Impact of heliogeophysical disturbances on ionospheric HF channels

The article presents the results of the observation of a strong magnetic storm and two X-ray flares during the summer solstice in 2015, and their impact on the HF signals characteristics in ionospheric oblique sounding. It was found that the negative phase of the magnetic storm led to a strong degradation of the ionospheric channel, ultimately causing a long blackout on paths adjacent to subauroral latitudes. On mid-latitude paths, the decrease in 1FMOF reached ～50% relative to the average values for the quiet ionosphere. It is shown that the propagation conditions via the sporadic Es layer during the magnetic storm on a subauroral path are substantially better than those for F-mode propagation via the upper ionosphere. The delay of the sharp decrease in 1FMOF during the main phase of the magnetic storm allowed us to determine the propagation velocity of the negative phase disturbances (～100 m/s) from subauroral to mid-latitude ionosphere along two paths: Lovozero – Yoshkar-Ola and Cyprus – Nizhny Novgorod. It is shown that both the LOF and the signal/noise ratio averaged over the frequency band corresponding to the propagation mode via the sporadic Es layer correlate well with the auroral AE index. Using an over-the-horizon chirp radar with a bistatic configuration on the Cyprus – Rostov-on-Don path, we located small-scale scattering irregularities responsible for abnormal signals in the region of the equatorial boundary of the auroral oval.     

Fostering research aptitude among high school students through space weather competition

Cultivating research culture at an early stage is important for capacity building in a community. The high school level is the appropriate stage for research to be introduced because of students’ competitive nature. Participation in the space weather competition is one of the ways in which research aptitude can be fostered in high school students in Malaysia. Accordingly, this paper presents how research elements were introduced to the students at the high school level through their participation in the space weather competition. The competition required the students to build a system to detect the presence of solar flares by utilizing VLF signals reflected from the ionosphere. The space weather competition started off with proposal writing for the space weather related project where the students were required to execute extensive literature review on the given topic. Additionally, the students were also required to conduct the experiments and analyse the data. Results obtained from data analysis were then validated by the students through various other observations that they had to carry out. At the end of the competition, students were expected to write a comprehensive technical report. Through this competition, the students learnt how to conduct research in accordance to the guidelines provided through the step by step approach exposed to them. Ultimately, this project revealed that the students were able to conduct research on their own with minimal guidance and that participation in the competition not only generated enjoyment in learning but also their interest in science and research.     

The automated prediction of solar flares from SDO images using deep learning

In the last few years, there has been growing interest in near-real-time solar data processing, especially for space weather applications. This is due to space weather impacts on both space-borne and ground-based systems, and industries, which subsequently impacts our lives. In the current study, the deep learning approach is used to establish an automated hybrid computer system for a short-term forecast; it is achieved by using the complexity level of the sunspot group on SDO/HMI Intensitygram images. Furthermore, this suggested system can generate the forecast for solar flare occurrences within the following 24 h. The input data for the proposed system are SDO/HMI full-disk Intensitygram images and SDO/HMI full-disk magnetogram images. System outputs are the “Flare or Non-Flare” of daily flare occurrences (C, M, and X classes). This system integrates an image processing system to automatically detect sunspot groups on SDO/HMI Intensitygram images using active-region data extracted from SDO/HMI magnetogram images (presented by Colak and Qahwaji, 2008) and deep learning to generate these forecasts. Our deep learning-based system is designed to analyze sunspot groups on the solar disk to predict whether this sunspot group is capable of releasing a significant flare or not. Our system introduced in this work is called ASAP_Deep. The deep learning model used in our system is based on the integration of the Convolutional Neural Network (CNN) and Softmax classifier to extract special features from the sunspot group images detected from SDO/HMI (Intensitygram and magnetogram) images. Furthermore, a CNN training scheme based on the integration of a back-propagation algorithm and a mini-batch AdaGrad optimization method is suggested for weight updates and to modify learning rates, respectively. The images of the sunspot regions are cropped automatically by the imaging system and processed using deep learning rules to provide near real-time predictions. The major results of this study are as follows. Firstly, the ASAP_Deep system builds on the ASAP system introduced in Colak and Qahwaji (2009) but improves the system with an updated deep learning-based prediction capability. Secondly, we successfully apply CNN to the sunspot group image without any pre-processing or feature extraction. Thirdly, our system results are considerably better, especially for the false alarm ratio (FAR); this reduces the losses resulting from the protection measures applied by companies. Also, the proposed system achieves a relatively high scores for True Skill Statistics (TSS) and Heidke Skill Score (HSS).     

