The seismic activity of a planet can be described by the corner magnitude, events larger than which are extremely unlikely, and the seismic moment rate, the long-term average of annual seismic moment release. Marsquake S1222a proves large enough to be representative of the global activity of Mars and places observational constraints on the moment rate. The magnitude-frequency distribution of relevant Marsquakes indicates a b-value of 1.17, but with its uncertainty and a volcanic region bias, b=1 is still possible. The moment rate is likely between 1.5e15 Nm/a and 1.6e18 Nm/a, with a marginal distribution peaking at 4.9e16 Nm/a. Comparing this with pre-InSight estimations shows that these tended to overestimate the moment rate, and that 30 % or more of the tectonic deformation may occur silently, whereas the seismicity is probably restricted to localized centers rather than spread over the entire planet.

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.

In 2007, the National Academies designated “understanding the structure & composition of the lunar interior” (to provide fundamental information on the evolution of a differentiated planetary body) as the second highest lunar science priority that needed to be addressed. Here we present the current status of the planned response of the Lunar Geophysical Network (LGN) team to the upcoming New Frontiers-5 AO. The Moon represents an end-member in the differentiation of rocky planetary bodies. Its small size (and heat budget) means that the early stages of differentiation have been frozen in time. But despite the success of the Apollo Lunar Surface Experiment Package (ALSEP), significant unresolved questions remain regarding the nature of the lunar interior and tectonic activity. General models of the processes that formed the present-day lunar interior are currently being challenged. While reinterpretation of the Apollo seismic data has led to the identification of a lunar core, it has also produced a thinning of the nearside lunar crust from 60-65 km in 1974 to 30-38 km today. With regard to the deep mantle, Apollo seismic data have been used to infer the presence of garnet below ~500 km, but the same data have also been used to identify Mg-rich olivine. A long-lived global lunar geophysical network (seismometer, heat flow probe, magnetometer, laser retro-reflector) is essential to defining the nature of the lunar interior and exploring the early stages of terrestrial planet evolution, add tremendous value to the GRAIL and SELENE gravity data, and allow other nodes to be added over time (ie, deliver the International Lunar Network). Identification of lateral and vertical heterogeneities, if present within the Moon, will yield important information about the early presence of a global lunar magma ocean (LMO) as well as exploring LMO cumulate overturn. LGN would also provide new constraints on seismicity, including shallow moonquakes (the largest type identified by ALSEP with magnitudes between 5-6) that have been linked to young thrust fault scarps, suggesting current tectonic activity. Advancing our understanding of the Moon’s interior is critical for addressing these and many other important lunar and Solar System science and exploration questions, including protection of astronauts from the strong shallow moonquakes.

The Seismometer to Investigate Ice and Ocean Structure (SIIOS) project is exploring the science capabilities of seismometers in ocean world analog environments. Ocean worlds, such as Europa, Enceladus and Titan, have thick global icy shells overlying liquid oceans. The icy shells may be seismically active due to tidal stresses. SIIOS tests several seismometers in a small-aperture array in a mock-lander configuration to quantify the ability to detect, locate, and identify seismic sources, as well as constrain local ice structure. The SIIOS experiment was deployed on two terrestrial analogs for ocean worlds. We first deployed on Gulkana Glacier in Alaska in September 2017, and then deployed in Northwestern Greenland, over a subglacial lake from May 2018-August 2018. Both areas serve as analog locations for Europa due to the layering of ice, water and rock. Gulkana was a relatively noisy site due to surface runoff and drainage, higher topographic variation (inducing rockfalls), and proximity to active plate boundaries. Greenland was a quieter site, in part due to its geologic setting high on the ice sheet, as well as from the installation process. During the Greenland deployment, we covered instruments with a large aluminum box that was buried, thus reducing noise from atmospheric and thermal effects. At both analog sites, the instruments passively recorded seismicity and seismic background noise. The passive data was used to create power spectral density (PSDs) and then probability density functions (PDFs), of the background noise. The PDFs of Gulkana showed higher noise levels compared to those of Greenland. Using the passive data, we detected and identified events originating from ice quakes, and in the case of Gulkana; rockfalls and drainage from a nearby moulin. A frequency-dependent polarization analysis was also conducted to indicate the dominant directionality of the background signals through time. The results indicate how background or ambient signals could be used on ocean worlds to characterize the local seismicity.

Introduction: Ocean Worlds are of high interest to the planetary community [1, 2] due to the potential habitability of their subsurface oceans [3–5]. Over the next few decades several missions will be sent to ocean worlds including the Europa Clipper [6], Dragonfly [7], and possibly a Europa lander [8]. The Dragonfly and Europa lander missions will carry seismic payloads tasked with detecting and locating seismic sources. The Seismometer to Investigate Ice and Ocean Structure (SIIOS) is a NASA PSTAR funded project that investigates ocean world seismology using terrestrial analogs. One goal of the SIIOS experiment is characterizing the local seismic environment of our field sites. Here we present an analysis of detected local events at our field sites at Gulkana Glacier in Alaska and in Northwest Greenland approximately 80 km North of Qaanaaq, Greenland (Fig. 1a). Both field sites passively recorded data for about two weeks. We deployed our experiment on Gulkana Glacier in September 2017 (Fig. 1b) and in Greenland in June 2018 (Fig. 1c). At Gulkana there was a nearby USGS weather station [9] which recorded wind data. Temperature data was collected using the MERRA satellite [10]. In Greenland we deployed our own weather station to collect temperature and wind data. Gulkana represents a noisier and more active environment: Temperatures fluctuated around 0C, allowing for surface runoff to occur during the day. The glacier had several moulins, and during deployment we heard several rockfalls from nearby mountains. In addition to the local environment, Gulkana is located close to an active plate boundary (relative to Greenland). This meant that there were more regional events recorded over two weeks, than in Greenland. Greenland’s local environment was also quieter, and less active: Temperatures remained below freezing. The Greenland ice was much thicker than Gulkana (~850 m [11] versus ~100 m [12, 13]) and our stations were above a subglacial lake. Both conditions can reduce event detections from basal motion. Lastly, we encased our Greenland array in an aluminum vault and buried it beneath the surface unlike our array in Gulkana where the instruments were at the surface and covered with plastic bins. The vault further insulated the array from thermal and atmospheric events. Event Detection and Clustering: To detect local events we filtered the data between 5-20 Hz. Using the Obspy module in python [14], we performed a short-term average/long-term average (STA/LTA) approach to determine where amplitudes spiked. For short term we used 1.5 seconds and 40 seconds and a ratio of 20 to detect events [15]. Through this approach we detect-ed 104 events at our Greenland site and 2252 events at our Gulkana site. The Gulkana site showed a strong correlation with both temperature and changes in temperature, while Greenland did not show this relationship [16]. Once we had a catalog of events, we performed a hierarchal cluster analysis to cluster events.