Bootstrapping Swarm and observatory data to generate candidates for the DGRF and IGRF-13
Creators
- 1. Universidad Complutense de Madrid (UCM) and Geoscience Institute IGEO (CSIC - UCM) (Spain)
- 2. Univ. Ramon Llull - CSIC. Observatori de l'Ebre (OE) (Spain)
- 3. Real Observatorio Geofísico de la Armada (ROA) (Spain)
- 4. Observatorio Geofísico de Toledo, Instituto Geográfico Nacional (IGN) (Spain)
Description
As posted by the Working Group V of the International Association of Geomagnetism and Aeronomy (IAGA), the 13th generation of the International Geomagnetic Reference Field (IGRF) has been released at the end of 2019. Following IAGA recommendations, in this work we present a candidate model for the IGRF-13, for which we have used the available Swarm satellite and geomagnetic observatory ground data for the last year. In order to provide the IGRF-13 candidate, we have extrapolated the Gauss coefficients of the main field and its secular variation to January 1st, 2020. In addition, we have generated a Definitive Geomagnetic Reference Field model for 2015.0 using the same modelling approach, but focussed on a 1-year time window of data centred on 2015.0. To jointly model both satellite and ground data, we have followed the classical protocols and data filters applied in geomagnetic field modelling. Novelty arrives from the application of bootstrap analysis to solve issues related to the inhomogeneity of the spatial and temporal data distributions. This new approach allows the estimation of not only the Gauss coefficients, but also their uncertainties.
Additional details
Identifiers
Publishing Information
- Journal Title
- Earth, Planets and Space (Online)
- Journal Volume
- 72
- Journal Issue
- 1
- Journal Page Range
- vp.
- ISSN
- 1880-5981
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55062020
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING; S58: GEOSCIENCES;
- Descriptors DEI
- ASTROPHYSICS; BOOTSTRAP MODEL; DATA ANALYSIS; FILTERS; GAUSS FUNCTION; RECOMMENDATIONS; SATELLITES; SIMULATION; SPATIAL DISTRIBUTION
- Descriptors DEC
- COMPOSITE MODELS; DATA PROCESSING; DISTRIBUTION; FUNCTIONS; MATHEMATICAL MODELS; PARTICLE MODELS; PHYSICS; PROCESSING
Optional Information
- Copyright
- Copyright (c) 2020 © The Author(s) 2020