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Found 12 entries in the Bibliography.
Showing entries from 1 through 12
| 2021 |
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Abstract We present a comparison of magnetospheric plasma mass/electron density observations during an 11-day interval which includes the geomagnetic storm of 22 June 2015. For this study we used: equatorial plasma mass density derived from geomagnetic field line resonances (FLRs) detected by Van Allen Probes and at the ground-based magnetometer networks EMMA and CARISMA; in situ electron density inferred by the Neural-network-based Upper hybrid Resonance Determination algorithm applied to plasma wave Van Allen Probes measurements. The combined observations at L ∼ 4, MLT ∼ 16 of the two longitudinally-separated magnetometer networks show a temporal pattern very similar to that of the in situ observations: a density decrease by an order of magnitude about 1 day after the Dst minimum, a partial recovery a few hours later, and a new strong decrease soon after. The observations are consistent with the position of the measurement points with respect to the plasmasphere boundary as derived by a plasmapause test particle simulation. A comparison between plasma mass densities derived from ground and in situ FLR observations during favourable conjunctions shows a good agreement. We find however, for L < ∼3, the spacecraft measurements to be higher than the corresponding ground observations with increasing deviation with decreasing L, which might be related to the rapid outbound spacecraft motion in that region. A statistical analysis of the average ion mass using simultaneous spacecraft measurements of mass and electron density indicates values close to 1 amu in plasmasphere and higher values (∼ 2-3 amu) in plasmatrough. This article is protected by copyright. All rights reserved. Vellante, M.; Takahashi, K.; Del Corpo, A.; Zhelavskaya, I.; Goldstein, J.; Mann, I.; Pietropaolo, E.; Reda, J.; Heilig, B.; Published by: Journal of Geophysical Research: Space Physics Published on: 06/2021 YEAR: 2021 DOI: https://doi.org/10.1029/2021JA029292 magnetoseismology; plasmasphere; Field line resonance; ground-based magnetometers; Van Allen Probes; Swarm satellites |
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A Comparison of the Location of the Mid-latitude Trough and Plasmapause Boundary Abstract We have compared the location of the mid-latitude trough observed in two dimensional vertical total electron content (vTEC) maps with four plasmapause boundary models, Radiation Belt Storm Probes observations, and IMAGE EUV observations all mapped to the ionosphere pierce point using the Tsyganenko [1996] magnetic field line model. For this study we examine four events over North America: one just after the 13 October 2012 storm, one during the 20 April 2002 double storm, another during a large substorm on 26 January 2013, and one quiet event on 19 May 2001. We have found that in general, the equatorward edge of the mid-latitude trough is within several degrees in geographic latitude of the mapped model plasmapause boundary location, the plasmapause boundary identified with IMAGE EUV, and the location identified by the Radiation Belt Storm Probes spacecraft. When the mid-latitude trough is mapped to the inner magnetosphere, the observed boundary agrees with the plasmapause boundary models within 2 Earth Radii at nearly all local times in the nightside and the observed mid-latitude boundary is within the uncertainty of the observations at most local times in the nightside. Furthermore, during dynamic solar wind conditions of 20 April 2002, the mid-latitude trough observed in the vTEC maps propagates equatorward as the plasmapause boundary identified with IMAGE EUV moves earthward. Our results indicate that the mid-latitude trough observed within the vTEC maps represents an additional means of identifying the plasmapause boundary location, which could result in improved plasmapause boundary models. This article is protected by copyright. All rights reserved. Weygand, J.M.; Zhelavskaya, I.; Shprits, Y.; Published by: Journal of Geophysical Research: Space Physics Published on: 03/2021 YEAR: 2021 DOI: https://doi.org/10.1029/2020JA028213 mid-latitude trough; plasmapause boundary; vTECs; plasmapause models; Van Allen Probes |
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Reconstruction of the Radiation Belts for Solar Cycles 17 – 24 (1933 – 2017) AbstractWe present a reconstruction of the dynamics of the radiation belts from Solar Cycles 17 – 24 which allows us to study how radiation belt activity has varied between the different solar cycles. The radiation belt simulations are produced using the Versatile Electron Radiation Belt (VERB)-3D code. The VERB-3D code simulations incorporate radial, energy, and pitch angle diffusion to reproduce the radiation belts. Our simulations use the historical measurements of Kp (available since Solar Cycle 17, i.e., 1933) to model the evolution radiation belt dynamics between L* = 1 – 6.6. A nonlinear auto regressive network with exogenous inputs (NARX) neural network was trained off GOES 15 measurements (Jan. 2011 – March 2014) and used to supply the upper boundary condition (L* = 6.6) over the course of Solar Cycles 17 – 24 (i.e., 1933 – 2017). Comparison of the model with long term observations of the Van Allen Probes and CRRES demonstrates