In order to protect society from space weather impacts, we must monitor space weather and obtain early warnings for extreme events if possible. For this purpose, the European Space Agency is currently preparing to launch the Vigil mission toward the end of this decade as a space-weather monitor at the fifth Lagrange point of the Sun–Earth system. Vigil will carry, amongst other instruments, the Plasma Analyser (PLA) to provide quasi-continuous measurements of solar wind ions. We model the performance of the PLA instrument, considering typical solar wind plasma conditions, to compare the expected observations of PLA with the assumed input conditions of the solar wind. We evaluate the instrument performance under realistic, non-equilibrium plasma conditions, accounting for temperature anisotropies, proton beams, and the contributions from α-particles. We examine the accuracy of the instrument's performance over a range of input solar wind moments. We identify sources of potential errors due to non-equilibrium plasma conditions and link these to instrument characteristics such as its angular and energy resolution and its field of view. We demonstrate the limitations of the instrument and potential improvements such as applying ground-based fitting techniques to obtain more accurate measurements of the solar wind even under non-equilibrium plasma conditions. The use of ground processing of plasma moments instead of on-board processing is crucial for the extraction of reliable measurements.
{"title":"The Impact of Non-Equilibrium Plasma Distributions on Solar Wind Measurements by Vigil's Plasma Analyser","authors":"H. Zhang, D. Verscharen, G. Nicolaou","doi":"10.1029/2023sw003671","DOIUrl":"https://doi.org/10.1029/2023sw003671","url":null,"abstract":"In order to protect society from space weather impacts, we must monitor space weather and obtain early warnings for extreme events if possible. For this purpose, the European Space Agency is currently preparing to launch the Vigil mission toward the end of this decade as a space-weather monitor at the fifth Lagrange point of the Sun–Earth system. Vigil will carry, amongst other instruments, the Plasma Analyser (PLA) to provide quasi-continuous measurements of solar wind ions. We model the performance of the PLA instrument, considering typical solar wind plasma conditions, to compare the expected observations of PLA with the assumed input conditions of the solar wind. We evaluate the instrument performance under realistic, non-equilibrium plasma conditions, accounting for temperature anisotropies, proton beams, and the contributions from <i>α</i>-particles. We examine the accuracy of the instrument's performance over a range of input solar wind moments. We identify sources of potential errors due to non-equilibrium plasma conditions and link these to instrument characteristics such as its angular and energy resolution and its field of view. We demonstrate the limitations of the instrument and potential improvements such as applying ground-based fitting techniques to obtain more accurate measurements of the solar wind even under non-equilibrium plasma conditions. The use of ground processing of plasma moments instead of on-board processing is crucial for the extraction of reliable measurements.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"16 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139925685","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}
This study addresses the limitations of single-viewpoint observations of Coronal Mass Ejections (CMEs) by presenting results from a 3D catalog of 360 CMEs during solar cycle 24, fitted using the Graduated Cylindrical Shell (GCS) model. The data set combines 326 previously analyzed CMEs and 34 newly examined events, categorized by their source regions into active region (AR) eruptions, active prominence (AP) eruptions, and prominence eruptions (PE). Estimates of errors are made using a bootstrapping approach. The findings highlight that the average 3D speed of CMEs is ∼1.3 times greater than the 2D speed. PE CMEs tend to be slow, with an average speed of 432 km s−1. AR and AP speeds are higher, at 723 and 813 km s−1, respectively, with the latter having fewer slow CMEs. The distinctive behavior of AP CMEs is attributed to factors like overlying magnetic field distribution or geometric complexities leading to less accurate GCS fits. A linear fit of projected speed to width gives a gradient of ∼2 km s−1 deg−1, which increases to 5 km s−1 deg−1 when the GCS-fitted ‘true’ parameters are used. Notably, AR CMEs exhibit a high gradient of 7 km s−1 deg−1, while AP CMEs show a gradient of 4 km s−1 deg−1. PE CMEs, however, lack a significant speed-width relationship. We show that fitting multi-viewpoint CME images to a geometrical model such as GCS is important to study the statistical properties of CMEs, and can lead to a deeper insight into CME behavior that is essential for improving future space weather forecasting.
