Space Weather最新文献_第10页

Modeling “Wrong Side” Failures Caused by Geomagnetically Induced Currents in Electrified Railway Signaling Systems in the UK 英国电气化铁路信号系统地磁诱导电流导致的 "错边 "故障建模

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-11 DOI: 10.1029/2023sw003625

C. J. Patterson, J. A. Wild, D. H. Boteler

{"title":"Modeling “Wrong Side” Failures Caused by Geomagnetically Induced Currents in Electrified Railway Signaling Systems in the UK","authors":"C. J. Patterson, J. A. Wild, D. H. Boteler","doi":"10.1029/2023sw003625","DOIUrl":"https://doi.org/10.1029/2023sw003625","url":null,"abstract":"The majority of studies into space weather impacts on ground-based systems focus on power supply networks and oil and gas pipelines. The effects on railway signaling infrastructure remain a sparsely covered aspect even though these systems are known to have experienced adverse effects in the past as a result of geomagnetic activity. This study extends recent modeling of geomagnetic effects on DC signaling for AC-electrified railways in the UK that analyzed “right side” failures in which green signals are turned to red. The extended model reported here allows the study of “wrong side” failures where red signals are turned green: a failure mode that is potentially more dangerous. Railway lines using track circuit signaling, like those modeled in this study, are separated into a number of individual blocks. This study shows that a relay is most susceptible to “wrong side” failure when a train is at the end of a track circuit block. Assuming that each train is positioned at the end of the block it is occupying, the results show that the geoelectric field threshold at which “wrong side” failures can occur is lower than for “right side” failures. This misoperation field level occurs on a timescale of once every 10 or 20 years. We also show that the estimated electric field caused by a 1-in-100 years event could cause a significant number of “wrong side” failures at multiple points along the railway lines studied, although this depends on the number of trains on the line at that time.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"21 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138569678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating Geomagnetically Induced Currents in High-Voltage Power Lines for the Territory of Kazakhstan 估算哈萨克斯坦境内高压电线的地磁诱导电流

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-08 DOI: 10.1029/2023sw003639

A. B. Andreyev, S. N. Mukasheva, V. I. Kapytin, O. I. Sokolova

{"title":"Estimating Geomagnetically Induced Currents in High-Voltage Power Lines for the Territory of Kazakhstan","authors":"A. B. Andreyev, S. N. Mukasheva, V. I. Kapytin, O. I. Sokolova","doi":"10.1029/2023sw003639","DOIUrl":"https://doi.org/10.1029/2023sw003639","url":null,"abstract":"Extreme solar events, such as powerful solar flares are accompanied by the release of strong solar disturbances, such as coronal mass ejections (CMEs). The impact of CMEs on the Earth's magnetosphere causes geomagnetic storms, which trigger geomagnetic effects measurable in the ionosphere, upper atmosphere, and on and in the ground. During extreme cases, rapidly changing geomagnetic fields generate intense geomagnetically induced currents (GICs), which can cause dramatic effects on man-made technological systems, including transmission lines and pipelines. In countries with large territories such as Kazakhstan, long power lines contribute to high values of induced currents during periods of extreme geoeffective solar events. It is of interest to estimate the values of GICs in an extensive network of power lines on the territory of Kazakhstan. However, there are no estimations of induced currents in power lines in Kazakhstan, and most estimation techniques are made difficult because of absence of field measurements of Earth conductivity. This study aims to model geoelectric fields on the surface of the Earth for Kazakhstan and to estimate the values of the GICs in 500 kV power lines. This study also compares between two methods for calculating induced voltages in power lines: one based on linear paths and the other based on curvilinear paths between substations of transmission power lines.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"1 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138562114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Analysis of a Strong Constraint 4DVar and 4DEnVar on Regional Ionosphere Imaging 区域电离层成像的强约束 4DVar 和 4DEnVar 性能分析

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-08 DOI: 10.1029/2023sw003584

Nicholas Ssessanga, Wojciech Jacek Miloch, Lasse Boy Novock Clausen, Daria Kotova

