Forecasting secular variation using physics-informed neural networks for IGRF-14

Abstract In response to the call for candidate models for the 14th generation of the International Geomagnetic Reference Field (IGRF) by the Geomagnetic Field Modeling Working Group (V-MOD) of the International Association of Geomagnetism and Aeronomy (IAGA), we present the University of Leeds candi...

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Autori principali:	N. Shakespeare-Rees, P. W. Livermore, C. J. Davies, H. F. Rogers, C. D. Beggan, W. J. Brown, C. C. Finlay
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	SpringerOpen 2026-04-01
Serie:	Earth, Planets and Space
Soggetti:	Physics Informed Neural Networks (PINNs) Regional Inversion Methods Secular Variation Outer Core Flow IGRF-14
Accesso online:	https://doi.org/10.1186/s40623-026-02427-6
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