Connection between winter mesopause region temperatures and diurnal LF reflection height variations measured at Collm

Scale height, H, estimates are calculated from the decrease/increase of ionospheric virtual reflection heights of low-frequency (LF) radio waves at oblique incidence in suitably defined morning intervals around sunrise during winter months. The day-to-day variations of H qualitatively agree with daily mean temperature variations around 90 km from meteor radar measurements. Since mesospheric long-period temperature variations are generally accepted to be the signature of atmospheric planetary waves, this shows that LF reflection height measurements can be used for monitoring the dynamics of the upper middle atmosphere. The long-term variations of monthly mean H estimates have also been analysed. There is no significant trend, which is in agreement with other measurements of mesopause region temperature trends.     

Forecast of recurrent geomagnetic storms

Long-term forecast of space weather allows in achieving a longer lead time for taking the necessary precautions against disturbances. Hence, there is a need for long-term forecasting of space weather. We studied the possibility for a long-term forecast of recurrent geomagnetic storms. Geomagnetic storms recur with an approximate 27-day period during the declining phase of a solar cycle. These disturbances are caused by the passage of corotating interaction regions, which are formed by interactions between the background slow-speed solar wind and high-speed solar wind streams from a coronal hole. In this study, we report on the performance of 27-day-ahead forecasts of the recurrent geomagnetic disturbances using Kp index. The methods of the forecasts are on the basis of persistence, autoregressive model, and categorical forecast using occurrence probability. The forecasts show better performance during the declining phase of a solar cycle than other phases. The categorical forecast shows the probability of detection (POD) more than 0.5 during the declining phase. Transition of the performance occurs sharply among the declining phases and other phases.     

军用无人机技术的发展现状及未来趋势

作为一种多用途、低费效比的航空武器装备,军用无人机日益受到世界各国军方的重视.本文分析了现役和即将服役军用无人机的技术水平及应用特点,并对军用无人机的发展趋势进行了展望.     

Behavior of F2-layer parameters and solar activity indices in the 24th cycle

The analysis of the behavior of the critical frequency foF2 during the 24th solar activity cycle (Danilov and Konstantinova, 2020a, c) is prolonged for two more months and the nighttime hours. In addition to the Rz and Ly-α indices used in the aforementioned papers for correction of the F10.7 index during the 24th cycle, the commonly used Mg II index is added. The results confirm the previous conclusions on the existence of the “vague” period with chaotic behavior of foF2 and the recovery of the negative trend in foF2 after 2008–2010. A comparison of the F10.7 index with three other SA indices (Ly-α, Rz, and Mg II) for the 22nd, 23rd, and 24th SA cycles is performed. It is shown that the relationship between F10.7 and other indices is close in the 22nd and 23rd cycles but differs from that in the 24th cycle. The corrected values of F10.7 in the 24th cycle are proposed for analysis of ionospheric trends during that cycle.     

Monitoring of long-term land subsidence from 2003 to 2017 in coastal area of Semarang,Indonesia by SBAS DInSAR analyses using Envisat-ASAR,ALOS-PALSAR,and Sentinel-1A SAR data

Land subsidence is a critical issue that large cities located in coastal areas, such as Semarang, Indonesia, must address. The monitoring of land subsidence is vital for predicting and mitigating the disasters that such subsidence may cause. Therefore, an economical and effective monitoring method, which can continuously provide accurate measurements over extensive areas, is highly required. Differential Interferometry Synthetic Aperture Radar (DInSAR) has the potential to be a powerful technique that can meet the above demands. Actually, DInSAR has been applied to monitor the subsidence in Semarang, but it was for a limited period before 2012.In order to clarify the transition of the long-term subsidence behavior in Semarang, the Small Baseline Subset (SBAS) method, which is one type of time-series DInSAR, is employed in this research. The sets of data of Envisat-ASAR (2003–2007), ALOS-PALSAR (2007–2011), and Sentinel-1A (2015–2017) are employed for the analyses. Then, the validity of the SBAS results is discussed from the viewpoints of both spatial distribution and temporal transition using GPS displacement measurement results and the geological conditions of the ground.On the other hand, as the lifespan of SAR satellites is commonly designed to be around 5–7?years, an appropriate method, which can connect the subsidence provided independently by the unlinked time-series data sets of the three different SAR satellite data, is required. This study uses the Hyperbolic Method (HM) to connect the above unlinked SBAS results. The HM is often used to fit the monitored subsidence in practice as a geotechnical engineering tool. Using this method, 14?years of the temporal behavior of the subsidence in Semarang is evaluated.It is found that the transition of the subsidence is different depending on the location, and that the subsidence rate is still increasing in the north and northeast parts of the coastal area. This study shows that SBAS DInSAR can be a useful tool for long-term continuous subsidence monitoring.     

Improved model of ionosphere variability and study for long-term statistical characteristics

Ionospheric variability is influenced by many factors, such as solar radiation, neutral atmosphere composition, and geomagnetic disturbances. Mainly characterized by the total electron content (TEC) and electron density, the climatology of the ionosphere features temporal and spatial changes. Establishing a multivariant regression model helps substantially in better understanding the ionosphere characteristics and their long-term variability. In this paper, an improvement of the existing ionosphere multivariate linear fitting regression model is proposed and investigated using data from both the ionosonde and the global ionosphere map (GIM) derived from ground-based Global Navigation Satellite System (GNSS) observations. The proposed method gives more consideration to the impact of the solar activity and adds modeling of the annual periodic fluctuations and half-year periodic fluctuations for the F10.7 index. The improved model is verified to have a better correlation with the real observations and can help reduce the calculation uncertainty. Moreover, the proposed model is used to evaluate the fitting accuracy of the GIMs produced by five authorized data analysis centers from the International GNSS Service (IGS). The results show that there is a fixing hole in the North America region for the GIM model where the correlation between the GIM and the proposed model always returns lower values compared to other places.     

美国导弹防御系统发展及对国际军控影响研究

大力推进导弹防御系统(MD)的研制和部署是美谋求绝对优势的重要举措。系统分析了美国导弹防御系统(BMDS)发展的基本态势和未来走向,以及其对国际军备控制的影响。     

Global dynamics of high area-to-mass ratios GEO space debris by means of the MEGNO indicator

In this paper we provide an extensive analysis of the global dynamics of high-area-to-mass ratios geosynchronous (GEO) space debris, applying a recent technique developed by Cincotta and Simó [Cincotta, P.M., Simó, C.Simple tools to study global dynamics in non-axisymmetric galactic potentials–I. Astron. Astrophys. (147), 205–228, 2000.], Mean Exponential Growth factor of Nearby Orbits (MEGNO), which provides an efficient tool to investigate both regular and chaotic components of the phase space.