{"title":"Performance Analysis of a Strong Constraint 4DVar and 4DEnVar on Regional Ionosphere Imaging","authors":"Nicholas Ssessanga, Wojciech Jacek Miloch, Lasse Boy Novock Clausen, Daria Kotova","doi":"10.1029/2023sw003584","DOIUrl":"https://doi.org/10.1029/2023sw003584","url":null,"abstract":"Data assimilation (DA) techniques have recently gained traction in the ionospheric community, particularly at regional operational centers where more precise data are becoming prevalent. At center stage is the argument over which technique or scheme merits realization. At 4DSpace, we have in-house developed and assessed the performance of two regional flavors of short-term forecast strong constraint four-dimensional (4D, space and time) variational (SC4DVar) DA schemes; the orthodox incremental (SC4DVar-Inc) and ensemble-based (SC4DEnVar) approach. SC4DVar-Inc is bottled-necked by expensive Tangent Linear Models (TLMs) and model Ad-joints (MAs), while SC4DEnVar design mitigates these limitations. Both schemes initialize from the same background (IRI-2016), and electron densities forward propagated (30-min) by a Gauss Markov filter- the densities take on a log-normal distribution to assert the mandatory ionosphere density positive definiteness. Preliminary assimilation is performed only with ubiquitous Global Navigation Satellite System observables from ground-based receivers, with a focus on moderately stable mid-latitudes, specifically the Japanese archipelago and neighboring areas. Using a simulation analysis, we find that under model space localization, 30 member Ensembles are sufficient for regional SC4DEnVar. Verification of reconstructions is with independent observations from ground-based ionosonde and satellite radio occultations: the performance of both schemes is fairly adequate during the quiet period when the background has a better estimation of the hmF2. SC4DVar-Inc is slightly better over areas densely populated with measurements, but SC4DEnVar estimates the overall 3D ionosphere picture better, particularly in remote areas and during severe conditions. These results warrant SC4DEnVar as a better candidate for precise short-time regional forecasts.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"40 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138566285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Occurrence of Large Geomagnetically Induced Currents Within the EPRI SUNBURST Monitoring Network 在 EPRI SUNBURST 监测网络内出现的大型地磁诱导电流

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-08 DOI: 10.1029/2023sw003532

Chigomezyo M. Ngwira, Robert Arritt, Charles Perry, James M. Weygand, Rishi Sharma

{"title":"Occurrence of Large Geomagnetically Induced Currents Within the EPRI SUNBURST Monitoring Network","authors":"Chigomezyo M. Ngwira, Robert Arritt, Charles Perry, James M. Weygand, Rishi Sharma","doi":"10.1029/2023sw003532","DOIUrl":"https://doi.org/10.1029/2023sw003532","url":null,"abstract":"Space weather, a natural hazard, can adversely impact human technological assets. High-voltage electric power transmission grids constitute one of the most critical technological systems vulnerable to space weather driven geomagnetically induced currents (GICs). One of the major challenges pertaining to the study of GICs over the continental United States has been the availability of GIC measurements, which are critical for validation of geoelectric field and power flow models, for example. In this study, we analyze GIC measurements collected at 17 Electrical Power Research Institute (EPRI) SUNBURST transformer locations across the United States for which a GIC value of 10 A or greater was recorded. This data set includes 52 individual geomagnetic storms with Kp index 6 and above during the period from 2010 to 2021. The analysis confirms that there is a good correlation between the number of geomagnetic storms per year and the number of recorded GIC events. Our results also show that about 76% of the top 17 GIC events are associated with the storm main phase, while only 24% are attributed to storm sudden commencements. In addition, it is shown, for the first time, that mid-latitude positive bays can cause large GICs over the continental United States. Finally, this study shows that the largest measured GIC event in the data set was associated with a localized intense dB/dt structure, which could be attributed to substorm activity.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"1 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138562270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Empirical Model of Ionospheric Total Electron Content Based on Tide-Like Signature Modeling 基于潮汐样特征建模的电离层总电子含量经验模型

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-07 DOI: 10.1029/2023sw003564

