Pub Date : 2024-06-03DOI: 10.3389/fspas.2024.1412905
Chen Shi, A. Tenerani, A. Rappazzo, M. Velli
Numerical simulations have been an increasingly important tool in space physics. Here, we introduce an open-source three-dimensional compressible Hall-Magnetohydrodynamic (MHD) simulation code LAPS (UCLA-Pseudo-Spectral, https://github.com/chenshihelio/LAPS). The code adopts a pseudo-spectral method based on Fourier Transform to evaluate spatial derivatives, and third-order explicit Runge-Kutta method for time advancement. It is parallelized using Message-Passing-Interface (MPI) with a “pencil” parallelization strategy and has very high scalability. The Expanding-Box-Model is implemented to incorporate spherical expansion effects of the solar wind. We carry out test simulations based on four classic (Hall)-MHD processes, namely, 1) incompressible Hall-MHD waves, 2) incompressible tearing mode instability, 3) Orszag-Tang vortex, and 4) parametric decay instability. The test results agree perfectly with theory predictions and results of previous studies. Given all its features, LAPS is a powerful tool for large-scale simulations of solar wind turbulence as well as other MHD and Hall-MHD processes happening in space.
{"title":"LAPS: An MPI-parallelized 3D pseudo-spectral Hall-MHD simulation code incorporating the expanding box model","authors":"Chen Shi, A. Tenerani, A. Rappazzo, M. Velli","doi":"10.3389/fspas.2024.1412905","DOIUrl":"https://doi.org/10.3389/fspas.2024.1412905","url":null,"abstract":"Numerical simulations have been an increasingly important tool in space physics. Here, we introduce an open-source three-dimensional compressible Hall-Magnetohydrodynamic (MHD) simulation code LAPS (UCLA-Pseudo-Spectral, https://github.com/chenshihelio/LAPS). The code adopts a pseudo-spectral method based on Fourier Transform to evaluate spatial derivatives, and third-order explicit Runge-Kutta method for time advancement. It is parallelized using Message-Passing-Interface (MPI) with a “pencil” parallelization strategy and has very high scalability. The Expanding-Box-Model is implemented to incorporate spherical expansion effects of the solar wind. We carry out test simulations based on four classic (Hall)-MHD processes, namely, 1) incompressible Hall-MHD waves, 2) incompressible tearing mode instability, 3) Orszag-Tang vortex, and 4) parametric decay instability. The test results agree perfectly with theory predictions and results of previous studies. Given all its features, LAPS is a powerful tool for large-scale simulations of solar wind turbulence as well as other MHD and Hall-MHD processes happening in space.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":"57 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141268826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.3389/fspas.2024.1289840
Andreas Kvammen, Juha Vierinen, D. Huyghebaert, T. Rexer, Andres Spicher, Björn J. Gustavsson, Jens Floberg
Millions of ionograms are acquired annually to monitor the ionosphere. The accumulated data contain untapped information from a range of locations, multiple solar cycles, and various geomagnetic conditions. In this study, we propose the application of deep convolutional neural networks to automatically classify and scale high-latitude ionograms. A supervised approach is implemented and the networks are trained and tested using manually analyzed oblique ionograms acquired at a receiver station located in Skibotn, Norway. The classification routine categorizes the observations based on the presence or absence of E− and F-region traces, while the scaling procedure automatically defines the E− and F-region virtual distances and maximum plasma frequencies. Overall, we conclude that deep convolutional neural networks are suitable for automatic processing of ionograms, even under auroral conditions. The networks achieve an average classification accuracy of 93% ± 4% for the E-region and 86% ± 7% for the F-region. In addition, the networks obtain scientifically useful scaling parameters with median absolute deviation values of 118 kHz ±27 kHz for the E-region maximum frequency and 105 kHz ±37 kHz for the F-region maximum O-mode frequency. Predictions of the virtual distance for the E− and F-region yield median distance deviation values of 6.1 km ± 1.7 km and 8.3 km ± 2.3 km, respectively. The developed networks may facilitate EISCAT 3D and other instruments in Fennoscandia by automatic cataloging and scaling of salient ionospheric features. This data can be used to study both long-term ionospheric trends and more transient ionospheric features, such as traveling ionospheric disturbances.
