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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Database for "A New Four-Component L*-dependent Model for Radial Diffusion based on Solar Wind and Magnetospheric Drivers of ULF Waves"

Authors: Murphy, Kyle;

Database for "A New Four-Component L*-dependent Model for Radial Diffusion based on Solar Wind and Magnetospheric Drivers of ULF Waves"

Abstract

Database for "A New Four-Component L*-dependent Model for Radial Diffusion based on Solar Wind and Magnetospheric Drivers of ULF Waves" submitted to Space Weather by Murphy et al. The repository contains 2 datasets: The power spectral density of the compressional magnetic field from THEMIS, Van Allen Probes, and GOES along with accompanying position (MLT, L, L* TS05), solar wind, and geomagnetic data The power spectral density of the azimuthal electric field from THEMIS and Van Allen Probes along with accompanying position (MLT, L, L* TS05), solar wind, and geomagnetic data Both datasets are provided as an IDL save file and as an HDF5 file. The IDL data can be loaded using: filename='electric_field_psd.sav' filename='magnetic_field_psd.sav' restore, filename, /verbose The HDF5 file can be opened and investigate using (small changes will be required to store each variable): import h5py filename = 'magnetic_field_psd.h5' # magnetic field data filename = 'magnetic_field_psd.h5' # electric field data with h5py.File(filename, "r") as f: # loop through all keys (data) #print key and key attribute and size for i in f.keys(): print(f"{i} - {f[i].attrs['attributes']}, shape - {f[i].shape}") ds_obj = f[i] # returns as a h5py dataset object ds_arr = f[i][()] # returns as a numpy array Below is a description of unique and common variables in each file. The psd variables have a shape [f,t], indicating the first dimension is frequency and the second is time, the f_mhz variable has shape [f], and all time series have shape [t]; here [f] and [t] denotes the number of elements in frequency and time arrays. ------------------------------------ Magnetic field data set: Files magnetic_field_psd.h5 magnetic_field_psd.sav Unique Data (variable in file) psd Power spectral density of the compressional magnetic field from THEMIS, Van Allen Probes, and GOES Units - nT2/mHz Shape - [f, t] ------------------------------------ Electric field data set: Files electric_field_psd.h5 electric_field_psd.sav Unique Data (variable in file) psd Power spectral density of the azimuthal electric field from THEMIS, Van Allen Probes, and GOES Units - (mV/m)2/mHz Shape - [f, t] ------------------------------------ Common Data in the Magnetic and Electric Field Datasets (variable in file): probe Corresponding satellite of each time stamp Shape [t] t Time stamp of each time series; number of seconds since 1970 (UNIX time), [t] Units - s Shape [t] f_mhz Frequency of psd data, [f] Units - mHz Shape [f] - (19) ae OMNI AE index of each time stamp Units - nT' Shape [t] al OMNI AL index of each time stamp, units - nT Shape [t] au OMNI AU index of each time stamp Units - nT Shape [t] b_t OMNI IMF B of each time stamp Units - nT Shape [t] b_x OMNI IMF Bx (GSM) of each time stamp Units - nT Shape [t] b_y OMNI IMF By (GSM) of each time stamp Units - nT Shape [t] b_z OMNI IMF Bz (GSM) of each time stamp Units - nT Shape [t] dst OMNI Dst of each time stamp Units - nT Shape [t] kp - OMNI Kp (Kp*10) of each time stamp units - NA Shape [t] l_sh L-shell of each time stamp Shape [t] ls_t05 L* from TS05 of each time stamp Shape [t] mlt Magnetic Local Time of each time stamp Unit - hour Shape [t] n OMNI Solar Wind Proton Density of each time stamp Units - n/cc Shape [t] pdyn OMNI Solar Wind Dynamic Pressure (flow pressure) of each time stamp Units - nPa Shape [t] symh - b'OMNI Sym-H of each time stamp, units - nT', shape - (477205,) v_t OMNI Solar wind V of each time stamp Units - km/s Shape [t] v_x OMNI Solar wind Vx (GSE) of each time stamp Units - km/s Shape [t] v_y OMNI Solar wind Vy (GSE) of each time stamp Units - km/s Shape [t] v_z OMNI Solar wind Vz (GSE) of each time stamp Units - km/s Shape [t]

Related Organizations
Keywords

Radial Diffusion, Electron Radiation Belt Dynamics, ULF waves

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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