本研究针对日冕物质抛射（CMEs）单视角观测的局限性，展示了太阳周期24期间360个CMEs的三维目录结果，并使用渐变圆柱壳（GCS）模型进行了拟合。数据集结合了以前分析过的 326 个 CME 和 34 个新研究的事件，按其来源区域分为活动区爆发 (AR)、活动突出部爆发 (AP) 和突出部爆发 (PE)。采用自举法对误差进行了估计。研究结果表明，CMEs 的平均 3D 速度是 2D 速度的 1.3 倍。PE CME 的速度往往较慢，平均速度为 432 km s-1。AR和AP的速度较高，分别为723和813 km s-1，后者的慢速CME较少。AP CMEs的独特行为可归因于上覆磁场分布或几何复杂性等因素，导致GCS拟合精度较低。投影速度与宽度的线性拟合得出的梯度为∼2 km s-1 deg-1，当使用GCS拟合的 "真实 "参数时，梯度增加到5 km s-1 deg-1。值得注意的是，AR CME 的梯度高达 7 km s-1 deg-1，而 AP CME 的梯度为 4 km s-1 deg-1。然而，PE CME 缺乏明显的速度-宽度关系。我们的研究表明，将多视点 CME 图像拟合到 GCS 等几何模型中对研究 CME 的统计特性非常重要，可以使人们更深入地了解 CME 的行为，这对改进未来的空间天气预报至关重要。
{"title":"Correcting Projection Effects in CMEs Using GCS-Based Large Statistics of Multi-Viewpoint Observations","authors":"Harshita Gandhi, Ritesh Patel, Vaibhav Pant, Satabdwa Majumdar, Sanchita Pal, Dipankar Banerjee, Huw Morgan","doi":"10.1029/2023sw003805","DOIUrl":"https://doi.org/10.1029/2023sw003805","url":null,"abstract":"This study addresses the limitations of single-viewpoint observations of Coronal Mass Ejections (CMEs) by presenting results from a 3D catalog of 360 CMEs during solar cycle 24, fitted using the Graduated Cylindrical Shell (GCS) model. The data set combines 326 previously analyzed CMEs and 34 newly examined events, categorized by their source regions into active region (AR) eruptions, active prominence (AP) eruptions, and prominence eruptions (PE). Estimates of errors are made using a bootstrapping approach. The findings highlight that the average 3D speed of CMEs is ∼1.3 times greater than the 2D speed. PE CMEs tend to be slow, with an average speed of 432 km s<sup>−1</sup>. AR and AP speeds are higher, at 723 and 813 km s<sup>−1</sup>, respectively, with the latter having fewer slow CMEs. The distinctive behavior of AP CMEs is attributed to factors like overlying magnetic field distribution or geometric complexities leading to less accurate GCS fits. A linear fit of projected speed to width gives a gradient of ∼2 km s<sup>−1</sup> deg<sup>−1</sup>, which increases to 5 km s<sup>−1</sup> deg<sup>−1</sup> when the GCS-fitted ‘true’ parameters are used. Notably, AR CMEs exhibit a high gradient of 7 km s<sup>−1</sup> deg<sup>−1</sup>, while AP CMEs show a gradient of 4 km s<sup>−1</sup> deg<sup>−1</sup>. PE CMEs, however, lack a significant speed-width relationship. We show that fitting multi-viewpoint CME images to a geometrical model such as GCS is important to study the statistical properties of CMEs, and can lead to a deeper insight into CME behavior that is essential for improving future space weather forecasting.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"1 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139925608","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}
The receiver tracking error stochastic (RTES) model can improve GNSS precise point positioning (PPP) performance under ionospheric scintillation. However, it relies on scintillation products derived from ionospheric scintillation monitoring receivers (ISMRs), which means the RTES model cannot be used for abundant geodetic GNSS receivers. In this study, we propose an improved RTES, referred to as Impr_RTES model, to mitigate scintillation effects on geodetic GNSS receivers at low latitudes, where severe scintillation frequently occurs. In the Impr_RTES model, the tracking error variances at the output of code delay locked loop are calculated by using the index S4c, and these of phase locked loop are modeled by using the rate of total electron content index (ROTI) and S4c. Both S4c and ROTI can be derived from geodetic GNSS receivers. The performance of the Impr_RTES model is validated by using the data sets from ISMR and geodetic receivers, respectively. Using one month of GPS data collected at HNLW station installed with ISMR in Hainan of China from 1 to 28 February in 2023, statistical results indicate that the PPP solution based on Impr_RTES model can improve the positioning accuracy by approximately 22.6%, 23.8%, and 30.2% in the east, north, and up directions, respectively, over the elevation angle stochastic (EAS) model. Meanwhile, the positioning performance of Impr_RTES PPP is comparable to that of RTES PPP. For the GPS data from geodetic receivers, experimental results suggest that compared with EAS, the Impr_RTES model can obviously mitigate scintillation effects on PPP.
