SEISMIC LOCATION IMPROVEMENTS FROM AN OBS/H TEMPORARY NETWORK IN SOUTHERN TYRRHENIAN SEA

Abstract

We present the first investigation performed on the seismicity of Southern Tyrrhenian Sea, off-shore Sicily with the contribution of data from broad-band ocean bottom seismometers and hydrophones (OBS/H). Off-shore data were recorded during the TYrrhenian Deep-sea Experiment (TYDE) from December 2000 to May 2001 in the Southern Tyrrhenian Sea. Hypocenter locations of a cluster of 53 seismic events which occurred in March 2001 in north-eastern Sicily were estimated by the integration of land (permanent network) and off-shore (temporary network) data and compared with locations estimated from land data only. The scatter of the cluster was evaluated by dispersion parameters. The off-shore data significantly reduced the scatter of the swarm hypocenters also restricting the depth range of the cluster. Moreover, space trends of the event distribution originally shown by the land data were only partially confirmed by the land-sea joint data. In order to assess the efficiency of a land-sea integrated network with respect to a land-based network in terms of hypocenter mislocations in the subject area, we performed simulations by assuming a grid distribution of earthquakes and a recent local 3D velocity model, computing synthetic arrival times of body waves to the stations of both network configurations (integrated and land-based) perturbing the computed times and relocating earthquakes by inversion. The results of the synthetic tests demonstrated that the presence of sea bottom stations in the Tyrrhenian Basin can reduce the mislocations of large magnitude and/or superficial earthquakes in the southernmost Calabria and Messina Strait and of low magnitude and/or deep earthquakes in north-eastern Sicily. The accuracy of synthetic earthquake locations obtained including OBS/H data provides additional support to the interpretation of the cluster occurred in March 2001 and the opportunity of long-term installation of an off-shore network like TYDE in the study region.