Found 14 entries in the Bibliography.
Showing entries from 1 through 14
Abstract Reconstruction and prediction of the state of the near-Earth space environment is important for anomaly analysis, development of empirical models and understanding of physical processes. Accurate reanalysis or predictions that account for uncertainties in the associated model and the observations, can be obtained by means of data assimilation. The ensemble Kalman filter (EnKF) is one of the most promising filtering tools for non-linear and high dimensional systems in the context of terrestrial weather prediction. In this study, we adapt traditional ensemble based filtering methods to perform data assimilation in the radiation belts. By performing a fraternal twin experiment, we assess the convergence of the EnKF to the standard Kalman filter (KF). Furthermore, with the split-operator technique, we develop two new three-dimensional EnKF approaches for electron phase space density that account for radial and local processes, and allow for reconstruction of the full 3D radiation belt space. The capabilities and properties of the proposed filter approximations are verified using Van Allen Probe and GOES data. Additionally, we validate the two 3D split-operator Ensemble Kalman filters against the 3D split-operator KF. We show how the use of the split-operator technique allows us to include more physical processes in our simulations and offers computationally efficient data assimilation tools that deliver accurate approximations to the optimal solution of the KF and are suitable for real-time forecasting. Future applications of the EnKF to direct assimilation of fluxes and non-linear estimation of electron lifetimes are discussed.
Published by: Space Weather Published on: 08/2021
YEAR: 2021   DOI: https://doi.org/10.1029/2020SW002672
AbstractRadial diffusion is one of the dominant physical mechanisms driving acceleration and loss of radiation belt electrons. A number of parameterizations for radial diffusion coefficients have been developed, each differing in the dataset used. Here, we investigate the performance of different parameterizations by Brautigam and Albert (2000), Brautigam et al. (2005), Ozeke et al. (2014), Ali et al. (2015); Ali et al. (2016); Ali (2016), and Liu et al. (2016) on long-term radiation belt modeling using the Versatile Electron Radiation Belt (VERB) code, and compare the results to Van Allen Probes observations. First, 1-D radial diffusion simulations are performed, isolating the contribution of solely radial diffusion. We then take into account effects of local acceleration and loss showing additional 3-D simulations, including diffusion across pitch-angle, energy, and mixed diffusion. For the L* range studied, the difference between simulations with Brautigam and Albert (2000), Ozeke et al. (2014), and Liu et al. (2016) parameterizations is shown to be small, with Brautigam and Albert (2000) offering the smallest averaged (across multiple energies) absolute normalized difference with observations. Using the Ali et al. (2016) parameterization tended to result in a lower flux than both the observations and the VERB simulations using the other coefficients. We find that the 3-D simulations are less sensitive to the radial diffusion coefficient chosen than the 1-D simulations, suggesting that for 3-D radiation belt models, a similar result is likely to be achieved, regardless of whether Brautigam and Albert (2000), Ozeke et al. (2014), and Liu et al. (2016) parameterizations are used.This article is protected by copyright. All rights reserved.
Published by: Journal of Geophysical Research: Space Physics Published on: 07/2021
YEAR: 2021   DOI: https://doi.org/10.1029/2020JA028707
Abstract Following the end of the Van Allen Probes mission, the Arase satellite offers a unique opportunity to continue in-situ radiation belt and ring current particle measurements into the next solar cycle. In this study we compare spin-averaged flux measurements from the MEPe, HEP-L, HEP-H, and XEP-SSD instruments on Arase with those from the MagEIS and REPT instruments on the Van Allen Probes, calculating Pearson correlation coefficient and the mean ratio of fluxes at L* conjunctions between the spacecraft. Arase and Van Allen Probes measurements show a close agreement over a wide range of energies, observing a similar general evolution of electron flux, as well as average, peak, and minimum values. Measurements from the two missions agree especially well in the 3.6 ≤ L* ≤ 4.4 range where Arase samples similar magnetic latitudes to Van Allen Probes. Arase tends to record higher flux for energies < 670 keV with longer decay times after flux enhancements, particularly for L* < 3.6 . Conversely, for energies > 1.4 MeV, Arase flux measurements are generally lower than those of Van Allen Probes, especially for L* > 4.4 . The correlation coefficient values show that the > 1.4 MeV flux from both missions are well correlated, indicating a similar general evolution, although flux magnitudes differ. We perform a preliminary intercalibration between the two missions using the mean ratio of the fluxes as an energy- and L*- dependent intercalibration factor. The intercalibration factor improves agreement between the fluxes in the 0.58-1 MeV range. This article is protected by copyright. All rights reserved.