每年都要采集数百万张电离图来监测电离层。积累的数据包含来自不同地点、多个太阳周期和各种地磁条件的未开发信息。在本研究中，我们建议应用深度卷积神经网络对高纬度电离图进行自动分类和缩放。我们采用了一种有监督的方法，并利用位于挪威斯基博特恩的接收站获取的人工分析倾斜电离图对网络进行了训练和测试。分类程序根据是否存在 E 区和 F 区痕迹对观测结果进行分类，而缩放程序则自动定义 E 区和 F 区的虚拟距离和最大等离子体频率。总之，我们认为深度卷积神经网络适用于自动处理电离图，即使在极光条件下也是如此。这些网络对 E 区域的平均分类准确率为 93% ± 4%，对 F 区域的平均分类准确率为 86% ± 7%。此外，网络还获得了科学上有用的缩放参数，E 区最大频率的绝对偏差中值为 118 kHz ±27 kHz，F 区最大 O 模式频率的绝对偏差中值为 105 kHz ±37 kHz。对 E 区和 F 区虚拟距离的预测得出的距离偏差中值分别为 6.1 km ± 1.7 km 和 8.3 km ± 2.3 km。所开发的网络可通过自动编目和缩放电离层显著特征，为 EISCAT 3D 和芬诺 斯堪迪亚的其他仪器提供便利。这些数据既可用于研究电离层的长期趋势，也可用于研究电离层的瞬态特征，如电离层扰动。
{"title":"NOIRE-Net–a convolutional neural network for automatic classification and scaling of high-latitude ionograms","authors":"Andreas Kvammen, Juha Vierinen, D. Huyghebaert, T. Rexer, Andres Spicher, Björn J. Gustavsson, Jens Floberg","doi":"10.3389/fspas.2024.1289840","DOIUrl":"https://doi.org/10.3389/fspas.2024.1289840","url":null,"abstract":"Millions of ionograms are acquired annually to monitor the ionosphere. The accumulated data contain untapped information from a range of locations, multiple solar cycles, and various geomagnetic conditions. In this study, we propose the application of deep convolutional neural networks to automatically classify and scale high-latitude ionograms. A supervised approach is implemented and the networks are trained and tested using manually analyzed oblique ionograms acquired at a receiver station located in Skibotn, Norway. The classification routine categorizes the observations based on the presence or absence of E− and F-region traces, while the scaling procedure automatically defines the E− and F-region virtual distances and maximum plasma frequencies. Overall, we conclude that deep convolutional neural networks are suitable for automatic processing of ionograms, even under auroral conditions. The networks achieve an average classification accuracy of 93% ± 4% for the E-region and 86% ± 7% for the F-region. In addition, the networks obtain scientifically useful scaling parameters with median absolute deviation values of 118 kHz ±27 kHz for the E-region maximum frequency and 105 kHz ±37 kHz for the F-region maximum O-mode frequency. Predictions of the virtual distance for the E− and F-region yield median distance deviation values of 6.1 km ± 1.7 km and 8.3 km ± 2.3 km, respectively. The developed networks may facilitate EISCAT 3D and other instruments in Fennoscandia by automatic cataloging and scaling of salient ionospheric features. This data can be used to study both long-term ionospheric trends and more transient ionospheric features, such as traveling ionospheric disturbances.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":"36 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141268839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.3389/fspas.2024.1371058
Charles W. Smith, B. Vasquez
The solar wind forms the largest wind tunnel for plasma and magnetofluid turbulence that is accessible to Earth. It evolves from what is thought to be a turbulent source that continues to drive nonlinear turbulent dynamics as it expands outward via large-scale, energy-containing wind shear and shocks. In the outer heliosphere, once the gradients in the flow have coalesced and they no longer provide an adequate source for the turbulence, the excitation of wave energy by the injection of interstellar pickup ions becomes the dominant source of energy that continues to drive the turbulence. While there are established formalisms for the determination of the strength of the turbulence and the evolution of the turbulent spectra is well-established, the actual nonlinear dynamics that are responsible for its formation and evolution remain unresolved and the subject of considerable debate. We examine the evidence and attempt to illuminate the various theories while demonstrating what is needed to resolve the debates and bring the subject of plasma turbulence into a new level of understanding.
