4.4 Article

Evaluation of using R-SCHA to simultaneously model main field and secular variation multilevel geomagnetic data for the North Atlantic

期刊

出版社

ELSEVIER
DOI: 10.1016/j.pepi.2016.11.008

关键词

Geomagnetism; Main field; Secular variation; Regional modelling; Revised Spherical Cap Harmonic Analysis; North Atlantic Ocean

资金

  1. Spanish Ministerio de Economia y Competitividad [CTM201452182-C3-1-P]
  2. European Union's Horizon under the Marie Sklodowska-Curie [659901]
  3. Marie Curie Actions (MSCA) [659901] Funding Source: Marie Curie Actions (MSCA)

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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. (C) 2016 Elsevier B.V. All rights

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