scholarly journals Spatial distributions of ions and electrons from the plasma sheet to the inner magnetosphere: Comparisons between THEMIS-Geotail statistical results and the Rice convection model

2011 ◽  
Vol 116 (A11) ◽  
pp. n/a-n/a ◽  
Author(s):  
Chih-Ping Wang ◽  
Matina Gkioulidou ◽  
Larry R. Lyons ◽  
Richard A. Wolf ◽  
Vassilis Angelopoulos ◽  
...  
Keyword(s):  
Plasma Sheet ◽  
Spatial Distributions ◽  
Inner Magnetosphere ◽  
Rice Convection Model ◽  
Convection Model ◽  
Statistical Results

Interplay of bubble injections in the plasma sheet dynamics as inferred from RCM-I simulations

2020 ◽  
Author(s):  
Sina Sadeghzadeh ◽  
Jian Yang
Keyword(s):  
Plasma Sheet ◽  
High Speed ◽  
Space Environment ◽  
Inner Magnetosphere ◽  
Near Earth Space ◽  
Hot Plasma ◽  
Plasma Distribution ◽  
Rice Convection Model ◽  
Convection Model ◽  
Interchange Instability

<p><span>Understanding the transport of hot plasma from tail towards the inner magnetosphere is of great importance to improve our perception of the near-Earth space environment. In accordance with the recent observations, the contribution of bursty bulk flows (BBFs)/bubbles in the inner plasma sheet especially in the storm-time ring current formation is nonnegligible. These high-speed plasma flows with depleted flux tube/entropy are likely formed in the mid tail due to magnetic reconnection and injected earthward as a result of interchange instability. In this presentation, we investigate the interplay of these meso-scale structures on the average magnetic field and plasma distribution in various regions of the plasma sheet, using the Inertialized Rice Convection Model (RCM-I). We will discuss the comparison of our simulation results with the observational statistics and data-based empirical models.</span></p>

Numerical simulation of plasma transport in Saturn's inner magnetosphere using the Rice Convection Model

2010 ◽  
Vol 115 (A12) ◽  
pp. n/a-n/a ◽  
Author(s):  
X. Liu ◽  
T. W. Hill ◽  
R. A. Wolf ◽  
S. Sazykin ◽  
R. W. Spiro ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Plasma Transport ◽  
Inner Magnetosphere ◽  
Rice Convection Model ◽  
Convection Model

scholarly journals Rice Convection Model simulation of the substorm-associated injection of an observed bubble into the inner magnetosphere: 1. Magnetic field and other inputs

2009 ◽  
Vol 114 (A8) ◽  
pp. n/a-n/a ◽  
Author(s):  
J.-C. Zhang ◽  
R. A. Wolf ◽  
G. M. Erickson ◽  
R. W. Spiro ◽  
F. R. Toffoletto ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Model Simulation ◽  
Inner Magnetosphere ◽  
Rice Convection Model ◽  
Convection Model

Formation of the Harang reversal and its dependence on plasma sheet conditions: Rice convection model simulations

2009 ◽  
Vol 114 (A7) ◽  
pp. n/a-n/a ◽  
Author(s):  
Matina Gkioulidou ◽  
Chih-Ping Wang ◽  
Larry R. Lyons ◽  
Richard A. Wolf
Keyword(s):  
Plasma Sheet ◽  
Model Simulations ◽  
Rice Convection Model ◽  
Convection Model

Relationships of models of the inner magnetosphere to the Rice Convection Model

2001 ◽  
Vol 106 (A8) ◽  
pp. 15545-15554 ◽  
Author(s):  
M. Heinemann ◽  
R. A. Wolf
Keyword(s):  
Inner Magnetosphere ◽  
Rice Convection Model ◽  
Convection Model

scholarly journals Spatial Distribution of Plasma Sheet Entropy Reduction Caused by a Plasma Bubble: Rice Convection Model Simulations

2018 ◽  
Vol 123 (5) ◽  
pp. 3380-3397 ◽  
Author(s):  
Chih-Ping Wang ◽  
Matina Gkioulidou ◽  
Larry R. Lyons ◽  
Richard A. Wolf
Keyword(s):  
Spatial Distribution ◽  
Plasma Sheet ◽  
Plasma Bubble ◽  
Model Simulations ◽  
Rice Convection Model ◽  
Entropy Reduction ◽  
Convection Model

scholarly journals Modeling and Prediction of Near-Earth Plasma Sheet Parameters Using the Rice Convection Model and the Recurrent Neural Network

2021 ◽  
Vol 8 ◽  
Author(s):  
Shishir Priyadarshi ◽  
Jian Yang ◽  
Weiqin Sun
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Plasma Sheet ◽  
First Principles ◽  
Short Term Memory ◽  
Flux Transport ◽  
Training Time ◽  
Central Plasma ◽  
Rice Convection Model ◽  
Convection Model

Interaction between Earth’s magnetotail and its inner magnetosphere plays an important role in the transport of mass and energy in the ionosphere–magnetosphere coupled system. A number of first-principles models are devoted to understanding the associated dynamics. However, running these models, including both magnetohydrodynamic models and kinetic drift models, can be computationally expensive when self-consistency and high spatial resolution are required. In this study, we exploit an approach of building a parallel statistical model, based on the long short-term memory (LSTM) type of recurrent neural network, to forecast the results of a first-principles model, called the Rice Convection Model (RCM). The RCM is used to simulate the transient injection events, in which the flux-tube entropy parameter, dawn-to-dusk electric field component, and cumulative magnetic flux transport are calculated in the central plasma sheet. These key parameters are then used as initial inputs for training the LSTM. Using the trained LSTM multivariate parameters, we are able to forecast the plasma sheet parameters beyond the training time for several tens of minutes that are found to be consistent with the subsequent RCM simulation results. Our tests indicate that the recurrent neural network technique can be efficiently used for forecasting numerical simulations of magnetospheric models. The potential to apply this approach to other models is also discussed.

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