{"title":"The unsolved problem of solar-wind turbulence","authors":"Charles W. Smith, B. Vasquez","doi":"10.3389/fspas.2024.1371058","DOIUrl":"https://doi.org/10.3389/fspas.2024.1371058","url":null,"abstract":"The solar wind forms the largest wind tunnel for plasma and magnetofluid turbulence that is accessible to Earth. It evolves from what is thought to be a turbulent source that continues to drive nonlinear turbulent dynamics as it expands outward via large-scale, energy-containing wind shear and shocks. In the outer heliosphere, once the gradients in the flow have coalesced and they no longer provide an adequate source for the turbulence, the excitation of wave energy by the injection of interstellar pickup ions becomes the dominant source of energy that continues to drive the turbulence. While there are established formalisms for the determination of the strength of the turbulence and the evolution of the turbulent spectra is well-established, the actual nonlinear dynamics that are responsible for its formation and evolution remain unresolved and the subject of considerable debate. We examine the evidence and attempt to illuminate the various theories while demonstrating what is needed to resolve the debates and bring the subject of plasma turbulence into a new level of understanding.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":"55 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140965629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.3389/fspas.2024.1273079
T. Bag, R. Kataoka, Y. Ogawa, H. Fujiwara, Z. Li, Vir Singh, V. Sivakumar, S. Sridharan, P. Pirnaris, T. Tourgaidis
We selected three superstorms (disturbance storm time [Dst] index less than −350 nT) of 2003–04 to study the thermospheric energy budget with a particular emphasis on the thermospheric cooling emission by nitric oxide via a wavelength of 5.3 μm. The nitric oxide radiative emission data are obtained from the Sounding of the Atmosphere by Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite and the thermosphere ionosphere electrodynamic general circulation model (TIEGCM) simulation. Different energy sources for the magnetospheric energy injection and the thermospheric/ionospheric dissipation processes are calculated using empirical formulations, model simulations, and space-borne and ground-based measurements. The Joule heating rates calculated from different sources showed similar variations but significant differences in the magnitude. The nitric oxide cooling power is calculated by zonally and meridionally integrating the cooling flux in the altitude range of 100–250 km. The satellite observed that cooling flux responds faster to the energy input, as compared to the modeled results. The cooling power increases by an order of magnitude during storm time with maximum radiation observed during the recovery phase. Both the satellite-observed and modeled cooling powers show a strong positive correlation with the Joule heating power during the main phase of the storm. It is found that the maximum radiative power does not occur during the strongest storm, and it strongly depends on the duration of the main phase. The model simulation predicts a higher cooling power than that predicted by the observation. During a typical superstorm, on average, a cooling power of 1.87 × 105 GW exiting the thermosphere is estimated by the TIEGCM simulation. On average, it is about 40% higher than the satellite observation.
{"title":"Thermospheric nitric oxide energy budget during extreme geomagnetic storms: a comparative study","authors":"T. Bag, R. Kataoka, Y. Ogawa, H. Fujiwara, Z. Li, Vir Singh, V. Sivakumar, S. Sridharan, P. Pirnaris, T. Tourgaidis","doi":"10.3389/fspas.2024.1273079","DOIUrl":"https://doi.org/10.3389/fspas.2024.1273079","url":null,"abstract":"We selected three superstorms (disturbance storm time [Dst] index less than −350 nT) of 2003–04 to study the thermospheric energy budget with a particular emphasis on the thermospheric cooling emission by nitric oxide via a wavelength of 5.3 μm. The nitric oxide radiative emission data are obtained from the Sounding of the Atmosphere by Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite and the thermosphere ionosphere electrodynamic general circulation model (TIEGCM) simulation. Different energy sources for the magnetospheric energy injection and the thermospheric/ionospheric dissipation processes are calculated using empirical formulations, model simulations, and space-borne and ground-based measurements. The Joule heating rates calculated from different sources showed similar variations but significant differences in the magnitude. The nitric oxide cooling power is calculated by zonally and meridionally integrating the cooling flux in the altitude range of 100–250 km. The satellite observed that cooling flux responds faster to the energy input, as compared to the modeled results. The cooling power increases by an order of magnitude during storm time with maximum radiation observed during the recovery phase. Both the satellite-observed and modeled cooling powers show a strong positive correlation with the Joule heating power during the main phase of the storm. It is found that the maximum radiative power does not occur during the strongest storm, and it strongly depends on the duration of the main phase. The model simulation predicts a higher cooling power than that predicted by the observation. During a typical superstorm, on average, a cooling power of 1.87 × 105 GW exiting the thermosphere is estimated by the TIEGCM simulation. On average, it is about 40% higher than the satellite observation.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":"48 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.3389/fspas.2024.1390427
