Hypocentral temperatures, crustal seismogenic thickness and 3D thermal model of the South Caribbean and NW South America

DOI

This data repository contains the 3D steady-state thermal field computed for the South Caribbean and NW South America down to 75 km depth, the modelled hypocentral temperatures, the depths to the upper and lower stability transitions, as well as the seismogenic thickness calculated from selected earthquakes of the ISC Bulletin (International Seismological Centre, 2022). All methodological details can be found in the main publication (see section 2).

We used the uppermost 75 km of the gravity-constrained structural and density model of Gómez-García et al. (2020, 2021) to derive the 3D thermal configuration of the study area. A steady-state approach was followed, in which upper and lower boundary conditions were set to run the thermal experiments using the software GOLEM (Cacace & Jacquey, 2017; Jacquey & Cacace, 2017).

We selected earthquakes from the ISC Bulletin from January 1980 to January 2021 (International Seismological Centre, 2022), considering the magnitude of completeness for different periods, removing earthquakes without depth, set as 0 km or fixed, as well as those with reported hypocentral depth errors >30 km. Of this set, we selected the crustal earthquakes, located between the topo-bathymetry from the GEBCO relief (Weatherall et al., 2015) and the Moho depth from the GEMMA model (Reguzzoni & Sampietro, 2015), interpolated to a resolution of 5 km. From this earthquake subset we computed the upper and lower stability transitions for seismogenesis, as the 10th and 90th percentiles (D10 and D90), respectively, of the hypocentral depths. These percentiles were mapped on a latitude-longitude grid, using for each grid node its 20 closest earthquakes as sample.

The hypocentral temperatures and the temperatures at the D10 and D90 crustal depths were calculated from the lithospheric-scale thermal model. Lastly, the crustal seismogenic thickness was computed as the difference between D90 and D10 for each grid node. For more details about the modelling approach and interpretation of the results, we kindly ask the reader to refer to the main publication: Gomez-Garcia et al., (2022).

Identifier
DOI https://doi.org/10.5880/GFZ.4.5.20202.005
Related Identifier https://doi.org/10.5880/GFZ.4.5.2020.003
Related Identifier https://doi.org/10.5194/se-12-275-2021
Related Identifier https://doi.org/10.31905/D808B830
Related Identifier https://doi.org/10.1029/2019JB018474
Related Identifier https://doi.org/10.1029/2019JB018475
Related Identifier https://doi.org/10.1016/j.jag.2014.04.002
Related Identifier https://doi.org/10.1002/2015EA000107
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:7612
Provenance
Creator Gómez-García, Ángela María ORCID logo; González, Álvaro ORCID logo; Cacace, Mauro ORCID logo; Scheck-Wenderoth, Magdalena ORCID logo; Monsalve, Gaspar ORCID logo
Publisher GFZ Data Services
Contributor Gómez-García, Ángela María; Scheck-Wenderoth, Magdalena; Monsalve, Gaspar
Publication Year 2022
Rights CC BY 4.0; http://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact Gómez-García, Ángela María (GFZ German Research Centre for Geosciences, Potsdam, Germany)
Representation
Resource Type Dataset
Discipline Geosciences
Spatial Coverage (-83.000W, 5.200S, -62.000E, 16.000N); 3D thermal model of the South Caribbean and NW South America