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Whistler mode chorus is an important magnetospheric wave emission playing a major role in radiation belt dynamics, where it contributes to both the acceleration and loss of relativistic electrons. In this study we compute bounce and drift averaged chorus diffusion coefficients for 3.0 < L* < 6.0, using the TS04 external magnetic field model, taking into account colocated nearequatorial measurements of the wave intensity and fpe/fce, by combining the Van Allen probes measurements with data from a multisatellite VLF wave database. The variation of chorus wave normal angle with spatial location and fpe/fce is also taken into account. We find that chorus propagating at small wave normal angles has the dominant contribution to the diffusion rates in most MLT sectors. However, in the region 4 <= MLT < 11 high wave normal angles dominate at intermediate pitch angles. In the region 3 < L* < 4, the bounce and drift averaged pitch angle and energy diffusion rates during active conditions are primarily larger than those in our earlier models by up to a factor of 10 depending on energy and pitch angle. Further out, the results are similar. We find that the bounce and drift averaged energy and pitch angle diffusion rates can be significantly larger than the new model in regions of low fpe/fce,eq, where the differences can be up to a factor of 10 depending on energy and pitch angle. Funding was provided by the Natural Environment Research Council (NERC) Highlight Topic grant NE/P01738X/1 (RadSat) and the NERC grants NE/V00249X/1 (SatRisk), NE/R016038/1 and NE/X000389/1.

We conduct a global survey of magnetosonic waves and compute the associated bounce and drift averaged diffusion coefficients, taking into account colocated measurements of fpe/fce, to assess the role of magnetosonic waves in radiation belt dynamics, where fpe is the plasma frequency and fce is the electron gyrofrequency.. The average magnetosonic wave intensities increase with increasing geomagnetic activity and decreasing relative frequency with the majority of the wave power in the range fcp < f < 0.3fLHR during active conditions, where fcp is the proton gyrofrequency and fLHR is the lower hybrid resonance frequency. In the region 4.0 <= L* <= 5.0, the bounce and drift averaged energy diffusion rates due to magnetosonic waves never exceed those due to whistler mode chorus, suggesting that whistler mode chorus is the dominant mode for electron energisation to relativistic energies in this region. Further in, in the region 2.0 <= L* <= 3.5, the bounce and drift averaged pitch angle diffusion rates due to magnetosonic waves can exceed those due to plasmaspheric hiss and very low frequency (VLF) transmitters over energydependent ranges of intermediate pitch angles. We compute electron lifetimes by solving the 1D pitch angle diffusion equation including the effects of plasmaspheric hiss, VLF transmitters and magnetosonic waves. We find that magnetosonic waves can have a significant effect on electron loss timescales in the slot region reducing the loss timescales during active times from 5.6 to 1.5 days for 500 keV electrons at L* = 2.5 and from 140.4 days to 35.7 days for 1 MeV electrons at L* = 2.0. The research leading to these results has received funding from the Natural Environment Research Council (NERC) Highlight Topic grant NE/P01738X/1 (RadSat) and the NERC grants NE/V00249X/1 (SatRisk) and NE/R016038/1.

The data files in this directory were used to create Figures 27 in the paper: Horne et al. (in press  2018/7/18). Figure 1 of the paper was constructed using publically available data from other sources.

Auroral oval boundary locations derived from IMAGE (Imager for MagnetopausetoAurora Global Exploration) satellite FUV (Far Ultra Violet imager) data covering the period from May 2000 until October 2002. Three sets of boundary data were derived separately from the WIC (Wideband Imaging Camera) and SI12/SI13 (Spectrographic Imager 121.8/135.6 nm) detectors. For each image, the position of each pixel in AACGM (Altitude Adjusted Corrected Geomagnetic) coordinates was established. Each image was then divided into 24 segments covering 1 hour of magnetic local time (MLT). For each MLT segment, an intensity profile was constructed by finding the average intensity across bins of 1 degree magnetic latitude in the range of 50 to 90 degrees (AACGM). Two functions were fit to each intensity profile: a function with one Gaussian component and a quadratic background, and a function with two Gaussian components and a quadratic background. The function with a single Gaussian component should provide a reasonable model when the auroral emission forms in a continuous oval. When the oval shows bifurcation, the function with two Gaussian components may provide a better model of the auroral emission. Of the two functions fit to each intensity profile, we determine the one with the lower reduced chisquare goodnessoffit statistic to be the better model for that profile. For the version 1.1 boundary location data, the fitting process was performed over 200 iterations to achieve each fit. The auroral boundaries were then determined to be the position of the peak of the poleward Gaussian curve, plus its FWHM (fullwidth halfmaximum) value of the Gaussian, to the peak of the equatorward Gaussian, minus its FWHM. In the case of the single Gaussian fit, the same curve is used for both boundaries. A number of criteria were applied to discard poorly located auroral boundaries arising from either poor fitting or incomplete data. A further correction can be applied to the data, to estimate the location of the Earth''s magnetic field''s OCB (openclose boundary). These corrections have been tabulated in a separate file; if this correction is required the adjustments should be made to the poleward boundary value.

