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/).
Data categories
RAW: Raw magnetic field data as provided by L1b
ACAL_CORR: Magnetic field data, aligned, calibrated and corrected
CHAOS7: CHAOS7 magnetic model predictions for core, crustal and large-scale magnetospheric field
APEX: Magnetic coordinates (Emmert et al, 2010)
FAC: Radial and field-aligned currents derived from magnetic data in ACAL_CORR
The Gravity Recovery and Climate Experiment-Follow-On (GRACE-FO) satellite mission, consisting of two satellites, each carry a magnetometer as part of its attitude orbit control system (AOCS). After careful calibration, the data acquired through them 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 et al. (2021, https://doi.org/10.5880/GFZ.2.3.2021.002) and uses a similar format. The platform magnetometer data has been calibrated against CHAOS-7 magnetic field model predictions for core, crustal and large-scale magnetospheric field (Finlay et al., 2020, https://doi.org/10.1186/s40623-020-01252-9) 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 information, 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. Additionally, in the folder ‚fac’, field-aligned current derived from the magnetic field data are provided.
There exists a similar dataset with calibrated magnetic data from the GOCE satellite mission under https://doi.org/10.5880/GFZ.2.3.2022.002 (Styp-Rekowski et al., 2022).