Data visualisation and download
contact: nicolas.gillet at univ-grenoble-alpes.fr
Example of visualisation by webgeodyn
Webgeodyn is a Python package that provides web-based visualisations for Gauss coefficients of magnetic field and core flow. It can be installed and run locally on a variety of data formats.
The tool is deployed on the website https://geodyn.univ-grenoble-alpes.fr to show visualisations on several magnetic field and core flow models (CHAOS, COV-OBS, pygeodyn results...). The models can be downloaded from the website in the Download section.
contact: cfinlay at space.dtu.dk
This delivery updates the preliminary geomagnetic datasets and models delivered by DTU. The report delivered at that time described in detail the datasets and processing schemes, the details of the processing schemes are unchanged.
Updated Virtual observatory (GVO) data
From this address one can access a zip file containing updated Swarm GVO data.
This contains updated 4 monthly and 12 monthly GVOs produced using DTU's GVO software, and also (for completeness) the latest 1 monthly official Swarm GVO product (which involves additional processing steps applied by BGS). These were derived from Swarm L1B Mag-L OPER data version 0602. Data up to end of April 2023 was used for the 4 monthly and 1 monthly GVOs and data up to end of 2022 for the 12 monthly GVOs. No update of the Oersted, CHAMP, Cryosat-2 or Grace GVOs is provided in this delivery, the latest versions of these legacy missions are still those of the previous release (see associated zip folders for each mission) as there has been no change in the processing scheme.
Each GVO file includes values for observed field, core field (with estimates of magnetospheric and ionospheric fields removed) and SV (from annual difference of the core field data). The file format follows the Swarm Geomagnetic Virtual Observatories Product Definition, Rev.2B, SW-DS-DTU-GS-004_2-1_GVO_PDD. See Hammer et al. (2021) for full details of the GVO processing algorithm. Further specific details regarding this update are found in the README file in the zipped folder.
Updated Ground Observatory data
A zip file containing updated GO data files in cdf format (following the ESA GVO file specifications) with 1monthly, 4monthly and annual averaging for data based on hourly mean data from 1997 to 2023 at 218 Ground observatories (from the BGS AUX_OBS data product version 0136 from May 2023) can be found at:http://www.spacecenter.dk/files/magnetic-models/GO/GO_data.zip
Each file contains the 'Observed' field (e.g. observed monthly means) and 'Core field' (e.g. revised monthly means) as well as SV derived as annual differences of the 'Core Field'. Full details of the processing of each data file and given in the file Readme_GO.txt inside the zip file.
This format has been successfully used within the consortium within the initial phase of the project e.g. by the Grenoble team. These are updated versions of the GO datasets described in the report of the initial phase of the Swarm+4D Deep Earth: Core project.
Refer to the archived_GO_files for earlier versions of the GO datafiles. These are labelled by version number.
Updated version of the CHAOS field model
Below are links to the CHAOS-7.15 geomagnetic field model, an updated version of the CHAOS-7 geomagnetic field model (Finlay et al., 2020), using Swarm baseline 0602 data up 8th June 2023 and ground observatory data up to end of May 2022 (based on the BGS AUX_OBS data product version 0136 from May 2023). Model coefficients for the time-dependent internal field are provided in spline coefficient and shc formats, while the .mat file contains all parts of the model.Links to software to read and use these files in Python, Matlab and Fortran
Updated vector and scalar satellite data files as used in the CHAOS field model
The link below gives ascii files containing the selected vector and scalar satellite data (from the Swarm, CHAMP, Oersted and Cryosat-2 satellites) used in building the CHAOS-7.15 field model. These contain Swarm data up until early June 2023. The vector field is provided as components in an Earth centred, Earth fixed, spherical polar coordinate system (i.e. radial, southward, eastward components). Estimates of the crustal and external fields based on the CHAOS-7.15 model are also provide for each datum, so users interested in the core field can subtract these if wished. The file header specifies the exact content.
Full Covariance Matrix for Swarm 4 monthly GVOs
link to a full data error covariance matrix for the 4-monthly GVO SV product.
Format is ascii, Covariance matrix of size 900x900 (900= 3 components at 300 GVOs) order as in GVO cdf files.
If a covariance matrix for the core field is required, assuming uncorrelated errors in time one can use the above SV matrix (derived from annual differences of the core field) scaled by a factor 0.5.
This was derived by the following procedure:
1. Load 4 monthly GVO product, core field or SV series
2. Remove large outliers w.r.t. CHAOS-7.15 field model
3. Compute a Gaussian Process fit to each component at each GVO location (squared exponential kernel).
4. Subtract this fit from observations.
5. Standardise the resulting residuals by removing the mean value and dividing by the standard deviation of the residuals from each component at each GVO.
6. Removed all time epochs with gaps in global coverage, except when only GVO was missing, in which case the missing value was replaced by zero.
7. Compute the non-linear Ledoit-Wolf estimator of the covariance matrix (Ledoit and Wolf, 2020) which results in a valid (symmetric, positive definite) covariance matrix.
The Ledoit-Wolf nonlinear shrinkage estimator is designed for estimating large covariance matrices. It is based on a minimum variance criteria and involves retaining all eigenvectors of the empirical covariance matrix but shrinking the eigenvalues based on a nonlinear analytic function of the eigenvalues, based on results from random matrix theory (Ledoit and Wolf, 2020).
Geodynamo simulation data
contact: aubert at ipgp.fr
- Deliverable D-C.1: Long time series of outputs from a geodynamo model approaching Earth’s core conditions
- Deliverable D-E.1: A catalogue of simulated jerks from a geodynamo model approaching Earth’s core conditions)
- Deliverables D-O.1: 3D base state
- Time series of outputs computed at 100% of the parameter space
can all be found here