Haibing Ruan, Jiuhou Lei, Jianyong Lu, Fen Tang

{"title":"An Empirical Model of Ionospheric Total Electron Content Based on Tide-Like Signature Modeling","authors":"Haibing Ruan, Jiuhou Lei, Jianyong Lu, Fen Tang","doi":"10.1029/2023sw003564","DOIUrl":"https://doi.org/10.1029/2023sw003564","url":null,"abstract":"Accurate modeling of the total electron content (TEC) benefits scientific research and practical application. In this study, the global ionospheric maps from the Center for Orbit Determination of Europe (CODE) covering the years 2000–2021 are utilized to develop an empirical model of TEC by superposing the tide-like components in the ionosphere. The tide-like components, including the migrating and non-migrating ones, are first derived from the daily CODE TEC data. Then, the sine and cosine components of a tide-like signature are separately decomposed into the basic modes as a function of the modified inclination latitude with the principle component analysis, and the temporal evolution is regressed to the solar radiation dependence and interannual variation. As such, the climatological behavior of tidal amplitudes and phases could be well parameterized, and the developed model is capable of reproducing the global TEC patterns. The modeled TEC agrees well with the CODE input data with zero systematic error and a low root mean square error of 3.849 TECu, demonstrating a good model performance. This developed model, associated with the parametric tide-like signatures, could serve as a background for future investigations of the ionospheric responses to the forcing from below or above.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"29 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138561752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of Global Ionospheric Total Electron Content (TEC) Based on SAM-ConvLSTM Model 基于 SAM-ConvLSTM 模型的全球电离层总电子含量 (TEC) 预测

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-07 DOI: 10.1029/2023sw003707

Hanze Luo, Yingkui Gong, Si Chen, Cheng Yu, Guang Yang, Fengzheng Yu, Ziyue Hu, Xiangwei Tian

{"title":"Prediction of Global Ionospheric Total Electron Content (TEC) Based on SAM-ConvLSTM Model","authors":"Hanze Luo, Yingkui Gong, Si Chen, Cheng Yu, Guang Yang, Fengzheng Yu, Ziyue Hu, Xiangwei Tian","doi":"10.1029/2023sw003707","DOIUrl":"https://doi.org/10.1029/2023sw003707","url":null,"abstract":"This paper first applies a prediction model based on self-attention memory ConvLSTM (SAM-ConvLSTM) to predict the global ionospheric total electron content (TEC) maps with up to 1 day of lead time. We choose the global ionospheric TEC maps released by the Center for Orbit Determination in Europe (CODE) as the training data set covering the period from 1999 to 2022. Besides that, we put several space environment data as additional multivariate-features into the framework of the prediction model to enhance its forecasting ability. In order to confirm the efficiency of the proposed model, the other two prediction models based on convolutional long short-term memory (LSTM) are used for comparison. The three models are trained and evaluated on the same data set. Results show that the proposed SAM-ConvLSTM prediction model performs more accurately than the other two models, and more stably under space weather events. In order to assess the generalization capabilities of the proposed model amidst severe space weather occurrences, we selected the period of 22–25 April 2023, characterized by a potent geomagnetic storm, for experimental validation. Subsequently, we employed the 1-day predicted global TEC products from the Center for Operational Products and Services (COPG) and the SAM-ConvLSTM model to evaluate their respective forecasting prowess. The results show that the SAM-ConvLSTM prediction model achieves lower prediction error. In one word, the ionospheric TEC prediction model proposed in this paper can establish the ionosphere TEC of spatio-temporal data association for a long time, and realize high precision of prediction performance.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"72 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138566273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting Equatorial Ionospheric Convective Instability Using Machine Learning 利用机器学习预测赤道电离层对流不稳定性

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-06 DOI: 10.1029/2023sw003505

D. Garcia, E. L. Rojas, D. L. Hysell

引用次数: 0

Topside Electron Density Modeling Using Neural Network and Empirical Model Predictions 利用神经网络和经验模型预测进行顶层电子密度建模

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-01 DOI: 10.1029/2023sw003501

