Description: The immense advances in computer power achieved in the last decades have had a significant impact in Earth science, providing valuable research outputs that allow the simulation of complex natural processes and systems, and generating improved forecasts. The development and implementation of innovative geoscientific software is currently evolving towards a sustainable and efficient development by integrating models of different aspects of the Earth system. This will set the foundation for a future digital twin of the Earth. The codification and update of this software require great effort from research groups and therefore, it needs to be preserved for its reuse by future generations of geoscientists. Here, we report on Geo-Soft-CoRe, a Geoscientific Software & Code Repository, hosted at the archive DIGITAL.CSIC. This is an open source, multidisciplinary and multiscale collection of software and code developed to analyze different aspects of the Earth system, encompassing tools to: 1) analyze climate variability; 2) assess hazards, and 3) characterize the structure and dynamics of the solid Earth. Due to the broad range of applications of these software packages, this collection is useful not only for basic research in Earth science, but also for applied research and educational purposes, reducing the gap between the geosciences and the society. By providing each software and code with a permanent identifier (DOI), we ensure its self-sustainability and accomplish the FAIR (Findable, Accessible, Interoperable and Reusable) principles. Therefore, we aim for a more transparent science, transferring knowledge in an easier way to the geoscience community, and encouraging an integrated use of computational infrastructure.

Description: Wide-angle seismic reflection/refraction (WA) surveys provide data that can be modeled to obtain lithospheric-scale P-wave velocity (VP) models. The interpretation of these datasets is often performed as a laborious and time-consuming trial-and-error procedure, in which the relevant model parameters (layer thickness and VP) are manually adjusted until the forward modeling matches the observed travel-times. In this work, we present a fully automatic iterative nonlinear approach to invert WA datasets based on the simulated annealing technique. We test our proposed approach with data from the MARCONI-3 WA profile (southern Bay of Biscay) and compare the outcome with an existing detailed interpretation, discussing the similarities between the two models and the agreement between our model and the observed travel-times.