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Chorus waves play an important role in the dynamic evolution of energetic electrons in the Earth’s radiation belts and ring current. Due to the orbit limitation of Van Allen Probes, our previous chorus wave model developed using Van Allen Probe data is limited to low latitude. In this study, we extend the chorus wave model to higher latitudes by combining measurements from the Van Allen Probes and Arase satellite. As a first step, we intercalibrate chorus wave measurements by comparing statistical features of chorus wave observations from Van Allen Probes and Arase missions. We first investigate the measurements in the same latitude range during the two years of overlap between the Van Allen Probe data and the Arase data. We find that the statistical intensity of chorus waves from Van Allen Probes is stronger than those from Arase observations. After the intercalibration, we combine the chorus wave measurements from the two satellite missions and develop an analytical chorus wave model which covers all magnetic local time and extends to higher latitudes. This chorus wave model will be further used in radiation belt and ring current simulations., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The Gravity field and steady-state ocean circulation explorer (GOCE) satellite mission carries three platform magnetometers. After careful calibration, the data acquired through these can be used for scientific purposes by removing artificial disturbances from other satellite payload systems. This dataset is based on the dataset provided by Michaelis and Korte (2022) and uses a similar format. The platform magnetometer data has been calibrated against CHAOS7 magnetic field model predic-tions for core, crustal and large-scale magnetospheric field (Finlay et al., 2020) and is provided in the ‘chaos’ folder. The calibration results using a Machine Learning approach are provided in the ‘calcorr’ folder. Michaelis’ dataset can be used as an extension to this dataset for additional infor-mation, as they are connected using the same timestamps to match and relate the same data points. The exact approach based on Machine Learning is described in the referenced publication. The data is provided in NASA CDF format (https://cdf.gsfc.nasa.gov/) and accessible at: ftp://isdcftp.gfz-potsdam.de/platmag/MAGNETIC_FIELD/GOCE/ML/v0204/ and further de-scribed in a README.

The GOCE satellite carries three magnetometers as part of its drag-free attitude orbit control system (DFACS). The magnetometers do not belong to the scientific payload of the mission. After postprocessing of the data, information on the geomagnetic field and on electric currents in near Earth space are derived. The GOCE fluxgate magnetometer data (MAG) have been combined into to a single time series. The provided data consists of raw magnetic field data as provided by Level 1b (RAW), magnetic field data aligned, calibrated and corrected (ACAL_CORR), CHAOS7 magnetic model predictions for core, crustal and large-scale magnetospheric field (CHAOS7, Finlay et al., 2020), housekeeping information, e.g. magnetorquer, solar array and battery currents (HK), Magnetic coordinates (APEX) and radial and field-aligned currents derived from magnetic data (FAC). The calibration and characterization follows the approach given in the references for GOCE calibration. The data are provided in NASA cdf format (https://cdf.gsfc.nasa.gov/) and accessible at: ftp://isdcftp.gfz-potsdam.de/platmag/MAGNETIC_FIELD/GOCE/Analytical/v0205/ and further described in a README.

GRACE-FO carries a magnetometer as part of its attitude orbit control system (AOCS). The magnetometer does not belong to the scientific payload of the mission. However, after postprocessing of the data, information on the geomagnetic field and on electric currents in near Earth space are derived. Each GRACE-FO satellite (GF1 and GF2) carries two fluxgate magnetometers (FGM), an active one, FGM A, and a redundant one, FGM B. So far, the redundant magnetometers were not switched and are not included in the data set. The provided data consists of raw magnetic field data as provided by L1b (RAW), Magnetic field data aligned, calibrated and corrected (ACAL_CORR), CHAOS7 magnetic model predictions for core, crustal and large-scale magnetospheric field (CHAOS7), Magnetic coordinates (APEX) and Radial and field-aligned currents derived from magnetic data in ACAL_CORR (FAC). The data are provided in NASA CDF format (https://cdf.gsfc.nasa.gov/).

Time series of processed, cleaned attitude readings in quaternion format of the two boom-mounted 'ASC' star sensors of the 'LEO' satellite 'CHAMP', describing the satellite system attitude in respect to the celestial background. The nominal time resolution of the time series in the 'ASCII'-file listing is 1 Hz.