A tentative statistical analysis of flare events observed by NoRH and NoRP

In this paper, we report the statistical analysis of flare events observed by NoRH during 1992–2005 and NoRP during 1994–2005. We give the power law indices for the frequency distribution of peak brightness temperature which is 1.87 ± 0.05 for 17 GHz observation and is 1.64 ± 0.04 for 34 GHz observation. We also present the frequency variation of power law indices for peak flux and total energy of flare for NoRP observation, which is mono-increasing from 1 to 17 GHz.     

耀斑后环珥系速度场的定量研究

本文研究了在太阳重力、偶极磁压强梯度和气体压力梯度联合作用下环珥系内物质的下落运动,并在等温、定常假设下用数值方法计算了该环系的二维视向速度场。通过将速度场的理论计算跟文[1]中给出的观测速度场拟合,导出了该环系的有关参数及分布。计算表明环系内物质密度和磁场强度对物质下落运动影响较显著。     

Physics of ion acceleration in the solar flare on 2005 September 7 determines γ-ray and neutron production

Relativistic neutrons were observed by the neutron monitors at Mt. Chacaltaya and Mexico City and by the solar neutron telescopes at Chacaltaya and Mt. Sierra Negra in association with an X17.0 flare on 2005 September 7. The neutron signal continued for more than 20 min with high statistical significance. Intense emissions of γ-rays were also registered by INTEGRAL, and during the decay phase by RHESSI. We analyzed these data using the solar-flare magnetic-loop transport and interaction model of Hua et al. [Hua, X.-M., Kozlovsky, B., Lingenfelter, R.E. et al. Angular and energy-dependent neutron emission from solar flare magnetic loops, Astrophys. J. Suppl. Ser. 140, 563–579, 2002], and found that the model could successfully fit the data with intermediate values of loop magnetic convergence and pitch-angle scattering parameters. These results indicate that solar neutrons were produced at the same time as the γ-ray line emission and that ions were continuously accelerated at the emission site.     

Correlation between solar flare productivity and photospheric vector magnetic fields

Studying the statistical correlation between the solar flare productivity and photospheric magnetic fields is very important and necessary. It is helpful to set up a practical flare forecast model based on magnetic properties and improve the physical understanding of solar flare eruptions. In the previous study ([Cui, Y.M., Li, R., Zhang, L.Y., He, Y.L., Wang, H.N. Correlation between solar flare productivity and photospheric magnetic field properties 1. Maximum horizontal gradient, length of neutral line, number of singular points. Sol. Phys. 237, 45–59, 2006]; from now on we refer to this paper as ‘Paper I’), three measures of the maximum horizontal gradient, the length of the neutral line, and the number of singular points are computed from 23990 SOHO/MDI longitudinal magnetograms. The statistical relationship between the solar flare productivity and these three measures is well fitted with sigmoid functions. In the current work, the three measures of the length of strong-shear neutral line, total unsigned current, and total unsigned current helicity are computed from 1353 vector magnetograms observed at Huairou Solar Observing Station. The relationship between the solar flare productivity and the current three measures can also be well fitted with sigmoid functions. These results are expected to be beneficial to future operational flare forecasting models.     

太阳耀斑的行星引潮力触发

阐述了太阳潮波动力学的概况，依据实际资料的统计结果指出；行星引潮力触发耀斑的效应随耀斑级别的增大而增强；对于3级及其以上耀斑，强潮汐触发较之弱触发的耀斑产出率之比高达9.33；这个重要事实在预报地球和日地空间灾害性扰动方面，会有相当大的实际价值。     

Radio Diagnostics of the Solar Flare Reconnection

First, high-frequency (HF) slowly drifting pulsating structures are interpreted as radio emissions of electron beams accelerated in the magnetic reconnection volume and injected into magnetic islands (plasmoids). Then, the time evolution of plasma parameters (density, magnetic field, etc.) in a 2-D MHD model of solar flare reconnection is computed numerically. Assuming plasma radio emission from locations where the “double-resonance’’ instability generates upper-hybrid (UH) waves due to unstable distribution function of suprathermal electrons, the radio spectra and spatial source structures in the reconnection region are modeled. By comparison of the modeled and observed spectra a remarkable similarity has been found between the computed narrow-band emission and the observed lace bursts. Finally, a new diagnostics of the reconnection process is proposed.