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New features in the open source toolkit for developing and evaluating earthquake forecasts

New features in the open source toolkit for developing and evaluating earthquake forecasts


This workflow demonstrates how pyCSEP users can develop multi-resolution Quadtree grids derived from earthquake catalogs. Credit: Tile Map by Carto under CC BY 3.0. Data by OpenStreetMap and contributors within ODbL. Modified from original using QGIS. From Seismic Research Letters (2024). doi: 10.1785/0220240197

An international team of 12 researchers across six institutions recently made valuable improvements to pyCSEP; An exemplary open source software package used to develop and evaluate earthquake prediction experiments.

These improvements significantly enhance the ability of earthquake forecasters to evaluate detailed, region-specific seismic predictions through advanced statistical functions, highlights Dr. Kenny Graham, GNS Statistical Science Seismologist, lead author of the paper published in Seismological Research Letters.

“Using New Zealand as an initial case study, we tested the upgraded pyCSEP code base to base long-term seismic estimates from a global model over a defined geographic area. This new feature provides valuable insight into the predictive skills and comparative performance of global models on a regional scale,” says Dr. Graham. .

Dr. Graham is a key member of the Collaborative for the Study of Earthquake Predictability (CSEP), which is committed to advancing earthquake predictability research through rigorous testing of probabilistic earthquake predictions. The pyCSEP toolkit provides a set of statistical tests that allow researchers to accurately evaluate model performance against observed earthquakes. The tool provides a strict, community-accepted set of rules on how to evaluate earthquake forecasts.

“These developments represent an important step forward in standardizing and comparing earthquake prediction models globally,” Dr. Graham adds. “The results of this case study demonstrate the practical application of these developments and underscore the power of the improved pyCSEP software package.

“It provides governments and researchers with greater confidence in the validity of their earthquake predictions, which is critical for long-term planning and preparedness to increase resilience to the devastating effects of earthquakes.”

New pyCSEP features include:

Access official earthquake catalogs from Italy (Bolletino Seismico Italiano), New Zealand (GeoNet), and the world (Global Centroid Moment Tensor). Creating multi-resolution spatial prediction networks. Adopting non-Poissonian testing methods. Applying a global seismic model to specific areas to measure regional models. Evaluation of alarm-based models.

More information: Kenny M. Graham et al., New Features in the pyCSEP Toolkit for Developing and Evaluating Earthquake Forecasts, Earthquake Research Letters (2024). doi: 10.1785/0220240197

Citation: New Features in the Open Source Toolkit for Developing and Evaluating Earthquake Predictions (2024, October 8) Retrieved October 8, 2024 from https://phys.org/news/2024-10-features-source-toolkit-earthquake.html

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