{"title":"An Improved Stochastic Model for the Geodetic GNSS Receivers Under Ionospheric Scintillation at Low Latitudes","authors":"Xiaomin Luo, Yingzong Lin, Xiaolei Dai, Shaofeng Bian, Dezhong Chen","doi":"10.1029/2023sw003632","DOIUrl":"https://doi.org/10.1029/2023sw003632","url":null,"abstract":"The receiver tracking error stochastic (RTES) model can improve GNSS precise point positioning (PPP) performance under ionospheric scintillation. However, it relies on scintillation products derived from ionospheric scintillation monitoring receivers (ISMRs), which means the RTES model cannot be used for abundant geodetic GNSS receivers. In this study, we propose an improved RTES, referred to as Impr_RTES model, to mitigate scintillation effects on geodetic GNSS receivers at low latitudes, where severe scintillation frequently occurs. In the Impr_RTES model, the tracking error variances at the output of code delay locked loop are calculated by using the index <i>S</i><sub>4<i>c</i></sub>, and these of phase locked loop are modeled by using the rate of total electron content index (ROTI) and <i>S</i><sub>4<i>c</i></sub>. Both <i>S</i><sub>4<i>c</i></sub> and ROTI can be derived from geodetic GNSS receivers. The performance of the Impr_RTES model is validated by using the data sets from ISMR and geodetic receivers, respectively. Using one month of GPS data collected at HNLW station installed with ISMR in Hainan of China from 1 to 28 February in 2023, statistical results indicate that the PPP solution based on Impr_RTES model can improve the positioning accuracy by approximately 22.6%, 23.8%, and 30.2% in the east, north, and up directions, respectively, over the elevation angle stochastic (EAS) model. Meanwhile, the positioning performance of Impr_RTES PPP is comparable to that of RTES PPP. For the GPS data from geodetic receivers, experimental results suggest that compared with EAS, the Impr_RTES model can obviously mitigate scintillation effects on PPP.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"9 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139925611","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}
Volcanic eruptions provide broad spectral forcing to the atmosphere and understanding the primary mechanisms that are relevant to explain the variety in waveform characteristics in the Ionosphere-Thermosphere (IT) is still an important open question for the community. In this study, Global Navigation Satellite System (GNSS) Total Electron Content (TEC) data are analyzed and compared to simulations performed by the Global Ionosphere-Thermosphere Model with Local Mesh Refinement (GITM-R) for the first phase of the 2015 Calbuco eruption that occurred on 22 April. A simplified source representation and spectral acoustic-gravity wave (AGW) propagation model are used to specify the perturbation at the lower boundary of GITM-R at 100 km altitude. Two assumptions on the propagation structure, Direct Spherical (DS) and Ground Coupled (GC), are compared to the GNSS data and these modeling specifications show good agreement with different aspects of the observations for some waveform characteristics. Most notably, GITM-R is able to reproduce the relative wave amplitude of AGWs as a function of radial distance from the vent, showing acoustic dominant forcing in the near field (<500 km) and gravity dominant forcing in the far-field (>500 km). The estimated apparent phase speeds from GITM-R simulations are consistent with observations with ∼10% difference from observation for both acoustic wave packets and a trailing gravity mode. The relevance of the simplifications made in the lower atmosphere to the simulated IT response is then discussed.
