Platform Magnetometer Satellites Overview
Swarm (Copyright: ESA–P. Carril, 2013), GOCE (credit: ESA), CHAMP (Quelle: Astrium GmbH), CASSIOPE (Credit: University of Calgary), GRACE/GRACE-FO (Quelle: Astrium)
Many satellites carry 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 can be derived.
GRACE-FO and GOCE data are also provided via Swarm Data Access in 'Multimission' subfolder and via Swarm VirES interface.
The GRACE-FO mission is a dedicated gravity field mission. Since the satellites carry two fluxgate magnetometers each, these have been calibrated and characterized for pertubations. The standard deviation of geomagnetic quiet time residual with high-performance geomagnetic field model (CHAOS7) is below 10 nT.
WARNING: The Field-Aligned Currents (FAC) dataset (v0201) is invalid since June 4th, 2020 and will not be continued. An updated FAC (v0202) is available now for the whole mission duration and replaces v0201.
A detailed study has been published here:
Stolle, C., Michaelis, I., Xiong, C. et al. Observing Earth’s magnetic environment with the GRACE-FO mission. Earth Planets Space 73, 51 (2021). doi.org/10.1186/s40623-021-01364-w
The data has been published here:
Michaelis, Ingo; Stolle, Claudia; Rother, Martin (2021): GRACE-FO calibrated and characterized magnetometer data. V. 0201. GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2021.002
and is available at
ftp://isdcftp.gfz-potsdam.de/grace-fo/MAGNETIC_FIELD/0201/
A new study using Machine Learning methods has been published here:
K. Styp-Rekowski, C. Stolle, I. Michaelis and O. Kao, "Calibration of the GRACE-FO Satellite Platform Magnetometers and Co-Estimation of Intrinsic Time Shift in Data," 2021 IEEE International Conference on Big Data (Big Data), 2021, pp. 5283-5290, doi: 10.1109/BigData52589.2021.9671977.
and updated here:
Kevin Styp-Rekowski, Ingo Michaelis, Monika Korte, et al. Physics-informed Neural Networks for the Improvement of Platform Magnetometer Measurements. Authorea. January 23, 2024.
DOI: 10.22541/au.170602061.18680921/v1
The data has been published here:
Styp-Rekowski, Kevin; Michaelis, Ingo; Korte, Monika; Stolle, Claudia (2023): GRACE-FO ML-calibrated magnetic field data. V. 0302. GFZ Data Services. doi.org/10.5880/GFZ.2.3.2023.001
and is available at
ftp://isdcftp.gfz-potsdam.de/grace-fo/MAGNETIC_FIELD/ML/0302/
The GOCE mission is a dedicated gravity field mission. Since the satellite carries three fluxgate magnetometers, these have been calibrated and characterized for pertubations. The standard deviation of geomagnetic quiet time residual with high-performance geomagnetic field model (CHAOS7) is below 13 nT.
The detailed study using Analytical method has been published here:
Michaelis, I., Styp-Rekowski, K., Rauberg, J. et al. Geomagnetic data from the GOCE satellite mission. Earth Planets Space 74, 135 (2022). https://doi.org/10.1186/s40623-022-01691-6
The data has been published here:
Michaelis, Ingo; Korte, Monika (2022): GOCE calibrated and characterised magnetometer data. V. 0205. GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2022.001
and is available at
ftp://isdcftp.gfz-potsdam.de/platmag/MAGNETIC_FIELD/GOCE/Analytical/v0205/
The detailed study using Machine Learning method has been published here:
Styp-Rekowski, K., Michaelis, I., Stolle, C. et al. Machine learning-based calibration of the GOCE satellite platform magnetometers. Earth Planets Space 74, 138 (2022). https://doi.org/10.1186/s40623-022-01695-2
The data has been published here:
Styp-Rekowski, Kevin; Michaelis, Ingo; Stolle, Claudia; Baerenzung, Julien; Korte, Monika; Kao, Odej (2022): GOCE ML-calibrated magnetic field data. V. 0204. GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2022.002
and is available at
ftp://isdcftp.gfz-potsdam.de/platmag/MAGNETIC_FIELD/GOCE/ML/v0204/
and updated here:
Kevin Styp-Rekowski, Ingo Michaelis, Monika Korte, et al. Physics-informed Neural Networks for the Improvement of Platform Magnetometer Measurements. Authorea. January 23, 2024.
DOI: 10.22541/au.170602061.18680921/v1
The data has been published here:
Styp-Rekowski, Kevin; Michaelis, Ingo; Stolle, Claudia; Baerenzung, Julien; Korte, Monika; Kao, Odej (2022): GOCE ML-calibrated magnetic field data. V. 0301. GFZ Data Services. doi.org/10.5880/GFZ.2.3.2022.002
and is available at
ftp://isdcftp.gfz-potsdam.de/platmag/MAGNETIC_FIELD/GOCE/ML/v0301/