Bibliography



Found 7 entries in the Bibliography.


Showing entries from 1 through 7


2021

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 de ...

Zhelavskaya, I.; Aseev, N.; . Y. Shprits, Y;

YEAR: 2021     DOI: https://doi.org/10.1029/2020JA028077

plasmasphere; plasma density; neural networks; data assimilation; Kalman Filter; Machine learning; Van Allen Probes

2020

Quantifying the Effects of EMIC Wave Scattering and Magnetopause Shadowing in the Outer Electron Radiation Belt by Means of Data Assimilation

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 ...

Cervantes, S.; . Y. Shprits, Y; Aseev, N.; Allison, H.;

YEAR: 2020     DOI: https://doi.org/10.1029/2020JA028208

data assimilation; EMIC waves; magnetopause shadowing; innovation vector; Kalman Filter; radiation belt losses; Van Allen Probes

2019

Reanalysis of Ring Current Electron Phase Space Densities Using Van Allen Probe Observations, Convection Model, and Log-Normal Kalman Filter

Aseev, N.; . Y. Shprits, Y;

YEAR: 2019     DOI: 10.1029/2018SW002110

data assimilation; inner magnetosphere; Kalman Filter; Reanalysis; ring current; Van Allen Probes

Reanalysis of ring current electron phase space densities using Van Allen Probe observations, convection model, and log-normal Kalman filter

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 convec ...

Aseev, N.A.; Shprits, Y.Y.;

YEAR: 2019     DOI: 10.1029/2018SW002110

data assimilation; inner magnetosphere; Kalman Filter; Reanalysis; ring current; Van Allen Probes

2017

Simultaneous event-specific estimates of transport, loss, and source rates for relativistic outer radiation belt electrons

The most significant unknown regarding relativistic electrons in Earth\textquoterights outer Van Allen radiation belt is the relative contribution of loss, transport, and acceleration processes within the inner magnetosphere. Detangling each individual process is critical to improve the understanding of radiation belt dynamics, but determining a single component is challenging due to sparse measurements in diverse spatial and temporal regimes. However, there are currently an unprecedented number of spacecraft taking measurem ...

Schiller, Q.; Tu, W.; Ali, A.; Li, X.; Godinez, H.; Turner, D.; Morley, S.; Henderson, M.;

YEAR: 2017     DOI: 10.1002/2016JA023093

CubeSat; data assimilation; electron; event specific; Modeling; Radiation belt; Van Allen Probes

2016

Ring Current Pressure Estimation with RAM-SCB using Data Assimilation and Van Allen Probe Flux Data

Capturing and subsequently modeling the influence of tail plasma injections on the inner magnetosphere is important for understanding the formation and evolution of the ring current. In this study, the ring current distribution is estimated with the Ring Current-Atmosphere Interactions Model with Self-Consistent Magnetic field (RAM-SCB) using, for the first time, data assimilation techniques and particle flux data from the Van Allen Probes. The state of the ring current within the RAM-SCB model is corrected via an ensemble b ...

Godinez, Humberto; Yu, Yiqun; Lawrence, Eric; Henderson, Michael; Larsen, Brian; Jordanova, Vania;

YEAR: 2016     DOI: 10.1002/2016GL071646

data assimilation; ring current; Van Allen Probes

2013

Application of a new data operator-splitting data assimilation technique to the 3-D VERB diffusion code and CRRES measurements

In this study we present 3-D data assimilation using CRRES data and 3-D Versatile Electron Radiation Belt Model (VERB) using a newly developed operator-splitting method. Simulations with synthetic data show that the operator-splitting Kalman filtering technique proposed in this study can successfully reconstruct the underlying dynamic evolution of the radiation belts. The method is further verified by the comparison with the conventional Kalman filter. We applied the new approach to 3-D data assimilation of real data to glob ...

Shprits, Yuri; Kellerman, Adam; Kondrashov, Dmitri; Subbotin, Dmitriy;

YEAR: 2013     DOI: 10.1002/grl.50969

data assimilation; Modeling; Radiation belts



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