{"title":"Ionospheric Disturbances Generated by the 2015 Calbuco Eruption: Comparison of GITM-R Simulations and GNSS Observations","authors":"J. Tyska, Y. Deng, S. Zhang, C. Y. Lin","doi":"10.1029/2023sw003502","DOIUrl":"https://doi.org/10.1029/2023sw003502","url":null,"abstract":"Volcanic eruptions provide broad spectral forcing to the atmosphere and understanding the primary mechanisms that are relevant to explain the variety in waveform characteristics in the Ionosphere-Thermosphere (IT) is still an important open question for the community. In this study, Global Navigation Satellite System (GNSS) Total Electron Content (TEC) data are analyzed and compared to simulations performed by the Global Ionosphere-Thermosphere Model with Local Mesh Refinement (GITM-R) for the first phase of the 2015 Calbuco eruption that occurred on 22 April. A simplified source representation and spectral acoustic-gravity wave (AGW) propagation model are used to specify the perturbation at the lower boundary of GITM-R at 100 km altitude. Two assumptions on the propagation structure, Direct Spherical (DS) and Ground Coupled (GC), are compared to the GNSS data and these modeling specifications show good agreement with different aspects of the observations for some waveform characteristics. Most notably, GITM-R is able to reproduce the relative wave amplitude of AGWs as a function of radial distance from the vent, showing acoustic dominant forcing in the near field (<500 km) and gravity dominant forcing in the far-field (>500 km). The estimated apparent phase speeds from GITM-R simulations are consistent with observations with ∼10% difference from observation for both acoustic wave packets and a trailing gravity mode. The relevance of the simplifications made in the lower atmosphere to the simulated IT response is then discussed.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"78 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139925687","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}
Weijia Zhan, Alireza Doostan, Eric Sutton, Tzu-Wei Fang
This study presents a data-driven approach to quantify uncertainties in the ionosphere-thermosphere (IT) system due to varying solar wind parameters (drivers) during quiet conditions (Kp < 4) and fixed solar radiation and lower atmospheric conditions representative of 16 March 2013. Ensemble simulations of the coupled Whole Atmosphere Model with Ionosphere Plasmasphere Electrodynamics (WAM-IPE) driven by synthetic solar wind drivers generated through a multi-channel variational autoencoder (MCVAE) model are obtained. Applying the polynomial chaos expansion (PCE) technique, it is possible to estimate the means and variances of the QoIs as well as the sensitivities of the QoIs with regard to the drivers. Our results highlight unique features of the IT system's uncertainty: (a) the uncertainty of the IT system is larger during nighttime; (b) the spatial distributions of the uncertainty for electron density and zonal drift at fixed local times present 4 peaks in the evening sector, which are associated with the low-density regions of longitude structure of electron density; (c) the uncertainty of the equatorial electron density is highly correlated with the uncertainty of the zonal drift, especially in the evening sector, while it is weakly correlated with the vertical drift. A variance-based global sensitivity analysis suggests that the IMF Bz plays a dominant role in the uncertainty of electron density. A further discussion shows that the uncertainty of the IT system is determined by the magnitudes and universal time variations of solar wind drivers. Its temporal and spatial distribution can be modulated by the average state of the IT system.
