Future mission carrying seismometer payloads to icy ocean worlds will measure global and local seismicity to determine where the ice shell is seismically active. We use two locations, a seismically active site on Gulkana Glacier, Alaska, and a more seismically quiet site on the northwestern Greenland Ice Sheet as geophysical analogs. We compare the performance of a single-station seismometer against a small-aperture seismic array to detect both high (> 1 Hz) and low (< 0.1 Hz) frequency events at each site. We created catalogs of high frequency (HF) and low frequency (LF) seismicity at each location using the automated Short-Term Average/ Long-Term Average technique. We find that with a 2-meter small-aperture seismic array, our detection rate increased (9 % for Alaska, 46% for Greenland) over the single-station approach. At Gulkana, we recorded an order of magnitude greater HF events than the Greenland site. We ascribe the HF events sources to a combination of icequakes, rockfalls, and ice-water interactions, while very high frequency events are determined to result from bamboo poles that were used to secure gear. We further find that local environmental noise reduces the ability to detect low-frequency global tectonic events. Based upon this study, we recommend that future missions consider the value of the expanded capability of a small array compared to a single station, design detection algorithms that can accommodate variable environmental noise, and assess the potential landings sites for sources of local environmental noise that may limit detection of global events.

Angela Marusiak

and 6 more

Titan’s surface icy shell is likely composed of water ice and methane clathrate [1, 2]. Methane clathrate may play a role in Titan’s methane cycle [3–5] affect Titan’s thermal profile [6] , and may affect the habitability of Titan’s ocean. Although the bulk properties of clathrates are similar to those of pure water ice, the thermal conductivity of methane clathrate is about 20% the value for pure water ice [7, 8]. The lower thermal conductivity acts to insulate Titan’s icy shell, changing the thermal profile of Titan. As seismic wave speeds [9, 10] and attenuation [11] are dependent on temperature, any changes to the thermal profile will result in changes to seismic waveforms recorded by seismic instrumentation. Here, we compare the seismic waveforms of model with a 100 km thick pure water ice shell, versus a model with a 10 km clathrate lid over 90 km of pure water ice. Our results have implications for the upcoming Dragonfly mission, which will carry seismic instrumentation as part of its payload [12]. Methods: We use PlanetProfile [13] to create interior structures models of a pure water ice shell and a model with a pure water ice shell with a 10 km clathrate lid. The interior structure models are used as inputs with AxiSEM [14] and Instaseis ([15] to generate seismic waveforms. We interpret the results to quantify the differences in seismic velocities, arrival times of seismic phases, and amplitudes of seismic waveforms at the surface of Titan. Results: The interior structure models show a clathrate lid will reduce the conductive lid thickness by ~ 2/3 compared to the pure water ice shell model. As a result, the clathrate lid model reaches higher temperatures at shallower depths (Figure 1a). The temperature profile affects the seismic velocity (Figure 1b), and the seismic quality factor (Q, Figure 1c) profiles. A clathrate lid creates a steeper negative gradient in seismic velocities and Q. The greatest difference in seismic velocities occurs at the base of the clathrate lid (Figure 2). Because of the change in seismic velocities, the arrival times and observable distances of seismic phases will be different between the two models. Using TauP [16], we calculate the differences for several seismic phases. We find that the change in seismic velocity profile results in a difference of a few seconds at most in arrival times. The range of observable distances will also vary by a few degrees. The small changes might be noticeable on waveforms, but would require high signal to noise ratios, and precise determinations of location and depth of the event. The changes in seismic velocities and Q will also impact the observed ground motion. Using AxiSEM and InstaSEIS, we create a database of seismic waveforms spaced 1 degree in epicentral distance. We compare the same event magnitude and distance between source and seismometer for the two models. For each waveform we calculate the root mean square (RMS) using ground acceleration.