Recovering and monitoring the thickness, density and elastic properties of sea ice from seismic noise recorded in Svalbard

Due to global warming, the decline in the Arctic sea ice has been accelerating over the last four decades, with a rate that was not anticipated by climate models. To improve these models, there is the need to rely on comprehensive field data. Seismic methods are known for their potential to estimate sea-ice thickness and mechanical properties with very good accuracy. However, with the hostile environment and logistical difficulties imposed by the polar regions, seismic studies have remained rare. Due to the rapid technological and methodological progress of the last decade, there has been a recent reconsideration of such approaches. This paper introduces a methodological approach for passive monitoring of both sea-ice thickness and mechanical properties. To demonstrate this concept, we use data from a seismic experiment where an array of 247 geophones was deployed on sea ice in a fjord at Svalbard, between March 1 and 24, 2019. From the continuous recording of the ambient seismic field, the empirical Green's function of the seismic waves guided in the ice layer was recovered via the so-called 'noise correlation function'. Using specific array processing, the multi-modal dispersion curves of the ice layer were calculated from the noise correlation function, and then inverted for the thickness and elastic properties of the sea ice via Bayesian inference. The evolution of sea-ice properties was monitored for 24 days, and values are consistent with the literature, as well as with measurements made directly in the field.

Relative Time Corrections for Historical Analog Seismograms Using the Single-Day Ambient Noise Correlation Function

ABSTRACT This study examines analog seismograms that were generated when most seismic stations had their own clock for timing, making precise comparison of time between different stations difficult. Availability of accurate relative timing facilitates differential travel-time analyses, such as seismic tomography and local earthquake relocations, to be performed using data originally recorded on paper or other physical media. These analyses allow for the investigation of longer-term processes like the earthquake cycle or climate change. We take advantage of the continuous nature of seismic noise to determine the relative time correction between two stations by leveraging the symmetry of the noise correlation function. This procedure is applied to two Global Positioning System-timed stations in the Hawaiian Volcano Observatory network demonstrating subsecond time accuracy. The technique is then applied to analog records from comparable stations between 7 and 10 August in 1988, and relative time corrections of up to about 6 s are obtained. These corrections are confirmed by the relative arrival times of teleseismic P waves of earthquake doublets.

An Adjoint Technique for Estimation of Interstation Phase and Group Dispersion from Ambient Noise Cross Correlations

A method of extracting group and phase velocity dispersions jointly for Love‐ and Rayleigh‐wave observations is presented. This method uses a spectral element representation of a path average Earth model parameterized with density, shear‐wave velocity, radial anisotropy, and VP/VS ratio. An initial dispersion curve is automatically estimated using a heuristic approach to prevent misidentification of the phase. A second step then more accurately fits the observed noise correlation function (NCF) between interstation pairs in the frequency domain. For good quality cross correlations with reasonable signal‐to‐noise ratio, we are able to very accurately fit the spectrum of NCFs and hence obtain reliable estimates of both phase and group velocity jointly for Love and Rayleigh surface waves. In addition, we also show how uncertainties can be estimated with linearized approximations from the Jacobians and subsequently used in tomographic inversions.