{"title":"Quantifying Uncertainties in the Quiet-Time Ionosphere-Thermosphere Using WAM-IPE","authors":"Weijia Zhan, Alireza Doostan, Eric Sutton, Tzu-Wei Fang","doi":"10.1029/2023sw003665","DOIUrl":"https://doi.org/10.1029/2023sw003665","url":null,"abstract":"This study presents a data-driven approach to quantify uncertainties in the ionosphere-thermosphere (IT) system due to varying solar wind parameters (drivers) during quiet conditions (Kp < 4) and fixed solar radiation and lower atmospheric conditions representative of 16 March 2013. Ensemble simulations of the coupled Whole Atmosphere Model with Ionosphere Plasmasphere Electrodynamics (WAM-IPE) driven by synthetic solar wind drivers generated through a multi-channel variational autoencoder (MCVAE) model are obtained. Applying the polynomial chaos expansion (PCE) technique, it is possible to estimate the means and variances of the QoIs as well as the sensitivities of the QoIs with regard to the drivers. Our results highlight unique features of the IT system's uncertainty: (a) the uncertainty of the IT system is larger during nighttime; (b) the spatial distributions of the uncertainty for electron density and zonal drift at fixed local times present 4 peaks in the evening sector, which are associated with the low-density regions of longitude structure of electron density; (c) the uncertainty of the equatorial electron density is highly correlated with the uncertainty of the zonal drift, especially in the evening sector, while it is weakly correlated with the vertical drift. A variance-based global sensitivity analysis suggests that the IMF Bz plays a dominant role in the uncertainty of electron density. A further discussion shows that the uncertainty of the IT system is determined by the magnitudes and universal time variations of solar wind drivers. Its temporal and spatial distribution can be modulated by the average state of the IT system.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"254 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139678547","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}
Giacomo Acciarini, Edward Brown, Tom Berger, Madhulika Guhathakurta, James Parr, Christopher Bridges, Atılım Güneş Baydin
Thermospheric density is one of the main sources of uncertainty in the estimation of satellites' position and velocity in low-Earth orbit. This has negative consequences in several space domains, including space traffic management, collision avoidance, re-entry predictions, orbital lifetime analysis, and space object cataloging. In this paper, we investigate the prediction accuracy of empirical density models (e.g., NRLMSISE-00 and JB-08) against black-box machine learning (ML) models trained on precise orbit determination-derived thermospheric density data (from CHAMP, GOCE, GRACE, SWARM-A/B satellites). We show that by using the same inputs, the ML models we designed are capable of consistently improving the predictions with respect to state-of-the-art empirical models by reducing the mean absolute percentage error (MAPE) in the thermospheric density estimation from the range of 40%–60% to approximately 20%. As a result of this work, we introduce Karman: an open-source Python software package developed during this study. Karman provides functionalities to ingest and preprocess thermospheric density, solar irradiance, and geomagnetic input data for ML readiness. Additionally, it facilitates developing and training ML models on the aforementioned data and benchmarking their performance at different altitudes, geographic locations, times, and solar activity conditions. Through this contribution, we offer the scientific community a comprehensive tool for comparing and enhancing thermospheric density models using ML techniques.
热层密度是低地轨道卫星位置和速度估算不确定性的主要来源之一。这给多个空间领域带来了负面影响，包括空间交通管理、避免碰撞、重返预测、轨道寿命分析和空间物体编目。在本文中，我们研究了经验密度模型（如 NRLMSISE-00 和 JB-08）与根据精确轨道测定得出的热层密度数据（来自 CHAMP、GOCE、GRACE、SWARM-A/B 卫星）训练的黑盒机器学习（ML）模型的预测准确性。我们的研究表明，通过使用相同的输入，我们设计的 ML 模型能够持续改进与最先进的经验模型相比的预测结果，将热层密度估计的平均绝对百分比误差（MAPE）从 40%-60% 的范围降低到大约 20%。作为这项工作的成果，我们介绍了 Karman：这是本研究期间开发的一个开源 Python 软件包。Karman 提供了摄取和预处理热层密度、太阳辐照度和地磁输入数据的功能，以便为 ML 做好准备。此外，它还有助于在上述数据上开发和训练 ML 模型，并对其在不同高度、地理位置、时间和太阳活动条件下的性能进行基准测试。通过这一贡献，我们为科学界提供了一个利用 ML 技术比较和增强热层密度模型的综合工具。