The auroral oval is the region receiving most magnetospheric particle precipitations and its boundaries can be highly dynamic and influenced by the solar wind and geomagnetic conditions. Polar orbiting Low Earth Orbit (LEO) satellites carrying high-precision magnetometers are suitable to derive Field-Aligned Currents (FACs) with tens of km-scale lengths flowing between the magnetosphere and ionosphere. Our previous work has used nearly 10 years FAC data from the CHAMP mission to construct an empirical model (called CH-Aurora-204) for estimating the location of the auroral oval boundaries. The model has been recently updated by taking nearly 5 years FAC data from the three Swarm satellites. Furthermore, magnetic data from other non-dedicated magnetic LEO missions, like Cryosat or e-PoP, are also used for improving the model predicts of the auroral oval boundaries.

Earth's magnetic field vector time series from `LEO' satellite 'CHAMP' for the 'CHAMP' mission period in high, unaveraged 50 Hz time resolution, using measurements from the FGM vector magnetometers and `ASC' Star Sensors on the mid-boom optical bench. The vector data are corrected and calibrated (by using the Overhauser scalar magnetometer as reference). The magnetic field vector data are given both in the satellite-bound sensor (`FGM') system and in the Earth Centered Earth Fixed local `NEC' (North-East-Center) system. For the latter the attitude time series (`ASC'), processed and cleaned, represented by quaternions describing the satellite attitude related to the celestial system, were used for the transformation. The files with daily time coverage are in the (binary and self-describing) `CDF' file format and accompanied, beside the `CDF'-format generic timestamp, by the satellite's geocentric positions and utility information like quality flags.

Electron density and electron temperature time series from 'LEO' satellite 'CHAMP' for the CHAMP mission period at satellite position in low time resolution of 15 second and given in daily files. This are processed readings from the Planar Langmuir probe, which, in normal flight mode, was exposed in flight direction at the front of the `CHAMP' satellite body. The files are formatted as simple 'ASCII'-listings with white-space delimited columns.

ESA’s Swarm constellation mission consisting of three identical satellites, successfully launched on 22 November 2013, provides the excellent opportunity of reliable electric current density estimates in the ionosphere based on multi-satellite magnetic field measurements. The final constellation with Swarm A/C orbiting the Earth at about 470 km (flying side-by-side) and Swarm B at about 520 km altitude was achieved on 17 April 2014. Swarm satellites need a period of about 130 days to cover all local times; therefore the coverage of all local times and local seasons can be achieved in 5 years from the final constellation when the dual-satellite current density estimations have been started. We present the climatology of field-aligned currents (FACs) at polar cap, cusp and auroral regions, radial, interhemispheric (IHFACs) and F region dynamo currents at mid-latitude and equatorial regions, using the single and dual satellite approaches for the current density estimations. Also, the higher-flying Swarm B satellite provides from time to time well-matched observations with the 50 km lower Swarm A/C pair that gives the possibility for zonal current estimates by using Ampère’s ring integral for determining the mean current density passing through the encircled area.

This is a Level 3 data daily file product from various scientific and utility sensors on board of the `LEO' satellite 'CHAMP' with magnetic field data given by a time resolution of 1 Hz. Thise Level 3 data type is build to hold and merge finally corrected data, focusing on mature data calibration and corrections -- as well as internal consistency. This Level 3 data product is intended to supersede the various Level 2 versions with calibrated magnetic field readings from the CHAMP mission distributed hitherto and should be fitted for scientific use, assembling time series of scalar magnetic field values (but not directly readings from the scalar Overhauser sensor), vector magnetic field data from the boom-mounted Fluxgate 'FGM' sensors and attitude data from the ('ASC') boom-mounted Star Cameras. The vector data are given both in the satellite-bound sensor ('FGM') system and the Earth Centered Earth Fixed local 'NEC' (North-East-Center) system. The attitude time series, processed and cleaned, are represented by quaternions describing the satellite attitude related to the celestial system. The readings of the scalar OVM (Overhauser) absolute magnetometer at the top of the boom are not supplied directly, but were used during calibration of the vector magnetometer readings. The files with daily time coverage are in the (binary and self-describing) 'CDF' file format and accompanied, beside the generic 'CDF'-format timestamp, by the satellite's geocentric positions and utility information like quality flags.

After more than 4 years in orbit, the Swarm constellation mission has collected global measurements of the ge-omagnetic field as well as the ionospheric plasma environment with a reasonable coverage in season and localtime. The Swarm mission started around the maximum of the solar cycle 24 and has collected data during itsdeclining phase. These data, sometimes combined with data from earlier or contemporary LEO satellites, haveenabled climatological studies of ionospheric currents and plasma structures. For examples, the longitudinal vari-ability of atmospheric wave structures in the equatorial electrojet and the seasonal dependence of the Poynting fluxassociated with low latitude plasma depletions have been studied. Furthermore, evidence was found for a plasmadepletion threshold at which severe disturbances of navigational signals occur. In this review, we will present anumber of novel studies and discuss open questions that have been raised from these observations.