that our model, driven by the NARX boundary, can reconstruct the general evolution of the radiation belt fluxes. Solar Cycle 24 (Jan 2008 – 2017) has been the least active of the considered solar cycles which resulted in unusually low electron fluxes. Our results show that Solar Cycle 24 should not be used as a representative solar cycle for developing long term environment models. The developed reconstruction of fluxes can be used to develop or improve empirical models of the radiation belts.This article is protected by copyright. All rights reserved. Saikin, A.; Shprits, Y; Drozdov, A; Landis, D.; Zhelavskaya, I.; Cervantes, S.; Published by: Space Weather Published on: 02/2021 YEAR: 2021 DOI: https://doi.org/10.1029/2020SW002524 Radiation belts; numerical modeling; Particle acceleration; Magnetosphere: inner; forecasting; Van Allen Probes |
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A combined neural network- and physics-based approach for modeling plasmasphere dynamics AbstractIn recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These neural network-based models capture the large-scale dynamics of the plasmasphere, such as plume formation and erosion of the plasmasphere on the nightside. However, their performance depends strongly on the availability of training data. When the data coverage is limited or non-existent, as occurs during geomagnetic storms, the performance of NNs significantly decreases, as networks inherently cannot learn from the limited number of examples. This limitation can be overcome by employing physics-based modeling during strong geomagnetic storms. Physics-based models show a stable performance during periods of disturbed geomagnetic activity, if they are correctly initialized and configured. In this study, we illustrate how to combine the neural network- and physics-based models of the plasmasphere in an optimal way by using data assimilation. The proposed approach utilizes advantages of both neural network- and physics-based modeling and produces global plasma density reconstructions for both quiet and disturbed geomagnetic activity, including extreme geomagnetic storms. We validate the models quantitatively by comparing their output to the in-situ density measurements from RBSP-A for an 18-month out-of-sample period from 30 June 2016 to 01 January 2018, and computing performance metrics. To validate the global density reconstructions qualitatively, we compare them to the IMAGE EUV images of the He+ particle distribution in the Earth s plasmasphere for a number of events in the past, including the Halloween storm in 2003.This article is protected by copyright. All rights reserved. Zhelavskaya, I.; Aseev, N.; Shprits, Y; Published by: Journal of Geophysical Research: Space Physics Published on: 02/2021 YEAR: 2021 DOI: https://doi.org/10.1029/2020JA028077 plasmasphere; plasma density; neural networks; data assimilation; Kalman Filter; Machine learning; Van Allen Probes |
| 2020 |
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Bayesian Inference of Quasi-Linear Radial Diffusion Parameters using Van Allen Probes Abstract The Van Allen radiation belts in the magnetosphere have been extensively studied using models based on radial diffusion theory, which is derived from a quasi-linear approach with prescribed inner and outer boundary conditions. The 1D diffusion model requires the knowledge of a diffusion coefficient and an electron loss timescale, which is typically parameterized in terms of various quantities such as the spatial (L) coordinate or a geomagnetic index (e.g., Kp). These terms are typically empirically derived, not directly measurable, and hence are not known precisely, due to the inherent nonlinearity of the process and the variable boundary conditions. In this work, we demonstrate a probabilistic approach by inferring the values of the diffusion and loss term parameters, along with their uncertainty, in a Bayesian framework, where identification is obtained using the Van Allen Probe measurements. Our results show that the probabilistic approach statistically improves the performance of the model, compared to the empirical parameterization employed in the literature. Sarma, Rakesh; Chandorkar, Mandar; Zhelavskaya, Irina; Shprits, Yuri; Drozdov, Alexander; Camporeale, Enrico; Published by: Journal of Geophysical Research: Space Physics Published on: 04/2020 YEAR: 2020 DOI: 10.1029/2019JA027618 radial diffusion; Magnetosphere; Bayesian inference; Van Allen radiation belt; Van Allen Probes |
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The Effect of Plasma Boundaries on the Dynamic Evolution of Relativistic Radiation Belt Electrons Abstract Understanding the dynamic evolution of relativistic electrons in the Earth s radiation belts during both storm and nonstorm times is a challenging task. The U.S. National Science Foundation s Geospace Environment Modeling (GEM) focus group “Quantitative Assessment of Radiation Belt Modeling” has selected two storm time and two nonstorm time events that occurred during the second year of the Van Allen Probes mission for in-depth study. Here, we perform simulations for these GEM challenge events using the 3D Versatile Electron Radiation Belt code. We set up the outer L* boundary using data from the Geostationary Operational Environmental Satellites and validate the simulation results against satellite observations from both the Geostationary