Automatic Generation of Artificial Space Weather Forecast Product Based on Sequence-to-sequence Model

Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.

Image Feature Extraction and Matching of Augmented Solar Images in Space Weather

Augmented solar images were used to research the adaptability of four representative image extraction and matching algorithms in space weather domain.These include the scale-invariant feature transform algorithm,speeded-up robust features algorithm,binary robust invariant scalable keypoints algorithm,and oriented fast and rotated brief algorithm.The performance of these algorithms was estimated in terms of matching accuracy,feature point richness,and running time.The experiment result showed that no algorithm achieved high accuracy while keeping low running time,and all algorithms are not suitable for image feature extraction and matching of augmented solar images.To solve this problem,an improved method was proposed by using two-frame matching to utilize the accuracy advantage of the scale-invariant feature transform algorithm and the speed advantage of the oriented fast and rotated brief algorithm.Furthermore,our method and the four representative algorithms were applied to augmented solar images.Our application experiments proved that our method achieved a similar high recognition rate to the scale-invariant feature transform algorithm which is significantly higher than other algorithms.Our method also obtained a similar low running time to the oriented fast and rotated brief algorithm,which is significantly lower than other algorithms.

Overview of the Solar Polar Orbit Telescope Project for Space Weather Mission

The Solar Polar ORbit Telescope(SPORT) project for space weather mission has been under intensive scientific and engineering background studies since it was incorporated into the Chinese Space Science Strategic Pioneer Project in 2011.SPORT is designed to carry a suite of remote-sensing and in-situ instruments to observe Coronal Mass Ejections(CMEs),energetic particles,solar high-latitude magnetism,and the fast solar wind from a polar orbit around the Sun.The first extended view of the polar regions of the Sun and the ecliptic enabled by SPORT will provide a unique opportunity to study CME propagation through the inner heliosphere,and the solar high-latitude magnetism giving rise to eruptions and the fast solar wind.Coordinated observations between SPORT and other spaceborne/ground-based facilities within the International Living With a Star(ILWS) framework can significantly enhance scientific output.SPORT is now competing for official selection and implementation during China's 13 th Five-Year Plan period of 2016-2020.

The effect of space weather on the ionosphere at the 110°meridian during CAWSES-Ⅱperiod

Space weather determines the state of the ionosphere,which is especially important to know during disturbances.To study this state,the period of March 7-17,2012,which was recommended by SCOSTEP for detailed studies and called CAWSES-II,was selected.In this period,the behavior of parameters of the solar wind(SW)and the interplanetary magnetic field(IMF)show a number of features.In this paper,we study their relationship with the total electron content(TEC)and the critical frequency(foF2)of the ionosphere at the 110°meridian,near which several ionosondes are located,in the range of 20°N-62.5°N.The correlation coefficients of TEC and foF2 with the SW and IMF parameters for the month and the selected period are calculated.The ionosphere showed the considered disturbances in different ways in different latitudinal zones:negative anomalies are observed at high latitudes,and positive ones at low latitudes.A distinctive feature is the presence of signs of a super-fountain effect.Deviations of TEC and foF2 from their medians can be significant.The IRI model reacted in the latitude range 40°N-62.5°N in the form of negative anomalies,although positive anomalies were observed in the TEC.At lower latitudes,no reaction was observed.For all factors(F10.7,Dst,Kp,IMF,Np),three zones(high-latitude,midlatitude,and low-latitude)are distinguished for different coefficients.The strongest influence of disturbances on the correlation coefficients is observed in the zone of 37.5°N 62.5°N.

Development of New Capabilities Using Machine Learning for Space Weather Prediction

With the development of space exploration and space environment measurements,the numerous observations of solar,solar wind,and near Earth space environment have been obtained in last 20 years.The accumulation of multiple data makes it possible to better use machine learning technique,which has achieved unforeseen results in industrial applications in last decades,for developing new approaches and models in space weather investigation and prediction.In this paper,the efforts on the forecasting methods for space weather indices,events,and parameters using machine learning are briefly introduced based on the study works in recent years.These investigations indicate that machine learning,especially deep learning technique can be used in automatic characteristic identification,solar eruption prediction,space weather forecasting for solar and geomagnetic indices,and modeling of space environment parameters.