The auroral oval is the region receiving most magnetospheric particle precipitations and its polward boundary approximately forms the boundary of the polar cap, inside which the magnetic field lines are open. The auroral oval boundaries can be highly dynamic and are related to solar and geomagnetic activity. Polar orbiting Low Earth orbit (LEO) satellites carrying as high as 1-Hz resolution magnetometers are suitable to detect magnetic-field aligned currents (FACs) with scale lengths of 10 km flowing between the magnetosphere and ionosphere. We use an existing empirical model of the location of the equatorward and poleward auroral oval boundaries, that was derived from nearly 10 years of FAC data from the CHAMP mission. This model is parameterized with the solar wind merging electric field. An even more precise estimate of the boundaries at a certain time is achieved when the oval is additionally fitted to independent, orbitwise auroral boundary calculations from other recent LEO missions. We fit the oval boundaries predicted by the exiting model to observations from the Swarm constellation and we investigate the dynamics of the auroral boundaries for different solar and magnetic activity periods during the last 5 years. The result is expected to be enhanced when FAC data derived from magnetic field observations from simultaneous other missions are considered, such as the e-POP mission.

The objective of the Electron Losses and Fields INvestigation on board the Lomonosov satellite ( ELFIN-L) project is to determine the energy spectrum of precipitating energetic electrons and ions and, together with other polar-orbiting and equatorial missions, to better understand the mechanisms responsible for scattering these particles into the atmosphere. This mission will provide detailed measurements of the radiation environment at low altitudes. The 400-500 km sun-synchronous orbit of Lomonosov is ideal for observing electrons and ions precipitating into the atmosphere. This mission provides a unique opportunity to test the instruments. Similar suite of instruments will be flown in the future NSF-and NASA-supported spinning CubeSat ELFIN satellites which will augment current measurements by providing detailed information on pitch-angle distributions of precipitating and trapped particles.

International audience; The eleventh generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2009 by the International Association of Geomagnetism and Aeronomy Working Group V-MOD. It updates the previous IGRF generation with a definitive main field model for epoch 2005.0, a main field model for epoch 2010.0, and a linear predictive secular variation model for 2010.0–2015.0. In this note the equations defining the IGRF model are provided along with the spherical harmonic coefficients for the eleventh generation. Maps of the magnetic declination, inclination and total intensity for epoch 2010.0 and their predicted rates of change for 2010.0–2015.0 are presented. The recent evolution of the South Atlantic Anomaly and magnetic pole positions are also examined.

Quantitative analyses of computed tomography images are prone to errors due to the partial volume effect which affects objects (e.g., bones) that have a different size or are assessed with different resolution. We have developed a set of equations suitable for both modeling the partial volume effect in cortical bone and for performing the corresponding adjustment. Seven hollow cylinders and 2 cuboid phantoms were made out of Al with 1% Si. The specimens were scanned with a pQCT machine (XCT2002, Stratec Medizintechnik, Pforzheim, Germany) and analyzed with the integrated software, version 5.50. Measurements were performed at different resolutions (voxel size=0.20 to 0.75 mm), both in air and in Ringer solution, and analyses were performed at different detection thresholds. Applying the correcting equations set we could reduce the errors in cortical density by about 80%. The cortical area was assessed with a negligible error at a threshold (theta0) that is equivalent to the mean of the cortical bone density and of the background density. On choosing theta0 as the detection threshold the error in density was lowered to less than 2%. We propose to assess cortical area and cortical density in several steps, first assessing the area and density thereafter. Applying this method should be beneficial whenever "true world" values are required, or objects of different size are compared.

It is difficult to disentangle the effects of pure ageing from those of disuse. Master athletes, however, provide an opportunity to assess the effects of ageing per se, as these people maintain high activity levels during ageing.We examined 200 female and 295 male master runners over the age of 35 who participated at European and World master championships. Runners were grouped by short, middle and long distance disciplines. Besides a questionnaire about their sports activities, measurements of counter movement jumps on a ground reaction force plate were performed. Specific peak jump power was the main subject, i.e., maximum jump power per body mass.All discipline groups showed an age-related decline in specific jump power when performing counter movement jumps (p0.001). Except for female long distance runners, the amount of decline was the same for all discipline groups (p0.001 to p0.01) for each gender. The results for female long distance runners was highly spread caused by the small number of participants with older age.Our data indicate a decline in specific jump power that is similar to that reported in previous studies. The novelty from our results is the comparison of intra-gender decline. We observed the same amount of decline for all runners participating in different running disciplines.