Search

International audience; The InSight mission expects to operate a geophysical observatory on Mars for at least two Earth years from late 2018. InSight includes a seismometer package, SEIS. The Marsquake Service (MQS) is created to provide a first manual review of the seismic data returned from Mars. The MQS will detect, locate, quantify and classify seismic events, whether tectonic or impact in origin. A suite of new and adapted methodologies have been developed to allow location and quantification of seismic events at the global scale using a single station, and a software framework has been developed that supports these methods. This paper describes the expected signals that will be recorded by SEIS, the methods used for their identification and interpretation, and reviews the planned MQS operational procedures. For each seismic event, the MQS will locate events using all available body and surface phases, using the best estimates of the Martian structure, which will become more accurate as more Martian marsquakes are identified and located. The MQS will curate the Mars seismicity catalogue, with all events being relocated to use revised suites of structure models as they are introduced.

The InSight mission to Mars is well underway and will be the first mission to acquire seismic data from a planet other than Earth. In order to maximise the science return of the InSight data, a multifaceted approach will be needed that seeks to investigate the seismic data from a series of different frequency windows, including body waves, surface waves, and normal modes. Here, we present a methodology based on globally-averaged models that employs the long-period information encoded in the seismic data by looking for fundamental-mode spheroidal oscillations. From a preliminary analysis of the expected signal-to-noise ratio, we find that normal modes should be detectable during nighttime in the frequency range 5–15 mHz. For improved picking of (fundamental) normal modes, we show first that those are equally spaced between 5–15 mHz and then show how this spectral spacing, obtained through autocorrelation of the Fourier-transformed time series can be further employed to select normal mode peaks more consistently. Based on this set of normal-mode spectral frequencies, we proceed to show how this data set can be inverted for globally-averaged models of interior structure (to a depth of $\sim 250~\mbox{km}$ ), while simultaneously using the resultant synthetically-approximated normal mode peaks to verify the initial peak selection. This procedure can be applied iteratively to produce a “cleaned-up” set of spectral peaks that are ultimately inverted for a “final” interior-structure model. To investigate the effect of three-dimensional (3D) structure on normal mode spectra, we constructed a 3D model of Mars that includes variations in surface and Moho topography and lateral variations in mantle structure and employed this model to compute full 3D waveforms. The resultant time series are converted to spectra and the inter-station variation hereof is compared to the variation in spectra computed using different 1D models. The comparison shows that 3D effects are less significant than the variation incurred by the difference in radial models, which suggests that our 1D approach represents an adequate approximation of the global average structure of Mars.