行了仿真分析，获取了飞行过程中能量变化规律，同时对飞行姿态进行优化。结果表明：通过对太阳能飞行器昼夜飞行高度的不同设置以及飞行姿态角的优化，太阳能飞行器可以实现跨昼夜持久飞行。     

2 AU以内的“渐进型”太阳高能粒子事件模拟

太阳高能粒子（Solar Energetic Particle,SEP）事件是影响地球空间以及深空辐射环境的主要因素之一。“渐进型”太阳高能粒子事件中的高能粒子主要来自于日冕物质抛射（Coronal Mass Ejection,CME）所驱动的激波扩散加速（Diffusive Shock Acceleration,DSA）过程。CME驱动的激波在行星际的传播过程中,其结构不断演化,进而影响到高能粒子的加速过程。本文利用二维太阳高能粒子加速和传播模型,对发生于2014年4月18日的太阳高能粒子事件实例进行了数值模拟。模型考察了黄道面上2 AU的距离以内包含地球所在位置的4个不同点,分别计算了每个点上高能粒子的通量。数值模拟的结果表明：黄道面内不同位置的观察点,与激波波前的磁力线连接不同,从而导致观察点处高能粒子的通量有着显著的差异。该模型的计算结果可以为深空探测计划开展辐射环境研究提供必要的输入。     

Study of ionospheric D region changes during solar flares using MF radar measurements

During solar flares, the X-ray radiation suddenly increases, resulting in an increase in the electron density of the atmospheric D region and a strong absorption of short-wave radio waves. Based on Langfang medium frequency (MF) radar, this paper analyzed the variation characteristics of D region in the lower ionosphere from 62 km to 82 km. The analysis focused on multiple C-level and M-level solar flare events before and after the large-scale flare event at 11:53 (UT) on September 6, 2017. The results show that it is difficult to detect the electron density over 70 km in Langfang during solar flares, but the electron density value can be obtained as low as 62 km, and the stronger the flare intensity, the lower the detectable electron density height. Besides, the equal electron density height, the received power of X and O waves will also be significantly reduced during the flares, and the reduction of equal electron density height has a weak linear relationship with flare intensity.     

The adjusted optical properties for Galileo/BeiDou-2/QZS-1 satellites and initial results on BeiDou-3e and QZS-2 satellites

Solar Radiation Pressure (SRP) is the dominant non-gravitational perturbation for GNSS (Global Navigation Satellite System) satellites. In the absence of precise surface models, the Empirical CODE Orbit Models (ECOM, ECOM2) are widely used in GNSS satellite orbit determination. Based on previous studies, the use of an a priori box-wing model enhances the ECOM model, especially if the spacecraft is a stretched body satellite. However, so far not all the GNSS system providers have published their metadata. To ensure a precise use of the a priori box-wing model, we estimate the optical parameters of all the Galileo, BeiDou-2, and QZS-1 (Quasi Zenith Satellite System) satellites based on the physical processes from SRP to acceleration. Validation using orbit prediction proves that the adjusted parameters of Galileo and QZS-1 satellites exhibit almost the same performance as the corresponding published and “best guess” values. Whereas, the estimated parameters of BeiDou-2 satellites demonstrate an improvement of more than 60% over the initial “guess” values. The resulting optical parameters of all the satellites are introduced into an a priori box-wing model, which is jointly used with ECOM and ECOM2 model in the orbit determination. Results show that the pure ECOM2 model exhibits better performance than the pure ECOM model for Galileo, BeiDou-2 GEO and QZS-1 orbits. Combined with the a priori box-wing model the ECOM model (ECOM+BW) results in the best Galileo, BeiDou-2 GEO and QZS-1 orbits. The standard deviation (STD) of satellite laser ranging residuals reduce by about 20% and 5% with respect to the pure ECOM2 model for Galileo and BeiDou-2 GEO orbits, while the reductions are about 40% and 60% for QZS-1 orbits in yaw-steering and orbit-normal mode respectively. BeiDou-2 IGSO and MEO satellite orbits do not benefit much from the a priori box-wing model. In summary, we suggest setting up a unified SRP model of ECOM+BW for Galileo, QZS-1, and BeiDou-2 orbits based on the adjusted metadata. In addition, we estimate the optical parameters of BeiDou-3e and QZS-2 satellites using a limited number of tracking stations. Results regarding the unified SRP model indicate the same advantages, the STD of satellite laser ranging residuals reduces by about 30% and 20% for QZS-2 and BeiDou-3e orbits respectively over orbit products without a priori model. The estimation procedure is effective and easy to apply to the new emerging satellites in the future.     

Comparison of observed ionospheric vertical TEC over the sea in Indian region with IRI-2016 model

The vertical ionospheric TEC values obtained from GAGAN grid based ionospheric delay correction values over the sea in the Indian equatorial region have been compared with the corresponding values derived from the International Reference Ionosphere model, IRI-2016. The objective of this work is to study the deviation of the vertical TEC derived from the IRI model from ground truths over the sea for different conditions. This will serve the basic intention of assessing the candidature of the IRI model as an alternative ionospheric correction model in navigation receivers in terms of accuracy. We have chosen different solar activity periods, seasons, geomagnetic conditions, locations etc. for our comparison and analysis. The TEC values by the IRI-2016 were compared with the actual measured values for the given conditions and errors were obtained. The measured vertical TEC values at the ionospheric grid points were derived from the GAGAN broadcast ionospheric delay data and used as reference. The IRI model with standard internal functions was used in estimating the TEC at the same ionospheric grid points. The errors in the model derived values are statistically analysed. Broadly, the results show that, for the Indian sector over the sea, the IRI model performs better on quiet days in off equatorial regions, particularly in the northern region. The overall performance degrades for other conditions with the model generally underestimating the true TEC values and most severely in the equatorial region. The performance is worst in this region for the disturbed days of the equinoctial period. The comparison study is also done with the TEC data measured directly by dual frequency GPS receivers. The results were found to be in general agreement with those obtained by comparing the model with GAGAN broadcast data as reference. This study will be useful in considering the IRI-2016 model for real time estimates of TEC as an alternative to the current parametric model in a satellite navigation receiver in absence of other options.     

