hide
Free keywords:
-
Abstract:
For government officials and the public to act on real-time forecasts of earthquakes, the seismological
community needs to develop confidence in the underlying scientific hypotheses of
the forecast generating models by assessing their predictive skill. For this purpose, the Collaboratory
for the Study of Earthquake Predictability (CSEP) provides cyberinfrastructure and
computational tools to evaluate earthquake forecasts. Here, we introduce pyCSEP, a Python
package to help earthquake forecast developers embed model evaluation into the model development
process. The package contains the following modules: (1) earthquake catalog access
and processing, (2) data models for earthquake forecasts, (3) statistical tests for evaluating
earthquake forecasts, and (4) visualization routines. pyCSEP can evaluate earthquake forecasts
expressed as expected rates in space-magnitude bins, and simulation-based forecasts
that produce thousands of synthetic seismicity catalogs. Most importantly, pyCSEP contains
community-endorsed implementations of statistical tests to evaluate earthquake forecasts, and
provides well defined file formats and standards to facilitate model comparisons. The toolkit
will facilitate integrating new forecasting models into testing centers, which evaluate forecast
models and prediction algorithms in an automated, prospective and independent manner,
forming a critical step towards reliable operational earthquake forecasting.