{"title":"Improving Thermospheric Density Predictions in Low-Earth Orbit With Machine Learning","authors":"Giacomo Acciarini, Edward Brown, Tom Berger, Madhulika Guhathakurta, James Parr, Christopher Bridges, Atılım Güneş Baydin","doi":"10.1029/2023sw003652","DOIUrl":"https://doi.org/10.1029/2023sw003652","url":null,"abstract":"Thermospheric density is one of the main sources of uncertainty in the estimation of satellites' position and velocity in low-Earth orbit. This has negative consequences in several space domains, including space traffic management, collision avoidance, re-entry predictions, orbital lifetime analysis, and space object cataloging. In this paper, we investigate the prediction accuracy of empirical density models (e.g., NRLMSISE-00 and JB-08) against black-box machine learning (ML) models trained on precise orbit determination-derived thermospheric density data (from CHAMP, GOCE, GRACE, SWARM-A/B satellites). We show that by using the same inputs, the ML models we designed are capable of consistently improving the predictions with respect to state-of-the-art empirical models by reducing the mean absolute percentage error (MAPE) in the thermospheric density estimation from the range of 40%–60% to approximately 20%. As a result of this work, we introduce Karman: an open-source Python software package developed during this study. Karman provides functionalities to ingest and preprocess thermospheric density, solar irradiance, and geomagnetic input data for ML readiness. Additionally, it facilitates developing and training ML models on the aforementioned data and benchmarking their performance at different altitudes, geographic locations, times, and solar activity conditions. Through this contribution, we offer the scientific community a comprehensive tool for comparing and enhancing thermospheric density models using ML techniques.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"30 2 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139678520","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}
John Malone-Leigh, Joan Campanyà, Peter T. Gallagher, Jim Hodgson, Colin Hogg
Geoelectric fields are generated at the Earth's surface and can lead to the induction of hazardous geomagnetically induced currents (GIC) in infrastructure like power grids, railways and pipelines during geomagnetic storms. Magnitude and orientation of the geoelectric fields, in relation to the infrastructure, are key features needed to determine the intensity of GIC. Here, we developed the first geoelectric hazard map for the island of Ireland, with the aim of providing detailed information that can help stakeholders mitigate the impact of GICs. The hazard map was developed by modeling and mapping the geoelectric field across Ireland for 28 years (1991–2018) using magnetic field data with magnetotelluric transfer functions. The approach for developing the hazard map calculates the probability of exceeding a hazardous geoelectric field threshold (500 mV/km) during large geomagnetic storms, taking directionality and amplitude into account. We found hazardous geoelectric fields to be mostly localized in areas in the west, south-west and northern coast. We observed that the geoelectric field have a stronger dominant orientation than the orientation of the geomagnetic field, often constraining the hazardous geoelectric field in particular directions only. We demonstrate a seasonal/diurnal effect is present in the geoelectric field time series. The impact of galvanic distortion was also assessed, and we demonstrate that there is a significant difference in terms of amplitude and direction between both models.
{"title":"Mapping Geoelectric Field Hazards in Ireland","authors":"John Malone-Leigh, Joan Campanyà, Peter T. Gallagher, Jim Hodgson, Colin Hogg","doi":"10.1029/2023sw003638","DOIUrl":"https://doi.org/10.1029/2023sw003638","url":null,"abstract":"Geoelectric fields are generated at the Earth's surface and can lead to the induction of hazardous geomagnetically induced currents (GIC) in infrastructure like power grids, railways and pipelines during geomagnetic storms. Magnitude and orientation of the geoelectric fields, in relation to the infrastructure, are key features needed to determine the intensity of GIC. Here, we developed the first geoelectric hazard map for the island of Ireland, with the aim of providing detailed information that can help stakeholders mitigate the impact of GICs. The hazard map was developed by modeling and mapping the geoelectric field across Ireland for 28 years (1991–2018) using magnetic field data with magnetotelluric transfer functions. The approach for developing the hazard map calculates the probability of exceeding a hazardous geoelectric field threshold (500 mV/km) during large geomagnetic storms, taking directionality and amplitude into account. We found hazardous geoelectric fields to be mostly localized in areas in the west, south-west and northern coast. We observed that the geoelectric field have a stronger dominant orientation than the orientation of the geomagnetic field, often constraining the hazardous geoelectric field in particular directions only. We demonstrate a seasonal/diurnal effect is present in the geoelectric field time series. The impact of galvanic distortion was also assessed, and we demonstrate that there is a significant difference in terms of amplitude and direction between both models.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"4 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139659281","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}