Ionospheric total electron content response to annular solar eclipse on June 21, 2020

The effects of physical events on the ionosphere structure is an important field of study, especially for navigation and radio communication. The paper presents the spatio-temporal ionospheric TEC response to the recent annular solar eclipse on June 21, 2020, which spans across two continents, Africa and Asia, and 14 countries. This eclipse took place on the same day as the June Solstice. The Global Navigation Satellite System (GNSS) based TEC data of the Global Ionosphere Maps (GIMs), 9 International GNSS Service (IGS) stations and FORMOSAT-7/COSMIC-2 (F7/C2) were utilized to analyze TEC response during the eclipse. The phases of the TEC time series were determined by taking the difference of the observed TEC values on eclipse day from the previous 5-day median TEC values. The results showed clear depletions in the TEC time series on June 21. These decreases were between 1 and 9 TECU (15–60%) depending on the location of IGS stations. The depletions are relatively higher at the stations close to the path of annular eclipse than those farther away. Furthermore, a reduction of about ?10 TECU in the form of an equatorial plasma bubble (EPB) was observed in GIMs at ~20° away from the equator towards northpole, between 08:00–11:00 UT where its maximum phase is located in southeast Japan. Additionally, an overall depletion of ~10% was observed in F7/C2 derived TEC at an altitude of 240 km (hmF2) in all regions affected by the solar eclipse, whereas, significant TEC fluctuations between the altitudes of 100 km ? 140 km were analyzed using the Savitzky-Golay smoothing filter. To prove TEC depletions are not caused by space weather, the variation of the sunspot number (SSN), solar wind (V_SW), disturbance storm-time (Dst), and Kp indices were investigated from 16th to 22nd June. The quiet space weather before and during the solar eclipse proved that the observed depletions in the TEC time series and profiles were caused by the annular solar eclipse.     

An empirical solar radiation pressure model for satellites moving in the orbit-normal mode

We present a family of empirical solar radiation pressure (SRP) models suited for satellites orbiting the Earth in the orbit normal (ON) mode. The proposed ECOM-TB model describes the SRP accelerations in the so-called terminator coordinate system. The choice of the coordinate system and the SRP parametrization is based on theoretical assumptions and on simulation results with a QZS-1-like box-wing model, where the SRP accelerations acting on the solar panels and on the box are assessed separately. The new SRP model takes into account that in ON-mode the incident angle of the solar radiation on the solar panels is not constant like in the yaw-steering (YS) attitude mode. It depends on the elevation angle of the Sun above the satellite’s orbital plane. The resulting SRP vector acts, therefore, not only in the Sun-satellite direction, but has also a component normal to it. Both components are changing as a function of the incident angle. ECOM-TB has been used for precise orbit determination (POD) for QZS-1 and BeiDou2 (BDS2) satellites in medium (MEO) and inclined geosynchronous Earth orbits (IGSO) based on IGS MGEX data from 2014 and 2015. The resulting orbits have been validated with SLR, long-arc orbit fits, orbit misclosures, and by the satellite clock corrections based on the orbits. The validation results confirm that—compared to ECOM2—ECOM-TB significantly (factor 3–4) improves the POD of QZS-1 in ON-mode for orbits with different arc lengths (one, three, and five days). Moderate orbit improvements are achieved for BDS2 MEO satellites—especially if ECOM-TB is supported by pseudo-stochastic pulses (the model is then called ECOM-TBP). For BDS2 IGSOs, ECOM-TB with its 9 SRP parameters appears to be over-parameterized. For use with BDS2 IGSO spacecraft we therefore developed a minimized model version called ECOM-TBMP, which is based on the same axis decomposition as ECOM-TB, but has only 2 SRP parameters and is supported by pseudo-stochastic parameters, as well. This model shows a similar performance as ECOM-TB with short arcs, but an improved performance with (3-day) long-arcs. The new SRP models have been activated in CODE’s IGS MGEX solution in Summer 2018. Like the other ECOM models the ECOM-TB derivatives might be used together with an a priori model.     

Scaling analysis and model estimation of solar corona index

A monthly average solar green coronal index time series for the period from January 1939 to December 2008 collected from NOAA (The National Oceanic and Atmospheric Administration) has been analysed in this paper in perspective of scaling analysis and modelling. Smoothed and de-noising have been done using suitable mother wavelet as a pre-requisite. The Finite Variance Scaling Method (FVSM), Higuchi method, rescaled range (R/S) and a generalized method have been applied to calculate the scaling exponents and fractal dimensions of the time series. Autocorrelation function (ACF) is used to find autoregressive (AR) process and Partial autocorrelation function (PACF) has been used to get the order of AR model. Finally a best fit model has been proposed using Yule-Walker Method with supporting results of goodness of fit and wavelet spectrum. The results reveal an anti-persistent, Short Range Dependent (SRD), self-similar property with signatures of non-causality, non-stationarity and nonlinearity in the data series. The model shows the best fit to the data under observation.