S. Dutta, M. Cohen

{"title":"Topside Electron Density Modeling Using Neural Network and Empirical Model Predictions","authors":"S. Dutta, M. Cohen","doi":"10.1029/2023sw003501","DOIUrl":"https://doi.org/10.1029/2023sw003501","url":null,"abstract":"We model the electron density in the topside of the ionosphere with an improved machine learning (ML) model and compare it to existing empirical models, specifically the International Reference Ionosphere (IRI) and the Empirical‐Canadian High Arctic Ionospheric Model (E‐CHAIM). In prior work, an artificial neural network (NN) was developed and trained on two solar cycles worth of Defense Meteorological Satellite Program data (113 satellite‐years), along with global drivers and indices to predict topside electron density. In this paper, we highlight improvements made to this NN, and present a detailed comparison of the new model to E‐CHAIM and IRI as a function of location, geomagnetic condition, time of year, and solar local time. We discuss precision and accuracy metrics to better understand model strengths and weaknesses. The updated neural network shows improved mid‐latitude performance with absolute errors lower than the IRI by 2.5 × 109 to 2.5 × 1010 e−/m3, modestly improved performance in disturbed geomagnetic conditions with absolute errors reduced by about 2.5 × 109 e−/m3 at high Kp compared to the IRI, and high Kp percentage errors reduced by >50% when compared to E‐CHAIM.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"210 9","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139022210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction 基于表面理论的区域电离层 TEC 预测高精度空间重构方法

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-12-01 DOI: 10.1029/2023sw003663

Jian Wang, Yi‐ran Liu, Yanmei Shi

{"title":"A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction","authors":"Jian Wang, Yi‐ran Liu, Yanmei Shi","doi":"10.1029/2023sw003663","DOIUrl":"https://doi.org/10.1029/2023sw003663","url":null,"abstract":"In order to achieve more accurate spatial reconstruction of ionospheric total electron content (TEC) and promote improved satellite positioning and ranging applications, a high accuracy spatial reconstruction (HASR) method for TEC is proposed based on the surface theory. The core theory of this method is as follows: (a) Any surface can be uniquely determined by its first and second fundamental quantities; (b) By direct difference approximation, differential equations are transformed into algebraic equations to solve Gauss equations faster. At the same time, taking parts of Europe as an example, the proposed HASR method is used to determine the correlation coefficients and the number of iterations of the model by using the relative root mean square error (RRMSE) as the evaluation criterion. The statistical results show that the TEC predicted by the HASR method is highly consistent with the actual observed values of ionospheric observation stations, and the prediction RRMSE is 9.75%. Compared with the Kriging interpolation with scale factor, the prediction accuracy of the HASR method is improved by 8.5%. We hope this method can provide ideas for the spatial reconstruction of other ionospheric parameters and further promote the realization of complete and accurate space weather forecast.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"68 ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138988779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Geomagnetically Induced Current Mitigation in New Zealand: Operational Mitigation Method Development With Industry Input 新西兰的地磁感应电流缓解:工业投入的操作缓解方法开发

IF 3.7 2区地球科学

Space Weather Pub Date : 2023-11-27 DOI: 10.1029/2023sw003533

D. H. Mac Manus, C. J. Rodger, A. Renton, J. Ronald, D. Harper, C. Taylor, M. Dalzell, T. Divett, M. A. Clilverd

{"title":"Geomagnetically Induced Current Mitigation in New Zealand: Operational Mitigation Method Development With Industry Input","authors":"D. H. Mac Manus, C. J. Rodger, A. Renton, J. Ronald, D. Harper, C. Taylor, M. Dalzell, T. Divett, M. A. Clilverd","doi":"10.1029/2023sw003533","DOIUrl":"https://doi.org/10.1029/2023sw003533","url":null,"abstract":"Reducing the impact of Geomagnetically induced currents (GICs) on electrical power networks is an essential step to protect network assets and maintain reliable power transmission during and after storm events. In this study, multiple mitigation strategies are tested during worst-case extreme storm scenarios in order to investigate their effectiveness for the New Zealand transmission network. By working directly with our industry partners, Transpower New Zealand Ltd, a mitigation strategy in the form of targeted line disconnections has been developed. This mitigation strategy proved more effective than previous strategies at reducing GIC magnitudes and durations at transformers at most risk to GIC while still maintaining the continuous supply of power throughout New Zealand. Under this mitigation plan, the average 60-min mean GIC decreased for 27 of the top 30 at-risk transformers, and the total network GIC was reduced by 16%. This updated mitigation has been adopted as an operational procedure in the New Zealand national control room to manage GIC. In addition, simulations show that the installation of 14 capacitor blocking devices at specific transformers reduces the total GIC sum in the network by an additional 16%. As a result of this study Transpower is considering further mitigation in the form of capacitor blockers. We strongly recommend collaborating with the relevant power network providers to develop effective mitigation strategies that reduce GIC and have a minimal impact on power distribution.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"32 5 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138529464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0