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Data Publication

GOCE ML-calibrated magnetic field data


Styp-Rekowski,  Kevin
External Organizations;


Michaelis,  Ingo
2.3 Geomagnetism, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Stolle,  Claudia
External Organizations;


Baerenzung,  Julien
1.3 Earth System Modelling, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;


Korte,  M.
2.3 Geomagnetism, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Kao,  Odej
External Organizations;

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Styp-Rekowski, K., Michaelis, I., Stolle, C., Baerenzung, J., Korte, M., Kao, O. (2022): GOCE ML-calibrated magnetic field data.

Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5011799
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.