Evaluation of using R-SCHA to simultaneously model main field and secular variation multilevel geomagnetic data for the North Atlantic
One efficient approach to modelling the Earth’s core magnetic field involves the inclusion of crossover marine data which cover areas lacking in observatory and repeat station data for epochs when precise three-component satellite magnetic field measurements were not common. In this study, we show h...
Published in: | Physics of the Earth and Planetary Interiors |
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Main Authors: | , , , |
Other Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Elsevier
2017
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Subjects: | |
Online Access: | http://hdl.handle.net/10261/185551 https://doi.org/10.1016/j.pepi.2016.11.008 https://doi.org/10.13039/501100003329 https://doi.org/10.13039/501100000780 |
Summary: | One efficient approach to modelling the Earth’s core magnetic field involves the inclusion of crossover marine data which cover areas lacking in observatory and repeat station data for epochs when precise three-component satellite magnetic field measurements were not common. In this study, we show how the Revised Spherical Cap Harmonic Analysis (R-SCHA) can appropriately provide a continuous-time field model for the North Atlantic region by using multilevel sets of geomagnetic data such as marine, repeat station, observatory, and satellite data. Taking advantage of the properties of the R-SCHA basis functions we can model the radial and horizontal variations of the main field and its secular variation with the most suitable spatial and temporal wavelengths. To assess the best compromise between the data fit and the model roughness, temporal and spatial regularization matrices were implemented in the modelling approach. Two additional strategies were also used to obtain a satisfactory regional model: the opportunity to fit the anomaly bias at each observatory location, and constraining the regional model to the CHAOS-6 model at the end of its period of validity, i.e. 1999–2000, allowing a smooth transition with the predictions of this recent model. In terms of the root mean square error, the degree of success was limited partly because of the high uncertainties associated with some of the datasets (especially the marine ones), but we have produced a model that performs comparably to the global models for the period 1960–2000, thus showing the benefits of using this regional technique. This study was partially funded by the project CTM2014-52182-C3-1-P of the Spanish Ministerio de Economía y Competitividad. F.J.P.C. is funded from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 659901. Peer reviewed |
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