M. Aghabozorgi Nafchi, F. Němec, G. Pi, Z. Němeček, J. Šafránková, K. Grygorov, J. Šimůnek, T.-C. Tsai
An intrinsic limitation of empirical models of the magnetopause location is a predefined magnetopause shape and assumed functional dependences on relevant parameters. We overcome this limitation using a machine learning approach (artificial neural networks), allowing us to incorporate general, purely data-driven dependences. For the training and testing of the developed neural network model, a data set of about 15,000 magnetopause crossings identified in the THEMIS A-E, Magion 4, Geotail, and Interball-1 satellite data in the subsolar region is used. A cylindrical symmetry around the direction of the impinging solar wind is assumed, and solar wind dynamic pressure, interplanetary magnetic field magnitude, cone angle, clock angle, tilt angle, and corrected Dst index are considered as parameters. The effect of these parameters on the magnetopause location is revealed. The performance of the developed model is compared with other empirical magnetopause models. Finally, we demonstrate and discuss the inaccuracy of magnetopause models due to the inaccurate information about the impinging solar wind parameters based on measurements near the L1 point. This inaccuracy imposes a theoretical limit on the precision of magnetopause predictions, a limit that our model closely approaches.
{"title":"Magnetopause location modeling using machine learning: inaccuracy due to solar wind parameter propagation","authors":"M. Aghabozorgi Nafchi, F. Němec, G. Pi, Z. Němeček, J. Šafránková, K. Grygorov, J. Šimůnek, T.-C. Tsai","doi":"10.3389/fspas.2024.1390427","DOIUrl":"https://doi.org/10.3389/fspas.2024.1390427","url":null,"abstract":"An intrinsic limitation of empirical models of the magnetopause location is a predefined magnetopause shape and assumed functional dependences on relevant parameters. We overcome this limitation using a machine learning approach (artificial neural networks), allowing us to incorporate general, purely data-driven dependences. For the training and testing of the developed neural network model, a data set of about 15,000 magnetopause crossings identified in the THEMIS A-E, Magion 4, Geotail, and Interball-1 satellite data in the subsolar region is used. A cylindrical symmetry around the direction of the impinging solar wind is assumed, and solar wind dynamic pressure, interplanetary magnetic field magnitude, cone angle, clock angle, tilt angle, and corrected Dst index are considered as parameters. The effect of these parameters on the magnetopause location is revealed. The performance of the developed model is compared with other empirical magnetopause models. Finally, we demonstrate and discuss the inaccuracy of magnetopause models due to the inaccurate information about the impinging solar wind parameters based on measurements near the L1 point. This inaccuracy imposes a theoretical limit on the precision of magnetopause predictions, a limit that our model closely approaches.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":"53 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.3389/fspas.2024.1388307
Adrian Pöppelwerth, F. Koller, Niklas Grimmich, Dragos Constantinescu, Georg Glebe, Zoltán Vörös, Manuela Temmer, Cyril Simon Wedlund, Ferdinand Plaschke
{"title":"Cluster: List of plasma jets in the subsolar magnetosheath","authors":"Adrian Pöppelwerth, F. Koller, Niklas Grimmich, Dragos Constantinescu, Georg Glebe, Zoltán Vörös, Manuela Temmer, Cyril Simon Wedlund, Ferdinand Plaschke","doi":"10.3389/fspas.2024.1388307","DOIUrl":"https://doi.org/10.3389/fspas.2024.1388307","url":null,"abstract":"","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":"25 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-13DOI: 10.3389/fspas.2024.1376073
Richard E. Denton, Phoebe M. Tengdin, David P. Hartley, Jerry Goldstein, Jinmyoung Lee, Kazue Takahashi
The high density plasmasphere in the magnetosphere is often separated from a lower density region outside of the plasmasphere, called the plasmatrough, by a sharp gradient in electron density called the plasmapause. Here we use plasmapause events identified from electron density data from the ISEE, CRRES, Polar, and IMAGE missions, and the nonlinear genetic algorithm TuringBot, to find models for the electron density at the midpoint of the plasmapause, ne,pp. A good model for ne,pp should include dependence on L, which is the strongest dependence. But models can be improved by including weaker dependencies on the magnetic local time, MLT, the solar EUV index F10.7, and geomagnetic activity as indicated by averages of Kp and AE. The most complicated model that we present predicts ne,pp within a factor of 1.64, and is within the range of observed plasmapause densities for about 96% of our events. These models can be useful for separating plasma populations into plasmasphere-like and plasmatrough-like populations. We also make available our database of electron density measurements categorized into various populations.
