Dataset linked to Longobardi et al., 2025

This repository contains the LPDT package, a Python-based workflow for the processing and analysis of seismic waveform data aimed at estimating the initial slope of P-wave signals, following the approach described in Longobardi et al., 2025 (https://www.nature.com/articles/s43247-025-02814-z#Abs1). The package computes peak ground motion paremeters (Pa, Pv, Pd) from vertical-component seismic records and derives LPdT (log–peak displacement vs. time) curves for individual stations. For each seismic event, an average LPdT curve is obtained by combining station-level results. The slope of the average LPdT curve is then used to estimate the moment magnitude (Mw) through empirical scaling relationships, following the methodology described in Longobardi et al. (2025). Input data consist of seismic waveforms in SAC format, organized by event. The processing workflow automatically loops over all events, performs signal conditioning and time-windowed analysis, computes LPdT curves, and stores the results in structured output directories. The repository includes: Python scripts for signal processing, curve fitting, and slope analysis A Jupyter notebook (LPDT_package.ipynb) implementing the full workflow Supporting modules for curvature estimation and fitting procedures Documentation describing inputs, outputs, configuration parameters, and dependencies The LPDT package is intended for research applications in seismology, particularly for the time domain, rapid estimation of earthquake magnitude from early P-wave data.