This data set contains the ULF wave model output data required to produce the figures in the article: A. W. Degeling, I. J. Rae, C. E. J. Watt, Q. Q. Shi, R. Rankin and Q. G. Zong, "Control of ULF Wave Accessibility to the Inner Magnetosphere by the Convection of Plasma Density", J. Geophys. Res. (accepted Dec. 2017) doi:10.1002/2017JA024874 The dataset has a Matlab binary file format. It consists of a structure array "d" (with 325 elements). These elements correspond to the 2D parameter scan in driver frequency and elapsed time during plume development performed for this study. The elapsed time parameter has 25 elements, ranging 0 to 24 hours (i.e. 1 hour spacing), and the driver frequency parameter has 13 elements ranging from 1 to 7 mHz (with 0.5 mHz spacing). e.g. use "d = reshape(d,25,13);" to reshape the structure array into 2D with columns for the frequency scan and rows for the elapsed time scan. The Matlab function "make_PDP_figs.m" is used to read the data, perform the necessary postprocessing operations and output the article figures. To produce all six figures, simply run the file without any input arguments.

These files contain the data from the figures in "A 30 year simulation of the outer electron radiation belt", S.A. Glauert, et al., Space Weather 2018. The paper describes a 30 year (1 January 1986  1 January 2016) reconstruction of the Earth''s electron radiation belt from L*=2 to L*=6.1 (approximately geostationary orbit), for energies ranging from 100 keV to 30 MeV at L*=6.1.

We present a concurrent series of 144 monthly reanalyses of Super Dual Auroral Radar Network (SuperDARN) plasma velocity measurements, using the method of datainterpolating Empirical Orthogonal Functions (EOFs). For each monthly reanalysis, the 5minute median values of the northern polar region''s radarmeasured lineofsight Doppler plasma velocities are binned in an equalarea grid defined in quasidipole latitude and quasidipole magnetic local time (MLT). The grid cells each have an area of approximately 110,000km2, and the grid extends to 30 degrees colatitude. Within this spatial grid, the sparse binned data are infilled to provide a measurement at every spatial and temporal location via two different EOF analysis models: one tailored to instances of low data coverage, the other tailored to higher data coverage. These two models each comprise 144 monthly sets of orthogonal modes of variability (spatial and temporal patterns), along with the timestamps of each epoch, and the spatial coordinate information of all bin locations. A companion dataset determines which of the two models should be chosen in each location for each month, in order to ensure the best accuracy of the infill solution. We also provide the temporal mean of the data in each spatial bin, which is removed prior to the EOF analysis. Collectively, the reanalysis delivers the SuperDARN data in terms of cardinal north and east vector components (in the quasidipole coordinate frame), without its usual extreme sparseness, for studies of ionospheric electrodynamics for the period 1997.0 to 2009.0. Funding was provided by NERC Standard grant NE/N01099X/1, titled ''Thermospheric Heating Modes and Effects on Satellites'' (THeMES) and the NERC grant NE/V002732/1, titled ''Space Weather Instrumentation, Measurement, Modelling, and Risk: Thermosphere'' (SWIMMRT).

The data provided is the underlying data used for creating the plots in Ross et al 2020. The research leading to these results has received funding from the National Environment Research Council Highlight Topic grant NE/P01738X/1 (RadSat), National Environment Research Council grant NE/R016445/1 and NE/R016038/1, and the STFC grant ST/S000496/1

