Full wavefield decomposition of high‐frequency secondary microseisms reveals distinct arrival azimuths for Rayleigh and Love waves

Abstract

In the secondary microseism band (0.1–1.0 Hz) the theoretical excitation of Rayleigh waves (Rg/LR), through oceanic wave‐wave interaction, is well understood. For Love waves (LQ), the excitation mechanism in the secondary microseism band is less clear. We explore high‐frequency secondary microseism excitation between 0.35 and 1 Hz by analyzing a full year (2013) of records from a three‐component seismic array in Pilbara (PSAR), Australia. Our recently developed three‐component waveform decomposition algorithm (CLEAN‐3C) fully decomposes the beam power in slowness space into multiple point sources. This method allows for a directionally dependent power estimation for all separable wave phases. In this contribution, we compare quantitatively microseismic energy recorded on vertical and transverse components. We find the mean power representation of Rayleigh and Love waves to have differing azimuthal distributions, which are likely a result of their respective generation mechanisms. Rayleigh waves show correlation with convex coastlines, while Love waves correlate with seafloor sedimentary basins. The observations are compared to the WAVEWATCH III ocean model, implemented at the Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), which describes the spatial and temporal characteristics of microseismic source excitation. We find Love wave energy to originate from raypaths coinciding with seafloor sedimentary basins where strong Rayleigh wave excitation is predicted by the ocean model. The total power of Rg waves is found to dominate at 0.35–0.6 Hz, and the Rayleigh/Love wave power ratio strongly varies with direction and frequency.

Matched Field Processing of Three‐Component Seismic Array Data Applied to Rayleigh and Love Microseisms

“…A general agreement between source regions of secondary microseism Rayleigh and Love waves is observed, but on a smaller scale differences are identified. Love waves whose generation mechanism in the secondary microseism range is to date unclear, have in the past been identified to originate from similar azimuths as Rayleigh waves (e.g., Haubrich & McCamy, ; Lacoss et al, ); however, a recent high‐resolution study showed that the azimuths can differ (Gal et al, ). With the current study we are able to estimate the generation regions with the help of multiple arrays and can further constrain the potential generation mechanisms.…”

“…The energy ratio between Rayleigh and Love waves has been under increasing investigation in recent years (e.g., Gal et al, ; Juretzek & Hadziioannou, ; Nishida et al, ; Tanimoto et al, , ). Our observations confirm prior findings that Love waves are stronger in the primary microseism range and equal or weaker on average in the secondary microseism range.…”

“…Our observations confirm prior findings that Love waves are stronger in the primary microseism range and equal or weaker on average in the secondary microseism range. The ratios depend on the geographical location (Juretzek & Hadziioannou, ) and also differ in back azimuth for the respective array (Gal et al, ). In this study we find that different source locations result in different Rayleigh to Love wave ratios, and hence, the ratio is a function of source location, path propagation effects, and geographical position of the array.…”

“…Microseism body waves have received a great deal of attention (e.g., Boue et al, ; Capon, ; Euler et al, ; Farra et al, ; Gal et al, ; Gerstoft et al, ; Gualtieri et al, ; Haubrich & McCamy, ; Koper et al, , ; Lacoss et al, ; Landès et al, ; Liu et al, ; Neale et al, ; Nishida & Takagi, ; Obrebski et al, ; Pyle et al, ; Reading et al, ; Toksöz & Lacoss, ; Traer et al, ; Zhang et al, , ) which can be attributed to the fact that back azimuth and velocity obtained from plane wave beamforming provide information on their spatial source region. On the other hand, the analysis of microseism surface waves (e.g., Behr et al, ; Bromirski & Duennebier, ; Bromirski et al, , ; Brooks et al, ; Cessaro, ; Chevrot et al, ; Friedrich et al, ; Gal et al, ; Juretzek & Hadziioannou, ; Kedar et al, ; Obrebski et al, ; Roux et al, ; Schulte‐Pelkum et al, ; Stehly et al, ) for constraining their source regions has experienced limited application. Triangulation of back azimuths from multiple arrays is a common approach to infer the source regions (e.g., Friedrich et al, ), but if path propagation effects are neglected or the initial back azimuths are biased by near‐field sources the accuracy of the inferred source regions remains questionable.…”

“…These oscillations can be classified into two groups, the primary and secondary microseisms, which vary in generation Microseism body waves have received a great deal of attention (e.g., Boue et al, 2013;Capon, 1973;Euler et al, 2014;Farra et al, 2016;Gal et al, 2015;Gerstoft et al, 2008;Gualtieri et al, 2014;Haubrich & McCamy, 1969;Koper et al, 2009Koper et al, , 2010Lacoss et al, 1969;Landès et al, 2010;Liu et al, 2016;Neale et al, 2017;Nishida & Takagi, 2016;Obrebski et al, 2013;Pyle et al, 2015;Reading et al, 2014;Toksöz & Lacoss, 1968;Traer et al, 2012;Zhang et al, 2009Zhang et al, , 2010 which can be attributed to the fact that back azimuth and velocity obtained from plane wave beamforming provide information on their spatial source region. On the other hand, the analysis of microseism surface waves (e.g., Behr et al, 2013;Bromirski & Duennebier, 2002;Bromirski et al, 2005Bromirski et al, , 2013Brooks et al, 2009;Cessaro, 1994;Chevrot et al, 2007;Friedrich et al, 1998;Gal et al, 2017;Juretzek & Hadziioannou, 2017;Kedar et al, 2008;Obrebski et al, 2012;Roux et al, 2005;Schulte-Pelkum et al, 2004;Stehly et al, 2006) for constraining their source regions has experienced limited application. Triangulation of back azimuths from multiple arrays is a common approach to i...…”