Isolating core field signals in Geomagnetic Virtual Observatory time series using Principle Component Analysis

Brown, William ORCID:; Beggan, Ciaran ORCID:; Hammer, Magnus ORCID:; Finlay, Chris ORCID:; Cox, Grace. 2021 Isolating core field signals in Geomagnetic Virtual Observatory time series using Principle Component Analysis. [Speech] In: IAGA-IASPEI Joint Scientific Assembly 2021, Online, 21-27 Aug 2021. (Unpublished)

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Geomagnetic Virtual Observatories (GVOs) are a method for processing magnetic satellite data in order to simulate the observed behaviour of the geomagnetic field at a fixed location. Signals at a given GVO location will be strongly correlated with its neighbours due to the influence of large-scale external field sources and the biased sampling effect caused by local time precession of the satellite orbit. Using Principal Component Analysis we identify and remove signals related to these noise sources in secular variation residuals, to better resolve core field variations on sub-annual timescales. We apply our methodology to monthly GVOs for the Ørsted, CHAMP, CryoSat-2 and Swarm missions. We identify common principle components representing local time sampling biases and external field sources across all missions. Our analysis is enhanced by focussing on regions of geomagnetic latitude where different external field sources dominate, identifying distinct polar, auroral and low-to-mid latitude regions. Annual differences are often used to calculate SV so as to remove annual and semi-annual external field signals, but these signals can be re-introduced if our corrected SV is integrated back to main field. We find representing secular variation with monthly first differences allows us to identify and remove annual and semi-annual external field variations from the SV, which leads to improved main field series. We are able to produce global grids of GVO time series which better represent core field secular variation at monthly time resolution.

Item Type: Publication - Conference Item (Speech)
Additional Keywords: Geomagnetism
Date made live: 27 Aug 2021 15:41 +0 (UTC)

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