Szabó-Roberts, Mátyás; Shprits, Yuri; Allison, Hayley; Vasile, Ruggero; Smirnov, Artem; Aseev, Nikita; Drozdov, Alexander; Miyoshi, Yoshizumi; Claudepierre, Seth; Kasahara, Satoshi; Yokota, Shoichiro; Mitani, Takefumi; Takashima, Takeshi; Higashio, Nana; Hori, Tomo; Keika, Kunihiro; Imajo, Shun; Shinohara, Iku;
Published by: Journal of Geophysical Research: Space Physics Published on: 06/2021
YEAR: 2021   DOI: https://doi.org/10.1029/2020JA028929
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.
Published by: Journal of Geophysical Research: Space Physics Published on: 02/2021
YEAR: 2021   DOI: https://doi.org/10.1029/2020JA028077
In this study we investigate two distinct loss mechanisms responsible for the rapid dropouts of radiation belt electrons by assimilating data from Van Allen Probes A and B and Geostationary Operational Environmental Satellites (GOES) 13 and 15 into a 3-D diffusion model. In particular, we examine the respective contribution of electromagnetic ion cyclotron (EMIC) wave scattering and magnetopause shadowing for values of the first adiabatic invariant μ ranging from 300 to 3,000 MeV G−1. We inspect the innovation vector and perform a statistical analysis to quantitatively assess the effect of both processes as a function of various geomagnetic indices, solar wind parameters, and radial distance from the Earth. Our results are in agreement with previous studies that demonstrated the energy dependence of these two mechanisms. We show that EMIC wave scattering tends to dominate loss at lower L shells, and it may amount to between 10\%/hr and 30\%/hr of the maximum value of phase space density (PSD) over all L shells for fixed first and second adiabatic invariants. On the other hand, magnetopause shadowing is found to deplete electrons across all energies, mostly at higher L shells, resulting in loss from 50\%/hr to 70\%/hr of the maximum PSD. Nevertheless, during times of enhanced geomagnetic activity, both processes can operate beyond such location and encompass the entire outer radiation belt.
Published by: Journal of Geophysical Research: Space Physics Published on: 08/2020
YEAR: 2020   DOI: https://doi.org/10.1029/2020JA028208
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.
Published by: Journal of Geophysical Research: Space Physics Published on: 04/2020
YEAR: 2020   DOI: 10.1029/2019JA027422
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.
Published by: Journal of Geophysical Research: Space Physics Published on: 04/2020
YEAR: 2020   DOI: https://doi.org/10.1029/2019JA027422
During geomagnetic storms, the rapid depletion of the high-energy (several MeV) outer radiation belt electrons is the result of loss to the interplanetary medium through the magnetopause, outward radial diffusion, and loss to the atmosphere due to wave-particle interactions. We have performed a statistical study of 110 storms using pitch angle resolved electron flux measurements from the Van Allen Probes mission and found that inside of the radiation belt (L* = 3 - 5) the number of storms that result in depletion of electrons with equatorial pitch angle αeq = 30o is higher than number of storms that result in depletion of electrons with equatorial pitch angle αeq = 75o. We conclude that this result is consistent with electron scattering by whistler and electromagnetic ion cyclotron waves. At the outer edge of the radiation belt (L* >= 5.2) the number of storms that result in depletion is also large (~40\textendash50\%), emphasizing the significance of the magnetopause shadowing effect and outward radial transport.
Published by: Journal of Geophysical Research: Space Physics Published on: 11/2019
YEAR: 2019   DOI: 10.1029/2019JA027332
Published by: Space Weather Published on: 04/2019
YEAR: 2019   DOI: 10.1029/2018SW002110
Models of ring current electron dynamics unavoidably contain uncertainties in boundary conditions, electric and magnetic fields, electron scattering rates, and plasmapause location. Model errors can accumulate with time and result in significant deviations of model predictions from observations. Data assimilation offers useful tools which can combine physics-based models and measurements to improve model predictions. In this study, we systematically analyze performance of the Kalman filter applied to a log-transformed convection model of ring current electrons and Van Allen Probe data. We consider long-term dynamics of μ = 2.3 MeV/G and K = 0.3 G1/2RE electrons from 1 February 2013 to 16 June 2013. By using synthetic data, we show that the Kalman filter is capable of correcting errors in model predictions associated with uncertainties in electron lifetimes, boundary conditions, and convection electric fields. We demonstrate that reanalysis retains features which cannot be fully reproduced by the convection model such as storm-time earthward propagation of the electrons down to 2.5 RE. The Kalman filter can adjust model predictions to satellite measurements even in regions where data are not available. We show that the Kalman filter can adjust model predictions in accordance with observations for μ = 0.1, 2.3, and 9.9 MeV/G and constant K = 0.3 G1/2RE electrons. The results of this study demonstrate that data assimilation can improve performance of ring current models, better quantify model uncertainties, and help deeper understand the physics of the ring current particles.