This dataset contains data produced by two Gorgon Global magnetohydrodynamic (MHD) simulations with steady solar wind conditions interacting with the Earth''s magnetosphere, as utilised in the study of Desai et al. (2021b). Further description of the Gorgon MHD model can be found at Mejnertsen et al., (2016,2018), Eggington et al., (2020) and Desai et al., (2021a). The data was produced on the Imperial College High Performance Computing Service (doi: 10.14469/hpc/2232). Two MHD simulations are contained; one with northward Interplanetary Magnetic Field (IMF) conditions and one with southward (IMF) conditions. The northward IMF condition is run with a grid resolution of 0.25 earth radii (RE) and the southward IMF conditions is run three times for grid resolutions of 0.5, 0.25 and 0.125 RE. The MHD equations were solved in the magnetosphere on a regular 3D Cartesian grid, covering a domain of dimensions (20,100) RE in X, (40,40) RE in Y and (40,40) RE in Z with an inner boundary at 3 RE. In this coordinate system the Sun lies in the negative Xdirection, the Z axis is aligned to the dipole in the 0 degree tilt case (where positive tilt points the north magnetic pole towards the Sun), and Y completes the righthanded set. Output data is timestamped in seconds and is defined at the centre of the grid cells. The simulation data corresponding to each shock are stored in separate directories ''NorthwardX'' and ''SouthwardX'' where X is the grid resolution in RE of: 0.5 for the northward case and 0.5, 0.25 and 0.125 for the southward case. The data are stored in hdf5 format. The magnetospheric variables are stored in the files: ''Gorgon_[YYYYMMDD]_MS_params_[XXXXX]s.hdf5'' where XXXXX is the simulation time in seconds. The magnetospheric data includes the magnetic field, (''Bvec_c'') and Electric field, (''Evec''), after 2hrs of simulation. The data are of shape (240,160,160,3) where the first 3 dimensions are the grid indices in (X,Y,Z) indexed from negative to positive, and the final dimension is the cartesian vector component in (i,j,k). Funding was provided by NERC Highlight grant to NE/P017347/1 (RadSat).

Ionospheric boundary locations derived from IMAGE (Imager for MagnetopausetoAurora Global Exploration) satellite FUV (Far Ultra Violet) imager data covering the period from May 2000 until October 2002. These include poleward and equatorward auroral boundary data derived directly from the three imagers, WIC (Wideband Imaging Camera), SI12 (Spectrographic Imager 121.8 nm), and SI13 (Spectrographic Imager 135.6 nm). These also include the OCB (openclosed magnetic field line boundary) and EPB (equatorward precipitation boundary) derived indirectly from the auroral boundaries. The data set also includes model fitted circles for all the boundary data sets for all measurement times. Chisham et al. (2022) also describe that the v2 data set also includes estimates of the OCB at each time, derived from a combination of the poleward auroral boundary measurements in combination with modelled statistical offsets between the auroral boundary and the OCB as measured by the DMSP spacecraft. The v2 data set also includes estimates of the EPB at each time, derived from a combination of the equatorward auroral boundary measurements in combination with modelled statistical offsets between the auroral boundary and the EPB as measured by the DMSP spacecraft. The v2 data set also includes model circle fit boundaries for all times for all eight raw data sets. These model circle fits were estimated using the methods outlined in Chisham (2017) and Chisham et al. (2022), which involves fitting circles to the spatial variation of the boundaries at any one time. The raw auroral boundaries were derived as outlined in Longden et al. (2010) (the original v1 data set) with the application of the additional selection criteria outlined in Chisham et al. (2022). For the creation of the original v1 data set, for each image, the position of each pixel in AACGM (Altitude Adjusted Corrected Geomagnetic) coordinates was established. Each image was then divided into 24 segments covering 1 hour of magnetic local time (MLT). For each MLT segment, an intensity profile was constructed by finding the average intensity across bins of 1 degree magnetic latitude in the range of 50 to 90 degrees (AACGM). Two functions were fit to each intensity profile: a function with one Gaussian component and a quadratic background, and a function with two Gaussian components and a quadratic background. The function with a single Gaussian component should provide a reasonable model when the auroral emission forms in a continuous oval. When the oval shows bifurcation, the function with two Gaussian components may provide a better model of the auroral emission. Of the two functions fit to each intensity profile, the one with the lower reduced chisquare goodnessoffit statistic was deemed to be the better model for that profile. The auroral boundaries were then determined to be the position of the peak of the poleward Gaussian curve, plus its FWHM (fullwidth halfmaximum) value of the Gaussian, to the peak of the equatorward Gaussian, minus its FWHM. In the case of the single Gaussian fit, the same curve is used for both boundaries. A number of criteria were applied to discard poorly located auroral boundaries arising from either poor fitting or incomplete data. Following Chisham et al. (2022), additional criteria were used to refine the data for the v2 auroral boundary data sets. These included dealing with anomalous data at the edges of the image fields of view, and dealing with anomalous mapping issues. Funding was provided by: STFC grant PP/E002110/1  Does magnetic reconnection have a characteristic scale in space and time? NERC directed grant NE/V002732/1  Space Weather Instrumentation, Measurement, Modelling and Risk  Thermosphere (SWIMMRT). NERC BAS National Capability  Polar Science for Planet Earth.