David H. Boteler, Shibaji Chakraborty, Xueling Shi, Michael D. Hartinger, Xuan Wang
Submarine cables have experienced problems during extreme geomagnetic disturbances because of geomagnetically induced voltages adding or subtracting from the power feed to the repeaters. This is still a concern for modern fiber-optic cables because they contain a copper conductor to carry power to the repeaters. This paper provides a new examination of geomagnetic induction in submarine cables and makes calculations of the voltages experienced by the TAT-8 trans-Atlantic submarine cable during the March 1989 magnetic storm. It is shown that the cable itself experiences an induced electromotive force (emf) and that induction in the ocean also leads to changes of potential of the land at each end of the cable. The process for calculating the electric fields induced in the sea and in the cable from knowledge of the seawater depth and conductivity and subsea conductivity is explained. The cable route is divided into 9 sections and the seafloor electric field is calculated for each section. These are combined to give the total induced emf in the cable. In addition, induction in the seawater and leakage of induced currents through the underlying resistive layers are modeled using a transmission line model of the ocean and underlying layers to determine the change in Earth potentials at the cable ends. The induced emf in the cable and the end potentials are then combined to give the total voltage change experienced by the cable power feed equipment. This gives results very close to those recorded on the TAT-8 cable in March 1989.
{"title":"An Examination of Geomagnetic Induction in Submarine Cables","authors":"David H. Boteler, Shibaji Chakraborty, Xueling Shi, Michael D. Hartinger, Xuan Wang","doi":"10.1029/2023sw003687","DOIUrl":"https://doi.org/10.1029/2023sw003687","url":null,"abstract":"Submarine cables have experienced problems during extreme geomagnetic disturbances because of geomagnetically induced voltages adding or subtracting from the power feed to the repeaters. This is still a concern for modern fiber-optic cables because they contain a copper conductor to carry power to the repeaters. This paper provides a new examination of geomagnetic induction in submarine cables and makes calculations of the voltages experienced by the TAT-8 trans-Atlantic submarine cable during the March 1989 magnetic storm. It is shown that the cable itself experiences an induced electromotive force (emf) and that induction in the ocean also leads to changes of potential of the land at each end of the cable. The process for calculating the electric fields induced in the sea and in the cable from knowledge of the seawater depth and conductivity and subsea conductivity is explained. The cable route is divided into 9 sections and the seafloor electric field is calculated for each section. These are combined to give the total induced emf in the cable. In addition, induction in the seawater and leakage of induced currents through the underlying resistive layers are modeled using a transmission line model of the ocean and underlying layers to determine the change in Earth potentials at the cable ends. The induced emf in the cable and the end potentials are then combined to give the total voltage change experienced by the cable power feed equipment. This gives results very close to those recorded on the TAT-8 cable in March 1989.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"19 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139664839","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}
Zhiyi Fu, Zhenpeng Su, Bin Miao, Zhiyong Wu, Yiren Li, Kai Liu, Xu Shan, Yuming Wang
Surface charging is one of the most common causes of spacecraft anomalies. When and to what potential the spacecraft is charged are two important questions in space weather. Here, for a Chinese geosynchronous navigation satellite, we infer the extreme negative surface charging potentials from the ion differential fluxes measured by a low-energy ion spectrometer. Without the solar eclipse effect away from the midnight, the charging potentials are found to have a negative limit which is determined by the maximum SuperMAG electrojet index in the preceding 2 hr. Such an empirical relation can be reasonably explained by the dependence of 1–50 keV electron fluxes on substorm strength. Similar relations may also exist for other inner magnetospheric spacecraft in the non-eclipse region, which would be useful for spacecraft engineering and space weather alerts.