{"title":"The electron density at the midpoint of the plasmapause","authors":"Richard E. Denton, Phoebe M. Tengdin, David P. Hartley, Jerry Goldstein, Jinmyoung Lee, Kazue Takahashi","doi":"10.3389/fspas.2024.1376073","DOIUrl":"https://doi.org/10.3389/fspas.2024.1376073","url":null,"abstract":"The high density plasmasphere in the magnetosphere is often separated from a lower density region outside of the plasmasphere, called the plasmatrough, by a sharp gradient in electron density called the plasmapause. Here we use plasmapause events identified from electron density data from the ISEE, CRRES, Polar, and IMAGE missions, and the nonlinear genetic algorithm TuringBot, to find models for the electron density at the midpoint of the plasmapause, ne,pp. A good model for ne,pp should include dependence on L, which is the strongest dependence. But models can be improved by including weaker dependencies on the magnetic local time, MLT, the solar EUV index F10.7, and geomagnetic activity as indicated by averages of Kp and AE. The most complicated model that we present predicts ne,pp within a factor of 1.64, and is within the range of observed plasmapause densities for about 96% of our events. These models can be useful for separating plasma populations into plasmasphere-like and plasmatrough-like populations. We also make available our database of electron density measurements categorized into various populations.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":"81 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140984527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-10DOI: 10.3389/fspas.2024.1383072
A. Wagner, D. Price, S. Bourgeois, J. Pomoell, S. Poedts, E. Kilpua
Modelling the early evolution of magnetic flux ropes (MFRs) in the solar atmosphere is crucial for understanding their destabilization and eruption mechanism. Identifying the relevant magnetic field lines in simulation data, however, is not straightforward. In previous work an extraction and tracking method was developed to facilitate this task. Here, we present the corresponding graphical user interface (GUI), called GUITAR (GUI for Tracking and Analysing flux Ropes), with the aim to offer a variety of tools to the community for identifying and tracking MFRs. The starting point is a map of a selected proxy parameter for MFRs, e.g., a map of the twist-parameter Tw, current density, etc. We showcase how the GUITAR tools can be used to disentangle a multi-MFR system and facilitate in-depth analysis of their properties and evolution by applying them on a time-dependent data-driven magnetofrictional model (TMFM) simulation of solar active region AR12473. We show the MFR extraction using Tw maps, together with targeted use of mathematical morphology algorithms and discuss the evolution of the system.