Neutralized solar energetic particles for SEP forecasting:Feasibility study of an innovative technique for space weather applications

Energetic neutral atoms(ENAs)are produced by the neutralization of energetic ions formed by shock-accelerated gradual solar energetic particle events(SEP).These high-energy ENAs(HENAs)can reach the Earth earlier than the associated SEPs and thus can provide information about the SEPs at the lower corona.The HENA properties observed at Earth depend on the properties of the coronal mass ejection(CME)-driven shocks that accelerate the SEPs.Using a model of HENA production in a shock-accelerated SEP event,we semi-quantitatively investigate the energy-time spectrum of HENAs depending on the width,propagation speed,and direction of the shock,as well as the density and ion abundances of the lower corona.Compared to the baseline model parameters,the cases with a wider shock width angle or a higher coronal density would increase the HENA flux observed at the Earth,while the case with an Earthpropagating shock shows a softened HENA spectrum.The comparison of expected HENA fluxes in different cases with a flight-proven ENA instrument suggests that solar HENAs can feasibly be monitored with current technologies,which could provide a lead time of 2−3 hours for SEPs at a few MeV.We propose that monitoring of solar HENAs could provide a new method to forecast shock-driven SEP events that are capable of significant space weather impacts on the near-Earth environment.

Space weather

Very hot and very cold Have you ever wondered how cold it is in space? Well, apparently the vacuum of space has no temperature. But, put an object in space and it is going to experience some extreme temperatures:if left in the sunlight an object can heat up to 260°Celsius, roughly 200 degrees hotter than the hottest place on Earth. In the shade temperatures can drop to-100℃. This is much colder than the coldest places on our planet:Antarctica has an average temperature of-55℃with a record low of-89.2℃. If you want to visit Pluto, don’t forget to pack your space jacket, because it can get as cold as-260°Celsius!

Online computation of International Reference Ionosphere Extended to Plasmasphere(IRI-Plas) model for space weather

Ionosphere is the most challenging part of Space Weather with its spatio-temporal variability and dispersive nature. Ionospheric models are very important in reducing positioning error in GNSS system.International Reference Ionosphere(IRI) is an empirical, deterministic and climatic model of ionosphere up to 2000 km in height. Recently, IRI Extended to Plasmasphere(IRI-Plas) model has been developed to extend the interest region of IRI to the GPS orbital height of 20,000 km. Both IRI and IRI-Plas provide ionospheric parameters such as electron density, electron and ion temperatures according to their height profiles. In order to update the model to current ionospheric conditions, IRI-Plas can input F2 layer critical frequency(foF2), maximum ionization height(hmF2), and also Total Electron Content(TEC).Online IRI-Plas is developed for the ionospheric community to run multiple tasks at various locations,dates and times with optional foF2, hmF2 and TEC inputs in a user-friendly manner. In this paper, we are going to present the capabilities of the Online IRI-Plas service and provide some comparisons between IRI-Plas outputs and ionosonde measurements. The comparison between online IRI-Plas foF2 outputs and ionosonde foF2 measurements indicates that the model with TEC input can significantly improve the representation of the current ionospheric state, which is very successful especially in the geomagnetically disturbed days.

Development of Operational Space Weather Prediction Models

In this report, we summarize the needs of space weather models, and recommend that developing operational prediction models, rather than transitioning from research to operation, is a more feasible and critical way for space weather services in the near future. Operational models for solar wind speed, geomagnetic indices, magnetopause, plasma sheet energetic electrons, inner boundary of ion plasma sheet, energetic electrons in outer radiation belt, and thermospheric density at low Earth orbit, have been developed and will be introduced briefly here. Their applications made a big progress in space weather services during the past two years in China.

Space weathering simulation and spectrum decoding

Visible and near-infrared spectra are routinely used to achieve mineral abundances and mineral chemistry of the global surfaces of the Moon and asteroids.However,these spectra can be significantly modified by space weathering,including micrometeorite impacting,solar wind implanting and cosmic ray irradiation.In this paper we report results of laser-bombarding experiments on the Jilin ordinary chondrite,simulating micrometeorite impacting on the surface of asteroids.After laser bombardment,the spectra became significantly redder and moderately darker. With the Modified Gaussian Model(MGM)method,the absorption band positions of olivine can be decoded from the modified spectra,which are correlated with their fayalite contents.In addition,a continuum of the modified spectra can be decoded,and its slope may be used to depict the degree of space weathering.However,relative strengths of the absorption sub-bands of olivine and pyroxenes show significant variant after the bombardment, hence they cannot be used to estimate the relative abundances of high-Ca to low-Ca pyroxenes of the lunar surface and other matured surfaces of asteroids.

