Strain Pattern and Kinematics of the Canary Islands from GNSS Time Series Analysis

Abstract

Following the 2004 seismic unrest at Tenerife and the 2011–2012 submarine eruption at El Hierro, the number of Global Navigation Satellite System (GNSS) observation sites in the Canary Islands (Spain) has increased, offering scientists a useful tool with which to infer the kinematics and present-day surface deformation of the Canary sector of the Atlantic Ocean. We take advantage of the common-mode component filtering technique to improve the signal-to-noise ratio of the velocities retrieved from the daily solutions of 18 permanent GNSS stations distributed in the Canaries. The analysis of GNSS time series spanning the period 2011–2017 enabled us to characterize major regions of deformation along the archipelago through the mapping of the 2D infinitesimal strain field. By applying the triangular segmentation approach to GNSS velocities, we unveil a variable kinematic behaviour within the islands. The retrieved extension pattern shows areas of maximum deformation west of Tenerife, Gran Canaria and Fuerteventura. For the submarine main seismogenic fault between Tenerife and Gran Canaria, we simulated the horizontal deformation and strain due to one of the strongest (mbLg 5.2) earthquakes of the region. The seismic areas between islands, mainly offshore Tenerife and Gran Canaria, seem mainly influenced by the regional tectonic stress, not the local volcanic activity. In addition, the analysis of the maximum shear strain confirms that the regional stress field influences the E–W and NE–SW tectonic lineaments, which, in accordance with the extensional and compressional tectonic regimes identified, might favour episodes of volcanism in the Canary Islands.

Detection of Tectonic and Crustal Deformation using GNSS Data Processing: The Case of PPGnet

“…Each coordinate time series (example at Figure 6) was checked for searching of jumps (usually as a result of near earthquake), co-seismic effect (which introduce exponential behavior of time seriesas in Ansari and Bae (2020) [20]) and yearly periodicities (usually as result of temperature deformation of the building where the station is located - Figure 5a). Due to using double differenced processing with good daily repeatability, we don't use the commonmode component filtering technique [21] for improving signal-to-noise ratio of the velocities. The results, i.e.…”

Recent Crustal Deformation Based on Interpolation of GNSS Velocity in Continental China

“…If the crust is thought of as an elastomer, the strain or strain rate can be calculated from the observed displacement or velocity. The strain tensor of the earth's surface can be expressed as a partial derivative of displacement in spherical coordinates [16,43]. The methods of strain rate calculation are divided into segment approach and gridded approaches.…”

“…With the rapid progress of Global Navigation Satellite System (GNSS) technology, as well as the continuous improvement of GNSS accuracy and space-time resolution, GNSS has gradually become an essential observation means in geoscience research, especially in crustal deformation research. Deformation research based on GNSS is ongoing, which provides a data reference basis for the different scales of subsequent deformation research [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]. Although many scholars have studied the velocity field data of GNSS stations, with the increasing time span of the data, previous studies have a certain timeliness.…”

2D strain rate and ground deformation modelling from continuous and survey mode GNSS data in El Hierro, Canary Islands

“…However, tackling challenging studies such as monitoring volcanoes and detecting pre-eruptive magmatic processes (e.g. Segall, 2010;Arnoso et al, 2020) requires the reconstruction of a reliable image of the deformation field. In this case, it is necessary to bridge the spatial resolution gap through the integration of continuous and repeated GNSS observations.…”