{"title":"Solar magnetic flux rope identification with GUITAR: GUI for Tracking and Analysing flux Ropes","authors":"A. Wagner, D. Price, S. Bourgeois, J. Pomoell, S. Poedts, E. Kilpua","doi":"10.3389/fspas.2024.1383072","DOIUrl":"https://doi.org/10.3389/fspas.2024.1383072","url":null,"abstract":"Modelling the early evolution of magnetic flux ropes (MFRs) in the solar atmosphere is crucial for understanding their destabilization and eruption mechanism. Identifying the relevant magnetic field lines in simulation data, however, is not straightforward. In previous work an extraction and tracking method was developed to facilitate this task. Here, we present the corresponding graphical user interface (GUI), called GUITAR (GUI for Tracking and Analysing flux Ropes), with the aim to offer a variety of tools to the community for identifying and tracking MFRs. The starting point is a map of a selected proxy parameter for MFRs, e.g., a map of the twist-parameter Tw, current density, etc. We showcase how the GUITAR tools can be used to disentangle a multi-MFR system and facilitate in-depth analysis of their properties and evolution by applying them on a time-dependent data-driven magnetofrictional model (TMFM) simulation of solar active region AR12473. We show the MFR extraction using Tw maps, together with targeted use of mathematical morphology algorithms and discuss the evolution of the system.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":" 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140993094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-10DOI: 10.3389/fspas.2024.1369749
Seth H. Garland, Vasyl B. Yurchyshyn, R. Loper, Benjamin F. Akers, Daniel J. Emmons
Using non-linear force free field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-min cadence Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of 1 hour before through 1 hour after the start of 18 X-class and 12 M-class solar flares. Several magnetic field parameters were calculated from the modeled fields directly, as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis, for two different regions: areas with photospheric |Bz|≥ 300 G (active region—AR) and areas above the photosphere with the magnitude of the non-potential field (BNP) greater than three standard deviations above |BNP|̄ of the AR field and either the unsigned twist number |Tw| ≥ 1 turn or the shear angle Ψ ≥ 80° (non-potential region—NPR). Superposed epoch (SPE) plots of the magnetic field parameters were analyzed to investigate the evolution of the 3D solar field during the solar flare events and discern consistent trends across all solar flare events in the dataset, as well as across subsets of flare events categorized by their magnetic and sunspot classifications. The relationship between different flare properties and the magnetic field parameters was quantitatively described by the Spearman ranking correlation coefficient, rs. The parameters that showed the most consistent and discernable trends among the flare events, particularly for the hour leading up to the eruption, were the total unsigned flux ϕ), free magnetic energy (EFree), total unsigned magnetic twist (τTot), and total unsigned free magnetic twist (ρTot). Strong (|rs| ∈ [0.6, 0.8)) to very strong (|rs| ∈ [0.8, 1.0]) correlations were found between the magnetic field parameters and the following flare properties: peak X-ray flux, duration, rise time, decay time, impulsiveness, and integrated flux; the strongest correlation coefficient calculated for each flare property was 0.62, 0.85, 0.73, 0.82, −0.81, and 0.82, respectively.
{"title":"Analysis of modeled 3D solar magnetic field during 30 X/M-class solar flares","authors":"Seth H. Garland, Vasyl B. Yurchyshyn, R. Loper, Benjamin F. Akers, Daniel J. Emmons","doi":"10.3389/fspas.2024.1369749","DOIUrl":"https://doi.org/10.3389/fspas.2024.1369749","url":null,"abstract":"Using non-linear force free field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-min cadence Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of 1 hour before through 1 hour after the start of 18 X-class and 12 M-class solar flares. Several magnetic field parameters were calculated from the modeled fields directly, as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis, for two different regions: areas with photospheric |Bz|≥ 300 G (active region—AR) and areas above the photosphere with the magnitude of the non-potential field (BNP) greater than three standard deviations above |BNP|̄ of the AR field and either the unsigned twist number |Tw| ≥ 1 turn or the shear angle Ψ ≥ 80° (non-potential region—NPR). Superposed epoch (SPE) plots of the magnetic field parameters were analyzed to investigate the evolution of the 3D solar field during the solar flare events and discern consistent trends across all solar flare events in the dataset, as well as across subsets of flare events categorized by their magnetic and sunspot classifications. The relationship between different flare properties and the magnetic field parameters was quantitatively described by the Spearman ranking correlation coefficient, rs. The parameters that showed the most consistent and discernable trends among the flare events, particularly for the hour leading up to the eruption, were the total unsigned flux ϕ), free magnetic energy (EFree), total unsigned magnetic twist (τTot), and total unsigned free magnetic twist (ρTot). Strong (|rs| ∈ [0.6, 0.8)) to very strong (|rs| ∈ [0.8, 1.0]) correlations were found between the magnetic field parameters and the following flare properties: peak X-ray flux, duration, rise time, decay time, impulsiveness, and integrated flux; the strongest correlation coefficient calculated for each flare property was 0.62, 0.85, 0.73, 0.82, −0.81, and 0.82, respectively.