Published by: Space Weather Published on: 04/2019
YEAR: 2019   DOI: 10.1029/2018SW002110
The Cluster mission, launched in 2000, has produced a large database of electron flux intensity measurements in the Earth\textquoterights magnetosphere by the Research with Adaptive Particle Imaging Detector (RAPID)/ Imaging Electron Spectrometer (IES) instrument. However, due to background contamination of the data with high-energy electrons (<400 keV) and inner-zone protons (230-630 keV) in the radiation belts and ring current, the data have been rarely used for inner-magnetospheric science. The current paper presents two algorithms for background correction. The first algorithm is based on the empirical contamination percentages by both protons and electrons. The second algorithm uses simultaneous proton observations. The efficiencies of these algorithms are demonstrated by comparison of the corrected Cluster/RAPID/IES data with Van Allen Probes/Magnetic Electron Ion Spectrometer (MagEIS) measurements for 2012-2015. Both techniques improved the IES electron data in the radiation belts and ring current, as the yearly averaged flux intensities of the two missions show the ratio of measurements close to 1. We demonstrate a scientific application of the corrected IES electron data analyzing its evolution during solar cycle. Spin-averaged yearly mean IES electron intensities in the outer belt for energies 40-400 keV at L-shells between 4 and 6 showed high positive correlation with AE index and solar wind dynamic pressure during 2001- 2016. The relationship between solar wind dynamic pressure and IES electron measurements in the outer radiation belt was derived as a uniform linear-logarithmic equation.
Published by: Space Weather Published on: 02/2019
YEAR: 2019   DOI: 10.1029/2018SW001989
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.
Published by: Journal of Geophysical Research: Space Physics Published on: 09/2017
YEAR: 2017   DOI: 10.1002/2017JA024485
Electromagnetic ion cyclotron (EMIC) waves play an important role in the dynamics of ultrarelativistic electron population in the radiation belts. However, as EMIC waves are very sporadic, developing a parameterization of such wave properties is a challenging task. Currently, there are no dynamic, activity-dependent models of EMIC waves that can be used in the long-term (several months) simulations, which makes the quantitative modeling of the radiation belt dynamics incomplete. In this study, we investigate Kp, Dst, and AE indices, solar wind speed, and dynamic pressure as possible parameters of EMIC wave presence. The EMIC waves are included in the long-term simulations (1 year, including different geomagnetic activity) performed with the Versatile Electron Radiation Belt code, and we compare results of the simulation with the Van Allen Probes observations. The comparison shows that modeling with EMIC waves, parameterized by solar wind dynamic pressure, provides a better agreement with the observations among considered parameterizations. The simulation with EMIC waves improves the dynamics of ultrarelativistic fluxes and reproduces the formation of the local minimum in the phase space density profiles.
Published by: Journal of Geophysical Research: Space Physics Published on: 08/2017
YEAR: 2017   DOI: 10.1002/2017JA024389
Radial diffusion is one of the dominant physical mechanisms that drives acceleration and loss of the radiation belt electrons, which makes it very important for nowcasting and forecasting space weather models. We investigate the sensitivity of the two parameterizations of the radial diffusion of Brautigam and Albert (2000) and Ozeke et al. (2014) on long-term radiation belt modeling using the Versatile Electron Radiation Belt (VERB). Following Brautigam and Albert (2000) and Ozeke et al. (2014), we first perform 1-D radial diffusion simulations. Comparison of the simulation results with observations shows that the difference between simulations with either radial diffusion parameterization is small. To take into account effects of local acceleration and loss, we perform 3-D simulations, including pitch angle, energy, and mixed diffusion. We found that the results of 3-D simulations are even less sensitive to the choice of parameterization of radial diffusion rates than the results of 1-D simulations at various energies (from 0.59 to 1.80 MeV). This result demonstrates that the inclusion of local acceleration and pitch angle diffusion can provide a negative feedback effect, such that the result is largely indistinguishable simulations conducted with different radial diffusion parameterizations. We also perform a number of sensitivity tests by multiplying radial diffusion rates by constant factors and show that such an approach leads to unrealistic predictions of radiation belt dynamics.
Published by: Space Weather Published on: 01/2017
YEAR: 2017   DOI: 10.1002/swe.v15.110.1002/2016SW001426