S44A-08:
Predicting High Frequency Wind-wave Generated Seismic Noise: a Way to Remotely Monitor Sea-ice Mechanical State.

Thursday, 18 December 2014: 5:45 PM
Florent Gimbert and Victor C Tsai, Caltech-Seismological Lab, Pasadena, CA, United States
Abstract:
It is commonly accepted that ambient ground motion within the 1 s to 10 s period range (including the so-called secondary microseism peak) is caused by ocean wave interactions that induce pressure fluctuations at the ocean floor through acoustic waves. In recent years, numerical ocean wave models have successfully predicted the maximum amplitude of the secondary microseism peak in the 4 s to 8 s range, where seismic energy is mainly caused by the interaction of ocean swells of typically 8 s to 16 s of periods, i.e. 100-400 m wavelengths, that travel in opposite directions as they are generated by distant storms, by single but fast moving storms or by coastal reflections.

In contrast, little attention has been devoted to the contribution of local wind generated seas characterized by shorter period waves (1 s to 3 s ocean waves, i.e. 1-10 m wavelengths) in the generation of higher frequency seismic noise in coastal regions. While this noise content is becoming increasingly used by seismologists, for example for high resolution ground imaging from dense arrays, its absolute amplitude and frequency dependence has not yet been consistently predicted: this is the purpose of this talk.

We present a simple analytical approach that allows the prediction of ambient seismic noise recorded on land in the 0.5 s to 3 s range from knowledge of the local wind field operating on the surrounding ocean. Ocean waves and their interactions are accounted for within hundreds of kilometers from coastal seismic stations, and a realistic ground structure is considered in the generation and propagation of Rayleigh waves. We show that the amplitude and frequency scaling of hourly noise spectra can be systematically predicted, and thus suggest that seismic stations can complement in-situ measurements in inferring wind sea properties in coastal regions.

Furthermore, we use our new approach to demonstrate that seismic stations deployed on land can be used to remotely study ocean waves in sea ice environments, which is a topic of growing interest due to the role of ocean waves in the current decline of sea ice. We show that sea ice mechanical changes can be monitored at daily timescales using our framework. Our ongoing work consists in combining seismic observations with satellite observations of sea ice concentration and thickness to extract sea ice mechanical strength.