We present a Python application to download events and data from FDSN webservices (https://www.fdsn.org/webservices/) and compute the events energy Magnitude (Me), producing outputs in several formats (QuakeML, HDF, CSV, HTML). This software has been used to compile a seismic catalogue including Me estimated form P-waves recorded at teleseismic distances in the range 20° ≤ ∆ ≤ 98°, available at GFZ Data Services (Bindi et al., 2023; https://doi.org/10.5880/GFZ.2.6.2023.010). The software complete pipeline (download and energy magnitude computation) can be deployed locally via terminal commands or chained and scheduled on a server to compute the energy magnitude in semi-realtime (e.g. daily or weekly).
This archive disseminated through the GFZ-Data Service includes both results and information as-sociated to Bindi et al. (2023). In particular, the archive includes a seismic catalogue reporting ener-gy magnitude Me estimated form vertical P-waves recorded at teleseismic distances in the range 20°≤ D ≤ 98°, following Di Giacomo et al (2008, 2010). The catalogue is built considering 6349 earth-quakes included in the GEOFON (Quinteros et al, 2021) catalogue with moment magnitude Mw larger than 5 and occurring after 2011. Tools used to compute the energy magnitude are free available. In particular, we used stream2segment (Zaccarelli, 2018) to download data from IRIS (https://ds.iris.edu/ds) and EIDA (Strollo et al., 2021) repositories, and me-compute [Zaccarelli, 2023) to process waveforms and compute Me. The methodology applied to me-compute is also implemented as add-on for SeicomP (GFZ and Gempa, 2020) in order to allow the real time computation of Me (https://github.com/SeisComP/scmert).