Space Weather Service for Chinese Space Science Satellites

Strategic Priority Research Program on Space Science has gained remarkable achievements. Space Environment Prediction Center(SEPC) affiliated with the National Space Science Center(NSSC) has been providing space weather services and helps secure space missions. Presently, SEPC is capable to offer a variety of space weather services covering many phases of space science missions including planning, design, launch,and orbital operation. The service packages consist of space weather forecasts, warnings, and effect analysis that can be utilized to avoid potential space weather hazard or reduce the damage caused by space storms,space radiation exposure for example. Extensive solar storms that occurred over Chinese Ghost Festival(CGF)in September 2017 led to a large enhancement of the solar energetic particle flux at 1 AU, which affected the near Earth radiation environment and brought great threat to orbiting satellites. Based on the space weather service by SEPC, satellite ground support groups collaborating with the space Tracking, Telemetering and Command system(TT&C) team were able to take immediate measures to react to the CGF solar storm event.

Influence of Fast Global Variations of Solar Magnetic Fields on Space Weather in Cycle 23

It is established that the large-scale and global magnetic fields in the Sun's atmosphere do not change smoothly, and long-lasting periods of gradual variations are superseded by fast structural changes of the global magnetic field. Periods of fast global changes on the Sun are accompanied by anomalous manifestations in the interplanetary space and in the geomagnetic field. There is a regular recurrence of these periods in each cycle of solar activity, and the periods are characterized by enhanced flaring activity that reflects fast changes in magnetic structures. Is demonstrated, that the fast changes have essential influencing on a condition of space weather, as most strong geophysical disturbances are connected to sporadic phenomena on the Sun. An explanation has been offered for the origin of anomalous geomagnetic disturbances that are unidentifiable in traditionally used solar activity indices. Is shown, main physical mechanism that leads to fast variations of the magnetic fields in the Sun's atmosphere is the reconnection process.

Radio Heliographic Diagnostics of Solar Activity That Governs Space Weather

In this paper, the possibility and some results of radioheliographic study of space weather solar factors are shortly described.

Influence and hazard of disastrous space weather on power grid in China

Based on the measured data of geomagnetically induced currents(GIC) in Guangdong Ling'ao 500 kV power networks during several magnetic storms at the peak years of 23rd Solar Cycle,the GIC calculation results of 750 kV planning power grid in Shanxi,Gansu,Qinghai and Ningxia,the structure and characteristics of power networks from 500 kV to 1 000 kV,and super magnetic storm in 1859 are analyzed in this paper. Through the analysis,the possible impacts of extreme space weather on the future ultra-high voltage(UHV) grid,the security of large-scale power system in China are expounded,and the research suggestions coping with the strong solar storms are proposed.

Observations of the first meteorological rocket of the Meridian Space Weather Monitoring Project

On June 3,2010,the first meteorological rocket of the Meridian Space Weather Monitoring Project was successfully launched at the Hainan rocket launch site(19.5°N),China.This paper analyzes the vertical profiles of atmospheric temperature and wind recorded by the rocket and its supportive balloons,and investigates wind shear,gravity waves and atmospheric stability.In addition,we compare the vertical profiles of atmospheric temperature and wind with SABER/TIMED temperature measurements and the modeling results of MSIS00 and HWM07.

Mapping of ionospheric parameters for space weather predictions: A concise review

Reviewing briefly the recent progress in a joint program of specifying the polar ionosphere primarily on the basis of ground magnetometer data, this paper em-phasizes the importance of processing data from around the world in real time for space weather predictions. The output parameters from the program include ionospheric electric fields and currents and field-aligned currents. These real-time records are essential for running computer simulations under realistic boundary conditions and thus for making numerical predictions of space weather efficient as reliable as possible. Data from individual ground magnetometers as well as from the solar wind are collected and are used as input for the KRM and AMIE mag-netogram-inversion algorithms, through which the two-dimensional distribution of the ionospheric parameters is calculated. One of the goals of the program is to specify the solar-terrestrial environment in terms of ionospheric processes and to provide the scientific community with more than what geomagnetic activity indices and statistical models indicate.

