The Gannon Storm’s Impact on Electric and Magnetic1 Fields in Italy: A Regional Perspective
Description
The dataset contains electromagnetic time-series data acquired by the permanent magnetotelluric (MT) monitoring station located on the Gargano Promontory, Italy (GARG), during the Gannon geomagnetic storm. The data provide insight into regional-scale geomagnetic and geoelectric field variations at mid-latitudes and support improved space weather monitoring and hazard mitigation strategies. The dataset is provided in two formats: 1. ASCII (.txt) Format Four files contain time-series data of deconvolved magnetic field components (in nanoteslas, nT) and scaled electric field components (in millivolts per kilometer, mV/km), with a temporal resolution of 1 second. The files correspond to four distinct intervals during the geomagnetic storm, as discussed in the associated publication. Each file includes four columns: Bx: North–South magnetic field By: East–West magnetic field Ex: North–South electric field Ey: East–West electric field 2. HDF5 (.h5) file in MTH5 format The file MAY.h5 contains the same time-series data structured according to the MTH5 specification v0.2.0 [Peacock et al., 2022]. MTH5 is an HDF5-based container designed for the archival and exchange of magnetotelluric time-series data. The MTH5 structure is organized into hierarchical groups, with the top-level SurveyID group containing station-specific subgroups (StationID), calibration filters (Filters), and run-specific subgroups (RunID) that include metadata such as geographic location, sampling rate, channel units, and sensor calibration. Data originally acquired with Metronix data loggers were converted to Metronix JSON and ATSS formats, then imported into the MTH5 structure, using the directory structure with full data description. Further technical information are provided in the accompanying "read me" executable file. Reference: Peacock, J. R., Kappler, K., Ronan, T., Heagy, L., Kelbert, A., & Frassetto, A. (2022). MTH5: An archive and exchangeable data format for magnetotelluric time-series data. Computers & Geosciences, 162, 105102. https://doi.org/10.1016/j.cageo.2022.105102
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Institutions
- Universita degli Studi di Bari Aldo Moro Dipartimento di Scienze della Terra e Geoambientali