{"title":"A Substorm-Dependent Negative Limit of Non-Eclipse Surface Charging of a Chinese Geosynchronous Satellite","authors":"Zhiyi Fu, Zhenpeng Su, Bin Miao, Zhiyong Wu, Yiren Li, Kai Liu, Xu Shan, Yuming Wang","doi":"10.1029/2023sw003780","DOIUrl":"https://doi.org/10.1029/2023sw003780","url":null,"abstract":"Surface charging is one of the most common causes of spacecraft anomalies. When and to what potential the spacecraft is charged are two important questions in space weather. Here, for a Chinese geosynchronous navigation satellite, we infer the extreme negative surface charging potentials from the ion differential fluxes measured by a low-energy ion spectrometer. Without the solar eclipse effect away from the midnight, the charging potentials are found to have a negative limit which is determined by the maximum SuperMAG electrojet index in the preceding 2 hr. Such an empirical relation can be reasonably explained by the dependence of 1–50 keV electron fluxes on substorm strength. Similar relations may also exist for other inner magnetospheric spacecraft in the non-eclipse region, which would be useful for spacecraft engineering and space weather alerts.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"4 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139659305","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}
S. Subritzky, A. C. Lapthorn, S. Hardie, D. Manus, C. Rodger, M. Dalzell
Space weather can have major impacts on electrical infrastructure. Multiple instances of transformer damage have been attributed to geomagnetic storms in recent decades, for example, the Hydro Quebec incident of 1989 and the November 2001 storm in New Zealand. While many studies exist on the impacts of geomagnetic storms on power transformers in New Zealand, no studies exist that employ Dissolved Gas Analysis (DGA) techniques to relate geomagnetic storms to transformer gassing. A relationship has been reported between geomagnetic activity and DGA for South Africa, while none was found in a recent study in Great Britain. This paper attempts to examine this research question by examining dissolved gas data across eight power transformers in different substations in New Zealand from 2016 to 2019. Case studies were conducted which analyzed the DGA readings of each transformer alongside horizontal magnetic field component rate of change measurements at Eyrewell across six geomagnetic storms. These case studies were then augmented with an analysis of the entire data set where magnetic field measurements were compared with individual gas rates to establish a correlation between gas production and geomagnetic activity. Analysis of the results of this study concluded that no link had been found between the production of combustible gasses in a transformer and geomagnetic activity during the observation period. However, we note our dissolved gas analysis was largely in a geomagnetically quieter period, which may limit our analysis. The production of combustible gasses is not correlated to geomagnetic storms for the time period and transformers analyzed.
{"title":"Assessment of Space Weather Impacts on New Zealand Power Transformers Using Dissolved Gas Analysis","authors":"S. Subritzky, A. C. Lapthorn, S. Hardie, D. Manus, C. Rodger, M. Dalzell","doi":"10.1029/2023sw003607","DOIUrl":"https://doi.org/10.1029/2023sw003607","url":null,"abstract":"Space weather can have major impacts on electrical infrastructure. Multiple instances of transformer damage have been attributed to geomagnetic storms in recent decades, for example, the Hydro Quebec incident of 1989 and the November 2001 storm in New Zealand. While many studies exist on the impacts of geomagnetic storms on power transformers in New Zealand, no studies exist that employ Dissolved Gas Analysis (DGA) techniques to relate geomagnetic storms to transformer gassing. A relationship has been reported between geomagnetic activity and DGA for South Africa, while none was found in a recent study in Great Britain. This paper attempts to examine this research question by examining dissolved gas data across eight power transformers in different substations in New Zealand from 2016 to 2019. Case studies were conducted which analyzed the DGA readings of each transformer alongside horizontal magnetic field component rate of change measurements at Eyrewell across six geomagnetic storms. These case studies were then augmented with an analysis of the entire data set where magnetic field measurements were compared with individual gas rates to establish a correlation between gas production and geomagnetic activity. Analysis of the results of this study concluded that no link had been found between the production of combustible gasses in a transformer and geomagnetic activity during the observation period. However, we note our dissolved gas analysis was largely in a geomagnetically quieter period, which may limit our analysis. The production of combustible gasses is not correlated to geomagnetic storms for the time period and transformers analyzed.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":"254 ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140482001","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}
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