Operational Environmental Satellites and Van Allen Probe missions for 0.9-MeV electrons. Our results show that the position of the plasmapause plays a significant role in the dynamic evolution of relativistic electrons. The magnetopause shadowing effect is included by using last closed drift shell, and it is shown to significantly contribute to the dropouts of relativistic electrons at high L*. We perform simulations using four different empirical radial diffusion coefficient models for the GEM challenge events, and the results show that these simulations reproduce the general dynamic evolution of relativistic radiation belt electrons. However, in the events shown here, simulations using the radial diffusion coefficients from Brautigam and Albert (2000) produce the best agreement with satellite observations. Wang, Dedong; Shprits, Yuri; Zhelavskaya, Irina; Effenberger, Frederic; Castillo, Angelica; Drozdov, Alexander; Aseev, Nikita; Cervantes, Sebastian; Published by: Journal of Geophysical Research: Space Physics Published on: 04/2020 YEAR: 2020 DOI: 10.1029/2019JA027422 Radiation belt; simulation; relativistic electrons; magnetopause shadowing; Wave-particle interaction; Plasmapause; Van Allen Probes |
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Bayesian Inference of Quasi-Linear Radial Diffusion Parameters using Van Allen Probes The Van Allen radiation belts in the magnetosphere have been extensively studied using models based on radial diffusion theory, which is derived from a quasi-linear approach with prescribed inner and outer boundary conditions. The 1D diffusion model requires the knowledge of a diffusion coefficient and an electron loss timescale, which is typically parameterized in terms of various quantities such as the spatial (L) coordinate or a geomagnetic index (e.g., Kp). These terms are typically empirically derived, not directly measurable, and hence are not known precisely, due to the inherent nonlinearity of the process and the variable boundary conditions. In this work, we demonstrate a probabilistic approach by inferring the values of the diffusion and loss term parameters, along with their uncertainty, in a Bayesian framework, where identification is obtained using the Van Allen Probe measurements. Our results show that the probabilistic approach statistically improves the performance of the model, compared to the empirical parameterization employed in the literature. Sarma, Rakesh; Chandorkar, Mandar; Zhelavskaya, Irina; Shprits, Yuri; Drozdov, Alexander; Camporeale, Enrico; Published by: Journal of Geophysical Research: Space Physics Published on: 04/2020 YEAR: 2020 DOI: https://doi.org/10.1029/2019JA027618 radial diffusion; Magnetosphere; Bayesian inference; Van Allen radiation belt; Van Allen Probes |
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The Effect of Plasma Boundaries on the Dynamic Evolution of Relativistic Radiation Belt Electrons Understanding the dynamic evolution of relativistic electrons in the Earth s radiation belts during both storm and nonstorm times is a challenging task. The U.S. National Science Foundation s Geospace Environment Modeling (GEM) focus group “Quantitative Assessment of Radiation Belt Modeling” has selected two storm time and two nonstorm time events that occurred during the second year of the Van Allen Probes mission for in-depth study. Here, we perform simulations for these GEM challenge events using the 3D Versatile Electron Radiation Belt code. We set up the outer L* boundary using data from the Geostationary Operational Environmental Satellites and validate the simulation results against satellite observations from both the Geostationary Operational Environmental Satellites and Van Allen Probe missions for 0.9-MeV electrons. Our results show that the position of the plasmapause plays a significant role in the dynamic evolution of relativistic electrons. The magnetopause shadowing effect is included by using last closed drift shell, and it is shown to significantly contribute to the dropouts of relativistic electrons at high L*. We perform simulations using four different empirical radial diffusion coefficient models for the GEM challenge events, and the results show that these simulations reproduce the general dynamic evolution of relativistic radiation belt electrons. However, in the events shown here, simulations using the radial diffusion coefficients from Brautigam and Albert (2000) produce the best agreement with satellite observations. Wang, Dedong; Shprits, Yuri; Zhelavskaya, Irina; Effenberger, Frederic; Castillo, Angelica; Drozdov, Alexander; Aseev, Nikita; Cervantes, Sebastian; Published by: Journal of Geophysical Research: Space Physics Published on: 04/2020 YEAR: 2020 DOI: https://doi.org/10.1029/2019JA027422 Radiation belt; simulation; relativistic electrons; magnetopause shadowing; Wave-particle interaction; Plasmapause; Van Allen Probes |
| 2018 |
