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EARTH SCIENCE > Sun-earth Interactions > Ionosphere/Magnetosphere Dynamics

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  • We conduct a global survey of magnetosonic waves and compute the associated bounce and drift averaged diffusion coefficients, taking into account co-located 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 energy-dependent 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 (Rad-Sat) and the NERC grants NE/V00249X/1 (Sat-Risk) and NE/R016038/1.

  • The data files in this directory were used to create Figures 2-7 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.

  • 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 post-processing operations and output the article figures. To produce all six figures, simply run the file without any input arguments.

  • We present a concurrent series of 144 monthly reanalyses of Super Dual Auroral Radar Network (SuperDARN) plasma velocity measurements, using the method of data-interpolating Empirical Orthogonal Functions (EOFs). For each monthly reanalysis, the 5-minute median values of the northern polar region''s radar-measured line-of-sight Doppler plasma velocities are binned in an equal-area grid defined in quasi-dipole latitude and quasi-dipole 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 quasi-dipole 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'' (SWIMMR-T).

  • Auroral oval boundary locations derived from IMAGE (Imager for Magnetopause-to-Aurora 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 chi-square goodness-of-fit 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 (full-width half-maximum) 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 (open-close 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.

  • Ionospheric boundary locations derived from IMAGE (Imager for Magnetopause-to-Aurora 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 (open-closed 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 chi-square goodness-of-fit 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 (full-width half-maximum) 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 (SWIMMR-T). NERC BAS National Capability - Polar Science for Planet Earth.

  • We present a reanalysis of SuperDARN plasma velocity measurements, using the method of data-interpolating Empirical Orthogonal Functions (EOFs). The northern polar region''s radar-measured line of sight Doppler velocities are binned in an equal-area grid (areas of approximately 110,000km2) in quasi-dipole latitude and quasi-dipole magnetic local time (MLT). Within this spatial grid, which extends to 30 degrees colatitude, the plasma velocity is given in terms of cardinal north and east vector components (in the quasi-dipole coordinate frame), with the median of every SuperDARN measurement in the spatial bin taken every 5 minutes. These sparse binned data are infilled to provide a measurement at every spatial and temporal location via EOF analysis, ultimately comprising a reanalysis spanning the month of February 2001. This resource provides a convenient method of using SuperDARN data without its usual extreme sparseness, for studies of ionospheric electrodynamics. The reanalysis is provided in 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. We also provide the temporal mean of the data in each spatial bin, which is removed prior to the EOF analysis. Funding was provided by NERC standard grants NE/N01099X/1 (THeMES) and NE/V002732/1 (SWIMMR-T).

  • 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 (Rad-Sat), National Environment Research Council grant NE/R016445/1 and NE/R016038/1, and the STFC grant ST/S000496/1

  • Whistler mode chorus is an important magnetospheric emission, playing fundamental roles in the dynamics of the Earth''s outer radiation belt and the production of the Earth''s diffuse and pulsating aurora. In this study we extend our existing database of whistler mode chorus by including ~3 years of data from RBSP-A and RBSP-B and an additional ~6 years of data from THEMIS A, D, and E, greatly improving the statistics and coverage in the near-equatorial region (|MLAT|<18^o). We produce new global maps of whistler mode chorus as a function of spatial location and frequency. This work is reported in Meredith et al. [2020] and the data provided here enable reconstruction of all of the figures in the paper. The research leading to these results has received funding from the Natural Environment Research Council (NERC) Highlight Topic grant NE/P01738X/1 (Rad-Sat) and the NERC grant NE/R016038/1. Wen Li and Xiao-Chen Shen received funding from NASA grants NNX17AG07G and 80NSSC19K0845, NSF grant AGS-1847818, and the Alfred P. Sloan Research Fellowship FG-2018-10936. Jacob Bortnik received funding from NASA grants NNX14AI18G, and RBSP-ECT and EMFISIS funding provided by JHU/APL contracts 967399 and 921647 under NASA''s prime contract NAS5-01072.

  • Radiation belts are hazardous regions found around several of the planets in our Solar System. They consist of very hot, electrically charged particles that are trapped in the magnetic field of the planet. At Saturn the most important way to heat these particles has for many years been thought to involve the particles drifting closer towards the planet. This paper builds on previous work on the emerging idea at Saturn that a different way to heat the particles is also possible where the heating is done by waves, in a similar way to what we find at the Earth. This work is reported in the paper "Acceleration of electrons by whistler-mode hiss waves at Saturn" by E.E. Woodfield et al., 2021. The data provided here enable reconstruction of all the figures in the paper. E.E.W., R.B.H., and S.A.G. were funded by STFC grant ST/S000496/1. R.B.H., S.A.G. and A.J.K. were funded by NERC grant NE/R016038/1 and R.B.H. and S.A.G. by NERC grant NE/R016445/1. J.D.M. and Y.Y.S. were supported by NASA grants NNX11AM36G and NNX16AI47G. University of Iowa (J.D.M.) was supported by NASA contract 1415150 with JPL. Y.Y.S. was supported by EC grant H2020 637302.