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":" 91","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140991283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-09DOI: 10.3389/fspas.2024.1385820
A. Shalchi
Introduction: In this article, we revisit the pitch-angle scattering equation describing the propagation of energetic particles through magnetized plasma. In this case, solar energetic particles and cosmic rays interact with magnetohydrodynamic turbulence and experience stochastic changes in the pitch-angle. Since this happens over an extended period of time, a pitch-angle isotropization process occurs, leading to parallel spatial diffusion. This process is described well by the pitch-angle scattering equation. However, the latter equation is difficult to solve analytically even when considering special cases for the scattering coefficient.Methods: In the past, a so-called subspace approximation was proposed, which has important applications in the theory of perpendicular diffusion. Alternatively, an approach based on the telegraph equation (also known as telegrapher’s equation) has been developed. We show that two-dimensional subspace approximation and the description based on the telegraph equation are equivalent. However, it is also shown that the obtained distribution functions contain artifacts and inaccuracies that cannot be found in the numerical solution to the problem. Therefore, an N-dimensional subspace approximation is proposed corresponding to a semi-analytical/semi-numerical approach. This is a useful alternative compared to standard numerical solvers.Results and Discussion: Depending on the application, the N-dimensional subspace approximation can be orders of magnitude faster. Furthermore, the method can easily be modified so that it can be used for any pitch-angle scattering equation.
导言在这篇文章中，我们重温了描述高能粒子在磁化等离子体中传播的俯仰角散射方程。在这种情况下，太阳高能粒子和宇宙射线与磁流体湍流相互作用，并经历俯仰角的随机变化。由于这种情况会持续很长时间，因此会出现俯仰角同向化过程，从而导致平行空间扩散。俯仰角散射方程可以很好地描述这一过程。然而，即使考虑到散射系数的特殊情况，后一方程也很难分析求解：方法：过去曾提出过一种所谓的子空间近似法，它在垂直扩散理论中有着重要的应用。另外，还有一种基于电报方程（又称电报员方程）的方法。我们证明了二维子空间近似和基于电报方程的描述是等价的。然而，我们也证明了所获得的分布函数包含在问题的数值解中无法发现的人工痕迹和不准确性。因此，提出了一种与半分析/半数值方法相对应的 N 维子空间近似方法。与标准数值求解器相比，这是一种有用的替代方法：根据不同的应用，N 维子空间近似法的速度可以快上几个数量级。此外，该方法可以很容易地进行修改，从而可用于任何俯仰角散射方程。
{"title":"Transport of energetic particles in turbulent space plasmas: pitch-angle scattering, telegraph, and diffusion equations","authors":"A. Shalchi","doi":"10.3389/fspas.2024.1385820","DOIUrl":"https://doi.org/10.3389/fspas.2024.1385820","url":null,"abstract":"Introduction: In this article, we revisit the pitch-angle scattering equation describing the propagation of energetic particles through magnetized plasma. In this case, solar energetic particles and cosmic rays interact with magnetohydrodynamic turbulence and experience stochastic changes in the pitch-angle. Since this happens over an extended period of time, a pitch-angle isotropization process occurs, leading to parallel spatial diffusion. This process is described well by the pitch-angle scattering equation. However, the latter equation is difficult to solve analytically even when considering special cases for the scattering coefficient.Methods: In the past, a so-called subspace approximation was proposed, which has important applications in the theory of perpendicular diffusion. Alternatively, an approach based on the telegraph equation (also known as telegrapher’s equation) has been developed. We show that two-dimensional subspace approximation and the description based on the telegraph equation are equivalent. However, it is also shown that the obtained distribution functions contain artifacts and inaccuracies that cannot be found in the numerical solution to the problem. Therefore, an N-dimensional subspace approximation is proposed corresponding to a semi-analytical/semi-numerical approach. This is a useful alternative compared to standard numerical solvers.Results and Discussion: Depending on the application, the N-dimensional subspace approximation can be orders of magnitude faster. Furthermore, the method can easily be modified so that it can be used for any pitch-angle scattering equation.","PeriodicalId":507437,"journal":{"name":"Frontiers in Astronomy and Space Sciences","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140996758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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