CORBASS - CORrelation Based Archeomagnetic SnapShot model
Cite as:
Schanner, Maximilian Arthus; Mauerberger, Stefan (2019): CORBASS - CORrelation Based Archeomagnetic SnapShot model. V. 1.0. GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2019.008
Status
I N R E V I E W : Schanner, Maximilian Arthus; Mauerberger, Stefan (2019): CORBASS - CORrelation Based Archeomagnetic SnapShot model. V. 1.0. GFZ Data Services. https://doi.org/10.5880/GFZ.2.3.2019.008
Abstract
Due to poor global data coverage and large data uncertainties, Holocene magnetic field models are of limited resolution. The most commonly used modeling approach is based on an inversion strategy based on truncated spherical harmonics and does not provide uncertainty estimates. Focusing on snapshots of the magnetic field, the CORBASS (CORrelation Based Archeomagnetic SnapShot model) algorithm breaks with the tradition of truncated models by implementing a field model based on Gaussian processes (GP). This way regions covered well by data can be modeled with higher resolution, while areas of poor coverage remain uncertain. The GP approach provides a posterior covariance, together with the (mean) field model, which naturally serves as model uncertainty estimate. A full description of the model can be found in <TODO: reference to our upcoming paper>.
CORBASS is provided as a collection of python scripts together with an install file for a conda environment. This way CORBASS can be easily set up under various system dependencies. The gitlab page provides installation instructions, documentation and example notebooks and can be found under "Related Work" in the left panel of this page.
A static version of CORBASS is linked under "Files", again in the left panel of this page.
affiliation (affiliationIdentifier=0000-0002-0497-9231 affiliationIdentifierScheme=ORCID): GFZ German Research Centre for Geosciences, Potsdam, Germany
creator
creatorName (nameType=Personal): Mauerberger, Stefan
CharacterString: Due to poor global data coverage and large data uncertainties, Holocene magnetic field models are of limited resolution. The most commonly used modeling approach is based on an inversion strategy based on truncated spherical harmonics and does not provide uncertainty estimates. Focusing on snapshots of the magnetic field, the CORBASS (CORrelation Based Archeomagnetic SnapShot model) algorithm breaks with the tradition of truncated models by implementing a field model based on Gaussian processes (GP). This way regions covered well by data can be modeled with higher resolution, while areas of poor coverage remain uncertain. The GP approach provides a posterior covariance, together with the (mean) field model, which naturally serves as model uncertainty estimate. A full description of the model can be found in <TODO: reference to our upcoming paper>.
CORBASS is provided as a collection of python scripts together with an install file for a conda environment. This way CORBASS can be easily set up under various system dependencies. The gitlab page provides installation instructions, documentation and example notebooks and can be found under "Related Work" in the left panel of this page.
A static version of CORBASS is linked under "Files", again in the left panel of this page.
CI_OnLineFunctionCode (codeList=http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnLineFunctionCode codeListValue=http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnLineFunctionCode_information): information
Released
Software
Abstract
;GFZ German Research Centre for Geosciences, Potsdam, Germany
Files