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We perform a statistical study calculating electromagnetic ion cyclotron (EMIC) wave amplitudes based off in situ plasma measurements taken by the Van Allen Probes\textquoteright (1.1\textendash5.8 Re) Helium, Oxygen, Proton, Electron (HOPE) instrument. Calculated wave amplitudes are compared to EMIC waves observed by the Electric and Magnetic Field Instrument Suite and Integrated Science on board the Van Allen Probes during the same period. The survey covers a 22-month period (1 November 2012 to 31 August 2014), a full Van Allen Probe magnetic local time (MLT) precession. The linear theory proxy was used to identify EMIC wave events with plasma conditions favorable for EMIC wave excitation. Two hundred and thirty-two EMIC wave events (103 H+-band and 129 He+-band) were selected for this comparison. Nearly all events selected are observed beyond L = 4. Results show that calculated wave amplitudes exclusively using the in situ HOPE measurements produce amplitudes too low compared to the observed EMIC wave amplitudes. Hot proton anisotropy (Ahp) distributions are asymmetric in MLT within the inner (L < 7) magnetosphere with peak (minimum) Ahp, \~0.81 to 1.00 (\~0.62), observed in the dawn (dusk), 0000 < MLT <= 1200 (1200 < MLT <= 2400), sectors. Measurements of Ahp are found to decrease in the presence of EMIC wave activity. Ahp amplification factors are determined and vary with respect to EMIC wave-band and MLT. He+-band events generally require double (quadruple) the measured Ahp for the dawn (dusk) sector to reproduce the observed EMIC wave amplitudes. Saikin, A.A.; Jordanova, V.K.; Zhang, J.C.; Smith, C.W.; Spence, H.E.; Larsen, B.A.; Reeves, G.D.; Torbert, R.B.; Kletzing, C.A.; Zhelavskaya, I.S.; Shprits, Y.Y.; Published by: Journal of Atmospheric and Solar-Terrestrial Physics Published on: 02/2018 YEAR: 2018 DOI: 10.1016/j.jastp.2018.01.024 EMIC waves Van Allen Probes Linear theory Wave generation; Van Allen Probes |
| 2017 |
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Empirical modeling of the plasmasphere dynamics using neural networks We propose a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural-network-based Upper hybrid Resonance Determination) algorithm for the period of October 1, 2012 - July 1, 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2<=L<=6 and all local times. We validate and test the model by measuring its performance on independent datasets withheld from the training set and by comparing the model predicted global evolution with global images of He+ distribution in the Earth\textquoterights plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). The optimal model is based on the 96-hour time history of Kp, AE, SYM-H, and F10.7 indices. The model successfully reproduces erosion of the plasmasphere on the night side and plume formation and evolution. We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in-situ observations by using machine learning techniques. Zhelavskaya, Irina; Shprits, Yuri; c, Maria; Published by: Journal of Geophysical Research: Space Physics Published on: 10/2017 YEAR: 2017 DOI: 10.1002/2017JA024406 inner magnetosphere; Machine learning; Models; neural networks; plasmasphere; Van Allen Probes |
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Up until recently, signatures of the ultrarelativistic electron loss driven by electromagnetic ion cyclotron (EMIC) waves in the Earth\textquoterights outer radiation belt have been limited to direct or indirect measurements of electron precipitation or the narrowing of normalized pitch angle distributions in the heart of the belt. In this study, we demonstrate additional observational evidence of ultrarelativistic electron loss that can be driven by resonant interaction with EMIC waves. We analyzed the profiles derived from Van Allen Probe particle data as a function of time and three adiabatic invariants between 9 October and 29 November 2012. New local minimums in the profiles are accompanied by the narrowing of normalized pitch angle distributions and ground-based detection of EMIC waves. Such a correlation may be indicative of ultrarelativistic electron precipitation into the Earth\textquoterights atmosphere caused by resonance with EMIC waves. Aseev, N.; Shprits, Y; Drozdov, A; Kellerman, A.; Usanova, M.; Wang, D.; Zhelavskaya, I.; Published by: Journal of Geophysical Research: Space Physics Published on: 09/2017 YEAR: 2017 DOI: 10.1002/2017JA024485 electron loss; EMIC waves; Radiation belts; ultrarelativistic electrons; Van Allen Probes; wave-particle interactions |
| 2016 |
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We present the Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm for automatic inference of the electron number density from plasma wave measurements made on board NASA\textquoterights Van Allen Probes mission. A feedforward neural network is developed to determine the upper hybrid resonance frequency, fuhr, from electric field measurements, which is then used to calculate the electron number density. In previous missions, the plasma resonance bands were manually identified, and there have been few attempts to do robust, routine automated detections. We describe the design and implementation of the algorithm and perform an initial analysis of the resulting electron number density distribution obtained by applying NURD to 2.5 years of data collected with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite of the Van Allen Probes mission. Densities obtained by NURD are compared to those obtained by another recently developed automated technique and also to an existing empirical plasmasphere and trough density model. Zhelavskaya, I.; Spasojevic, M.; Shprits, Y; Kurth, W.; Published by: Journal of Geophysical Research: Space Physics Published on: 05/2016 YEAR: 2016 DOI: 10.1002/2015JA022132 |
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