南极长城站哨声波监测仪设备及其初步观测

在子午工程二期项目的支持下,武汉大学(Wuhan University,WHU)联合中国极地研究中心研制了一套甚低频(very low frequency,VLF)波动探测系统,并在2022年由中国极地研究中心部署于南极洲的中国长城站(Great Wall Station,GWS,62.22°S,58.96°W).该探测系统的动态范围为~110 dB,时间精度为~100 ns,可为空间物理和空间天气研究提供高分辨率的波动观测数据.本文详细介绍了WHU VLF(子午工程编码:OCHCH_WHWM01)波动探测系统在GWS的初步观测结果,充分验证了系统的优越性能和稳定性.在过去一年的常规运行中,此系统能精确探测北美和欧洲等区域内各种地基VLF台站信号的动态变化.初步分析结果表明,在多次X级太阳耀斑爆发期间,GWS观测到的人工VLF台站信号特性与以往的研究结果高度一致.由于HWU-GWS(HWU为发射台站的名称)路径穿过南大西洋异常(south Atlantic anomaly,SAA)区域,观测结果同时表明,在磁暴期间,HWU VLF信号的扰动与磁层电子沉降在时空关系上具有很强的关联性.此外,此设备也能观测到闪电激发的宽频带哨声波,在频谱图上呈现特有的清晰色散结构.因此,在南极独特的地理位置,地基哨声波监测仪的观测结合其它仪器的观测,有利于深入开展与极区哨声波传播、低电离层扰动、地面闪电放电和辐射带粒子沉降等相关的空间天气学研究,对开展全天时空间环境监测具有重要意义.

Cost-Efficient Medium Frequency Propagation Research with Software Defined Radio

Medium Frequency radio holds significance in modern society as it supports broadcasting and individual communications in the public, government, and military sectors. Enhancing the availability and quality of these communications is only possible by enhancing the understanding of medium frequency propagation. While traditional methods of radio wave propagation research can have a high material demand and cost, software defined radio presents itself as a versatile and low-cost platform for medium frequency signal reception and data acquisition. This paper details a research effort that utilizes software defined radio to help characterize medium frequency signal strength in relation to ionospheric and solar weather propagation determinants. Signal strength data from seven medium frequency stations of unique transmission locations and varying transmission powers were retrieved in 24-hour segments via a receiving loop antenna, Airspy HF+ Discovery software defined radio, and SDR Sharp software interface network. Retrieved data sets were visualized and analyzed in MATLAB for the identification of signal strength trends, which were subsequently compared to historical ionospheric and space weather indices in pursuit of a quantifiable correlation between such indices and medium frequency signal strengths. The results of the investigation prove that software defined radio, when used in conjunction with a receiving antenna and data analysis program, provides a versatile mechanism for cost-efficient propagation research.

Metallurgical performance evaluation of space-weathered Chang’e-5 lunar soil

Space metallurgy is an interdisciplinary field that combines planetary space science and metallurgical engineering.It involves systematic and theoretical engineering technology for utilizing planetary resources in situ.However,space metallurgy on the Moon is challenging because the lunar surface has experienced space weathering due to the lack of atmosphere and magnetic field,making the mi-crostructure of lunar soil differ from that of minerals on the Earth.In this study,scanning electron microscopy and transmission electron microscopy analyses were performed on Chang’e-5 powder lunar soil samples.The microstructural characteristics of the lunar soil may drastically change its metallurgical performance.The main special structure of lunar soil minerals include the nanophase iron formed by the impact of micrometeorites,the amorphous layer caused by solar wind injection,and radiation tracks modified by high-energy particle rays inside mineral crystals.The nanophase iron presents a wide distribution,which may have a great impact on the electromagnetic prop-erties of lunar soil.Hydrogen ions injected by solar wind may promote the hydrogen reduction process.The widely distributed amorph-ous layer and impact glass can promote the melting and diffusion process of lunar soil.Therefore,although high-energy events on the lun-ar surface transform the lunar soil,they also increase the chemical activity of the lunar soil.This is a property that earth samples and tradi-tional simulated lunar soil lack.The application of space metallurgy requires comprehensive consideration of the unique physical and chemical properties of lunar soil.

A planetary perspective on Earth's space environment evolution

The planet Earth is an integrated system, in which its multi-spheres are coupled, from the space to the inner core. Whether the space environment in short to long terms has been controlled by the earth's interior process is contentious. In the past several decades,space weather and space climate have been extensively studied based on either observation data measured directly by man-made instruments or ancient data inferred indirectly from some historical medium of past thousands of years. The acquired knowledge greatly helps us to understand the dynamic processes in the space environment of modern Earth, which has a strong magnetic dipole and an oxygen-rich atmosphere. However, no data is available for ancient space weather and climate(>5 ka). Here, we propose to take the advantage of " space-diversity" to build a " generalized planetary space family", to reconcile the ancient space environment evolution of planet Earth from modern observations of other planets in our solar system. Such a method could also in turn give us a valuable insight into other planets' evolution.