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Abstract:
Historically, the study of the seismic structure beneath the Canary Islands using local earthquakes has been hampered by the sparse distribution of recording stations and by the moderate seismic activity. Recently, the number of permanent stations from monitoring networks has significantly increased, from barely one seismometer per island in the early 2000s to more than 10 stations in each the most seismically active ones. Similarly, temporary deployments of broadband stations have also taken place in most of the islands, further increasing the station density. On the other side, the number of recorded earthquakes has also greatly increased. This is due in part to the seismicity associated with the 2011-2012 El Hierro and 2021 La Palma eruptions, but also because of the improvements in the detection capabilities of the monitoring network. Here we present new P and S wave velocity regional models of the Canary archipelago and higher resolution models for the islands of Tenerife, La Palma and El Hierro. The bulk of the arrival time data used to obtain these models comes from the Instituto Geográfico Nacional (IGN) permanent monitoring network. We have augmented this dataset by incorporating arrival time data from recent temporary deployments, obtained using Deep Learning phase pickers. Because of the increased coverage of this new dataset, we are able to image features such as crustal thickness variations, magmatic intrusions, and regions of shallow (crustal) and deep (uppermost mantle) magma storage. Funding has been provided by Spanish Ministry of Science and Innovation projects PID2020-114682RB-C31 and PID2020-114682RB-C32.
