AbstractUnderstanding seismic tremor wavefields can shed light on the complex functioning of a volcanic system and, thus, improve volcano monitoring systems. Usually, several seismic stations are required to detect, characterize, and locate volcanic tremors, which can be difficult in remote areas or low-income countries. In these cases, alternative techniques have to be used. Here, we apply a data-reduction approach based on the analysis of three-component seismic data from two co-located stations operating in different times to detect and analyze long-duration tremors. We characterize the spectral content and the polarization of 355 long-duration tremors recorded by a seismic sensor located 9.5 km SE from the active vent of Copahue volcano in the period 2012–2016 and 2018–2019. We classified them as narrow- (NB) and broad-band (BB) tremors according to their spectral content. Several parameters describe the characteristic peaks composing each NB episode: polarization degree, rectilinearity, horizontal azimuth, vertical incidence. Moreover, we propose two coefficients $$C_P$$
for describing to what extent the wavefield is polarized. For BB episodes, we extend these attributes and express them as a function of frequency. We compare the occurrence of NB and BB episodes with the volcanic activity (including the level of the crater lake, deformation, temperature, and explosive activity) to get insights into their mechanisms. This comparison suggests that the wavefield of NB tremors becomes more linearly polarized during eruptive episodes, but does not provide any specific relationship between the tremor frequency and volcanic activity. On the other hand, BB tremors show a seasonal behavior that would be related to the activity of the shallow hydrothermal system.