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Diffusion Coefficients of Chorus Waves

This dataset provides diffusion coefficients of chorus waves, which are essential for understanding the scattering and transport of energetic particles in Earth's magnetosphere. The data were generated using the Full Diffusion Code (FDC) (Ni et al., 2008; Shprits and Ni, 2009; Orlova and Shprits, 2011), a widely employed tool in diffusion coefficient studies, and have been used in our research to model wave-particle interactions. By making this dataset available, we aim to support the broader scientific community in their investigations of magnetospheric dynamics and particle behavior. The dataset includes diffusion coefficients for both upper and lower band chorus waves and is organized into three folders: • UBC: Diffusion coefficients for the upper chorus frequency band. • LBC_Low_till20: Diffusion coefficients for the lower chorus frequency band up to 20° latitude. • LBC_Mid_20-45: Diffusion coefficients for the lower chorus frequency band between 20° and 45° latitude.

The 3-rd Order Polynomial Fit Coefficients of Electron Lifetime Caused by Interaction with Chorus Waves

In near-Earth space, a large population of high-energy electrons are trapped by Earth’s magnetic field. These energetic electrons are trapped in the regions called Earth’s ring current and radiation belts. They are very dynamic and show a very strong dependence on solar wind and geomagnetic conditions. These energetic electrons can be dangerous to satellites in the near-Earth space. Therefore, it is very important to understand the mechanisms which drive the dynamics of these energetic electrons. Wave-particle interaction is one of the most important mechanisms. Among the waves that can be encountered by the energetic electrons when they move around our Earth, whistler mode chorus waves can cause both acceleration and the loss of energetic electrons in the Earth's radiation belts and ring current. Using more than 5 years of wave measurements from NASA’s Van Allen Probe mission, Wang et al (2019) developed chorus wave models which depend on magnetic local time (MLT), Magnetic Latitude (MLat), L-shell, and geomagnetic condition index Kp. To quantify the effect of chorus waves on energetic electrons, we calculated the bounce-averaged quasi-linear diffusion coefficients using the chorus wave model developed by Wang et al (2019) and extended to higher latitudes according to Wang and Shprits (2019). Using these diffusion coefficients, we calculated the lifetime of the electrons with an energy range from 1 keV to 2 MeV. In each MLT, we calculate the lifetime for each energy and L-shell using two different methods according to Shprits et al (2007) and Albert and Shprits (2009). We make the calculated electron lifetime database available here. Please notice that the chorus wave model by Wang et al (2019) is valid when Kp <= 6. If the user wants to use this lifetime database for Kp >6, please be careful and contact the authors.

Electron density derived with the Neural-network-based Upper-hybrid Resonance Determination algorithm from the Van Allen Probes EMFISIS measurements

The dataset presents the electron density derived using the Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm (Zhelavskaya et al., 2016) from plasma wave measurements made with the Van Allen Probes Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) (Kletzing et al., 2013). The method employs feedforward neural networks to derive the upper hybrid resonance frequency from the electric field measurements, and hence electron density, in an automated fashion. The dataset contains electron density for the period from October 1, 2012 to January 14, 2018 for RBSP-A and from October 1, 2012 to July 1, 2016 for RBSP-B (RBSP = Radiation Belt Storm Probes).For convenience, the density data are organized in two ways: in terms of orbits and in terms of days. Directories ../../Orbits_organization/ and ../../Days_organization/ contain files with densities per orbit and per day, respectively. Data are provided in .txt and .cdf formats. Data in .mat format are available at ftp://ftp.gfz-potsdam.de/home/rbm/NURD/. For more information on directory organization and files description, please refer to the associated data description and Zhelaskaya et al. (2016).

An empirical model of electron pitch angle distributions in the outer radiation belt based on Van Allen Probes data

Here, we present an empirical model of the equatorial electron pitch angle distributions, based on the Magnetic Electron Ion Spectrometer (MagEIS) instrument aboard the Van Allen Probes. The model was created for energies from 37 keV up to 2.65 MeV. The model uses the solar wind dynamic pressure as a driving parameter and has a continuous dependence on Lm, magnetic local time and activity. It works for L-shells from 3.05 up around 5.95. For each channel of the MagEIS instrument, there are two files with model coefficients, one for Pdyn <5.5-6 nPa (e.g., “Pijk_246_keV.dat’) , and the second one for very high dynamic pressure values above 5.5 nPa (e.g., “Pijk_246_keV_HIGH.dat’). The script to read both file types is provided (“read_coefs.py”), and the data format is explained in the readme file.

Lifetime of Energetic Electrons due to Interactions with Chorus Waves

In the near-Earth space, there are a large population of high energy electrons trapped by Earth’s magnetic field. These energetic electrons are trapped in the regions called Earth’s ring current and radiation belts. They are very dynamic and show a very strong dependence on solar wind and geomagnetic conditions. These energetic electrons can be dangerous to satellites in the near-Earth space. Therefore, it is very important to understand the mechanisms which drive the dynamics of these energetic electrons. Wave particle interaction is one of the most important mechanisms. Among the waves that can be encountered by the energetic electrons when they move around our Earth, whistler mode chorus waves can cause both acceleration and the loss of energetic electrons in the Earth's radiation belts and ring current. To quantify the effect of chorus waves on energetic electrons, we calculated the bounce-averaged quasi-linear diffusion coefficients using the chorus wave model developed by Wang et al (2019) and extended to higher latitudes according to Wang and Shprits (2019). Using these diffusion coefficients, we calculated the lifetime of the electrons with an energy range from 1 keV to 2 MeV. In each magnetic local time (MLT), we calculate the lifetime for each energy and L-shell using two different methods according to Shprits et al (2007) and Albert and Shprits (2009). We make the calculated electron lifetime database available here. Please notice that the chorus wave model by Wang et al (2019) is valid when Kp <= 6. If the user wants to use this lifetime database for Kp >6, please be careful and contact the authors.

MLT-averaged Plasmapause Position Calculated from the PINE Plasmasphere Model for the GEM Challenge Events

This dataset is the MLT-averaged plasmapause position calculated for the NSF GEM Challenge Events. We use the recently developed Plasma density in the Inner magnetosphere Neural network-based Empirical (PINE) model [Zhelavskaya et al., 2017]. The PINE density model was developed using neural networks and was trained on the electron density data set from the Van Allen Probes Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) [Kletzing et al., 2013]. The model reconstructs the plasmasphere dynamics well (with a cross-correlation of ~0.95 on the test set), and its global reconstructions of plasma density are in good agreement with the IMAGE EUV images of the global distribution of He+. We compare the electron number density value given by the PINE model with the density threshold separating plasmaspheric-like and trough-like density given by [Sheeley et al., 2001] and get the plasmapause position in each MLT. Then, we calculate the MLT-averaged plasmapause position. The. time resolution is 1 hour. These data files presenting the Magnetic Local Time (MLT)-averaged plasmapause position used in the simulations in Wang et al [2020]. The data are presented as the following three tabular ASCII files (.dat) : Lpp_PINE_Sheely_Mean_Mar15_Mar20.dat: content, column1 time [day], column 2 L [Re (Earth Radii)] Lpp_PINE_Sheely_Mean_May30_Jun02.dat: content, column1 time [day], column 2 L [Re (Earth Radii)] Lpp_PINE_Sheely_Mean_Sep17_Sep26.dat: content, column1 time [day], column 2 L [Re (Earth Radii)]