Quantifying the Uncertainty in Ground-Based GNSS-Reflectometry Sea Level Measurements

Global Navigation Satellite System reflectometry (GNSS-R) tide gauges are a promising alternative to traditional tide gauges. However, the precision of GNSS-R sea-level measurements when compared to measurements from a colocated tide gauge is highly variable, with no clear indication of what causes the variability. Here, we present a modeling technique to estimate the precision of GNSS-R sea-level measurements that relies on creating and analyzing synthetic signal-to-noise-ratio (SNR) data. The modeled value obtained from the synthetic SNR data is compared to observed root mean square error between GNSS-R measurements and a colocated tide gauge at five sites and using two retrieval methods: spectral analysis and inverse modeling. We find that the inverse method is more precise than the spectral analysis method by up to 60 for individual measurements but the two methods perform similarly for daily and monthly means. We quantify the contribution of dominant effects to the variations in precision and find that noise is the dominant source of uncertainty for spectral analysis whereas the effect of the dynamic sea surface is the dominant source of uncertainty for the inverse method. Additionally, we test the sensitivity of sea-level measurements to the choice of elevation angle interval and find that the spectral analysis method is more sensitive to the choice of elevation angle interval than the inverse method due to the effect of noise, which is greater at larger elevation angle intervals. Conversely, the effect of tropospheric delay increases for lower elevation angle intervals but is generally a minor contribution

Single station Monitoring of Volcanoes Using Seismic ambient noise

Seismic ambient noise cross correlation is increasingly used to monitor volcanic activity. However, this method is usually limited to volcanoes equipped with large and dense networks of broadband stations. The single station approach may provide a powerful and reliable alternative to the classical “cross-stations” approach when measuring variation of seismic velocities. We implemented it on the Piton de la Fournaise in Reunion Island, a very active volcano with a remarkable multi-disciplinary continuous monitoring. Over the past decade, this volcano was increasingly studied using the traditional cross-correlation technique and therefore represents a unique laboratory to validate our approach. Our results, tested on stations located up to 3.5 km from the eruptive site, performed as well as the classical approach to detect the volcanic eruption in the 1-2 Hz frequency band. This opens new perspectives to successfully forecast volcanic activity at volcanoes equipped with a single 3-component seismometer

Application of Surface wave methods for seismic site characterization

Surface-wave dispersion analysis is widely used in geophysics to infer a shear wave velocity model of the subsoil for a wide variety of applications. A shear-wave velocity model is obtained from the solution of an inverse problem based on the surface wave dispersive propagation in vertically heterogeneous media. The analysis can be based either on active source measurements or on seismic noise recordings. This paper discusses the most typical choices for collection and interpretation of experimental data, providing a state of the art on the different steps involved in surface wave surveys. In particular, the different strategies for processing experimental data and to solve the inverse problem are presented, along with their advantages and disadvantages. Also, some issues related to the characteristics of passive surface wave data and their use in H/V spectral ratio technique are discussed as additional information to be used independently or in conjunction with dispersion analysis. Finally, some recommendations for the use of surface wave methods are presented, while also outlining future trends in the research of this topic

Statistical signal processing workshop (SPP)

In this paper, we present MUSIQUE, an algorithm designed to analyze seismic signals recorded by arrays of three-component seismic sensors. Using the original MUSIC algorithm [1], azimuth and slowness (or velocity) of incident waves are estimated. The quaternion-MUSIC algorithm [2, 3] is then used to characterize the polarization properties of the waves. In this way, Love and Rayleigh waves are distinguished and their respective properties retrieved. This allows the characterization of the seismic wave field and the soil structure underneath the seismic array, which are important parameters for the estimation of seismic hazards

Diffracted wave-field decomposition and multi-dimensional site effects in the Argostoli valley, Greece

International audienceEffects of seismic ground motion induced by surface geology and geometry are known to be associated with the generation of a substantial proportion of surface waves. As a consequence, surface waves significantly contribute to ground-motion variability and site amplification. There is a growing body of literature recognizing that an understanding of physical patterns of the wavefield crossing a site is the key aspect to characterize and quantify them. However, this task remains technically challenging due to the complexity of such effects as well as the limitations of geophysical investigations, especially in case of small sedimentary valleys. The present study attempts to investigate the waves propagating across two two-dimensional dense seismic arrays from a number of earthquakes, and explore the extent to which they are contributing to the multi-dimensional site effects. The arrays were deployed in the small-size, shallow alluvial valley of Koutavos-Argostoli, located in Cephalonia Island, Greece, and consisted of three-component velocimeters with interstation distances ranging from 5 to 160 meters. A set of 46 earthquakes, with magnitudes between 2 and 5 and epicentral distances up to 200 km, was analyzed by using an advanced seismic array processing technique, MUSIQUE. The phase velocity, backazimuth and energy of the dominant waves crossing the array were extracted, and their identification as Love or prograde/retrograde Rayleigh waves was obtained. The results clearly indicate a predominance of scattered surface waves (up to 60 per cent of total energy), mainly from the closest valley edges, above the fundamental frequency (∼1.5 Hz) of the valley. Love waves dominate the low-frequency wavefield (< 3 Hz) while Rayleigh waves dominate some high-frequency bands. An excellent consistency is observed, in a given frequency range, among the dominance of the type of diffracted surface waves, group velocities estimated from the ground velocity structure, and site amplification. The outcomes of this research provide a better understanding of the contribution of edge-diffracted surface waves and the 2D/3D site amplification at small and shallow alluvium valleys like Argostoli. The method applied here can be used to calibrate and validate 3D models for simulating seismic ground motion