The Superior Province Rifting Earthscope Experiment (SPREE) deployed seismic stations in 2011-2013 throughout Wisconsin, Minnesota, and Ontario. To protect equipment from groundwater damage, SPREE stations were buried at unusually shallow depths, increasing the power of long period noise and facilitating an investigation into the regional effects of atmospheric tides and soil properties (Wolin et al., 2015). Here we utilize the SPREE array to study the effects of solid-earth tides and meteorological conditions, on very long-period seismic noise in the U.S. midcontinent. Continuous seismic data was collected from SPREE and Transportable Array (TA) stations located in Wisconsin and Minnesota (WIMN) between July 2011 and September 2013. This data was “cleaned”, filtered, and averaged to produce a monthly representation of the very-long period signals recorded by the SPREE stations. The signals showed diurnal (24 hr) and semidiurnal (12 hr) periodicities, whose magnitudes and dominance vary seasonally. Using cross correlations, we compare our very-long period observations with theoretical solid-earth tides (Milbert, 2018) as well as meteorological components in the WIMN region. Meteorological data, specifically temperature and pressure, was obtained from the National Oceanic and Atmospheric Administration’s (NOAA) National Center for Environmental Information (NCEI). Solid-earth tides result from the gravitational pull of the moon and sun, and have previously been documented in seismic data (e.g. Pillet et al.,1994; Lambotte et al., 2005). We observe a distinct correlation between theoretical solid-earth tides and very-long period signals in seismic data from SPREE and TA stations in the WIMN region, where one frequency component is correlated while the other appears delayed. In addition, we observe a remarkable seasonal change in SPREE recordings of these signals, but not in TA recordings. We will report our findings from testing the hypothesis that the observed very-long period signals in SPREE data are a combination of both tidal and thermal effects and that these cumulative effects are the result of the unusual burial depth of SPREE stations.

We are engaging citizen scientists in an experiment to test if many human ears can replace the process of a professional seismologist in identifying dynamically triggered seismic events. Ordinarily, this process involves interactive data processing and visualization efforts on a volume of earthquake recordings (seismograms) that exploded during the recent big-data revolution, for example through EarthScope. In this citizen seismology project, we ask citizens to listen to relevant sections of seismograms that are accelerated to audible frequencies. This approach has five advantages: 1) The human ear implicitly performs a time-frequency analysis and is capable of discerning a wide range of different signals, 2) Many human ears listening to the same data provides statistics that rank seismograms in order of their likelihood to contain a recording of a triggered event, which is helpful to researchers’ analysis of this data as well as to 3) the ability of a deep-learning algorithm to model the boolean identifications or bulk statistics of the analyses, 4) the project has the potential to enhance informal learning because of the online platform that hosts the project, Zooniverse, is available to people of all identities and hosts many other citizen science projects, and 5) it helps prepare our team for diverse post-graduation careers as part of IDEAS, an NRT program at Northwestern University. The events we are asking citizens to help identify via listening are small seismic events such as local earthquakes and tectonic tremor, that occur in response to transient stresses from passing seismic surface waves from a large, distant earthquake. While much research progress has been made in understanding how these events are triggered, there is no reliable deterministic recipe for their occurrence. The aim of our project is to enlist the help of citizens to increase the data set of known triggered seismic events and known absences of triggered events in order to help researchers unravel key aspects of that recipe. A better understanding of triggered seismic events is expected to provide important clues towards a fundamental understanding of all seismic activity, including damaging earthquakes.

On November 4, 2013, residents near a quarry in the western suburbs of Chicago felt shaking from a rare, small earthquake. The USGS reported a magnitude of 3.2 and Dr. Robert Herrmann reported a dip-slip source mechanism from analyzing surface wave amplitudes recorded by USArray stations. With the goal of detecting potential aftershocks in this region of low seismicity and possibly gaining more insight into the source mechanism, a broadband seismic station was installed in the source region by researchers of Northwestern University. Due to the station’s suburban setting and proximity to various transportation arteries, industrial operations, and city infrastructure including a deep tunnel and reservoir, detecting and discriminating small earthquakes from urban noise events poses a serious challenge. Average daily noise levels can be 50 dB above typical noise levels for broadband seismometers in Illinois in pertinent frequency bands, so aftershock signals can be buried deep within the noise, rendering typical STA/LTA detection methods relatively ineffective. A preliminary analysis of several months of waveform data identified seismic signals from ~1000 events. None of these events occurred on a Sunday or at night, implying an anthropogenic origin and further illustrating the challenge. Recorded signals from these events span a wide range of waveforms, rendering popular detection methods like template matching less effective than in other settings. We aim to define and engineer a set of waveform features to aid with seismic event detection using data from a single broadband station in a noisy, urban environment. To identify useful spectral parameters, we first computed power spectral density (PSD) estimates using segments ranging from the hour-scale to the second-scale. Week-long spectrograms of the PSD estimates revealed characteristic frequencies that are likely associated with routine quarry operations. Select features were then tested for their ability to detect regional and local seismic events for one month of data. We will present the results of this analysis, including the performance of several features and discuss their respective benefits and limitations for seismic event detection in an urban environment.

Continental rifting is a critical component of the plate tectonic paradigm, and occurs in more than one mode, phase, or stage. While rifting is typically facilitated by abundant magmatism, some rifting is not. We aim to develop a better understanding of the fundamental processes associated with magma-poor (dry) rifting. Here, we provide an overview of the NSF-funded Dry Rifting In the Albertine-Rhino graben (DRIAR) project, Uganda. The project goal is to apply geophysical, geological, geochemical, and geodynamic techniques to investigate the Northern Western Branch of the East African Rift System in Uganda. We test three hypotheses: (1) in magma-rich rifts, strain is accommodated through lithospheric weakening from melt, (2) in magma-poor rifts, melt is present below the surface and weakens the lithosphere such that strain is accommodated during upper crustal extension, and (3) in magma-poor rifts, there is no melt at depth and strain is accommodated along pre-existing structures such as inherited compositional, structural, and rheological lithospheric heterogeneities. Observational methods in this project include: passive seismic to constrain lithospheric structure and asthenospheric flow patterns; gravity to constrain variations in crustal and lithospheric thickness; magnetics to constrain the thermal structure of the upper crust; magnetotellurics to constrain lithospheric thickness and the presence of melt; GNSS to constrain surface motions, extension rates, and help characterize mantle flow; geologic mapping to document the geometry and kinematics of active faults; seismic reflection analyses of intra-rift faults to document temporal strain migration; geochemistry to identify and quantify mantle-derived fluids in hot springs and soil gases; and geodynamic modeling to develop new models of magma-poor rifting processes. Fieldwork will begin in January 2022 and the first DRIAR field school is planned for summer 2022. Geodynamic modeling work and morphometric analyses are already underway.