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ABSTRACT Seismic data contains a continuous record of wind influenced by different factors across the frequency spectrum. To assess the influences of wind on ground motion, we use colocated wind and seismic data from 110 stations in the Alaska component of the EarthScope Transportable Array. We compare seismic probability power spectral densities and wind speed and direction during 2018 to develop a quantitative measure of the seismic sensitivity to wind. We observe a pronounced increase in seismic energy as a function of wind speed for almost all stations. At frequencies below the microseism band, our observations agree with previous authors in finding that sensor emplacement and ground materials are important, and that much of the wind influence likely comes from associated changes in barometric pressure. Wind has the least influence in the microseism band, but that is only because its contribution to noise is much smaller than the ubiquitous microseism background. At frequencies above the microseism band, we find that wind sensitivity is correlated with land cover type, increasing with vegetation height. This sensitivity varies seasonally, which we attribute to snow insulation, the burial of vegetation and objects around the station, and potentially the role of frozen ground. Wind direction also manifests in seismic data, which we attribute to turbulent air on the lee side of station huts coupling with the ground and the seismometer borehole cap. We find some dependence on bedrock type, with a greater seismic response in unconsolidated sediment. These results provide guidance on site selection and construction, and make it possible to forecast seismic network performance under different wind conditions. When we examine the factors at work in a warming climate, we find reason to anticipate increasing seismic noise from wind in the Arctic over the decades to come. 

The SD-FIRST program helps fill in the gaps of first-generation students’ home-to-college transition, provides a robust support system by connecting existing campus resources, and provides guidance for staff and faculty on interactions and unique challenges with this student population. Programmatic elements specific for first-generation students, driven by evidence-based resiliency research, were developed to provide academic, social, and economic support. The expected outcome of the SD-FIRST program is to achieve a sustainable increased retention and graduation rate, and an increase in emotional intelligence for students participating in the program. The initial cohort of SD-FIRST scholars began in the fall 2021 semester, and the details of the program as well as initial implementation are included in this paper. 

Abstract The addition of 108 infrasound sensors—a legacy of the temporary USArray Transportable Array (TA) deployment—to the Alaska regional network provides an unprecedented opportunity to quantify the effects of a diverse set of site conditions on ambient infrasound noise levels. TA station locations were not chosen to optimize infrasound performance, and consequently span a dramatic range of land cover types, from temperate rain forest to exposed tundra. In this study, we compute power spectral densities for 2020 data and compile new ambient infrasound low- and high-noise models for the region. In addition, we compare time series of root-mean-squared (rms) amplitudes with wind data and high-resolution land cover data to derive noise–wind speed relationships for several land cover categories. We observe that noise levels for the network are dominated by wind, and that network noise is generally higher in the winter months when storms are more frequent and the microbarom is more pronounced. Wind direction also exerts control on noise levels, likely as a result of infrasound ports being systematically located on the east side of the station huts. We find that rms amplitudes correlate with site land cover type, and that knowledge of both land cover type and wind speed can help predict infrasound noise levels. Our results show that land cover data can be used to inform infrasound station site selection, and that wind–noise models that incorporate station land cover type are useful tools for understanding general station noise performance. 

ABSTRACT A typical seismic experiment involves installing 10–50 seismometers for 2–3 yr to record distant and local earthquakes, along with Earth’s ambient noise wavefield. The choice of the region is governed by scientific questions that may be addressed with newly recorded seismic data. In most experiments, not all stations record data for the full expected duration. Data loss may arise from defective equipment, improperly installed equipment, vandalism or theft, inadequate power sources, environmental disruptions (e.g., snow covering solar panels and causing power outage), and many other reasons. In remote regions of Alaska and northwestern Canada, bears are a particular threat to seismic stations. Here, we document three recent projects (Southern Alaska Lithosphere and Mantle Observation Network, Fault Locations and Alaska Tectonics from Seismicity, and Mackenzie Mountains EarthScope Project) in which bears were regular visitors to remote seismic stations. For these projects, there were documented bear encounters at 56 out of 88 remote stations and 6 out of 85 nonremote stations. Considering bear‐disrupted sites—such as dug‐up cables or outages—there were 29 cases at remote stations and one case at nonremote stations. We also compile bear encounters with permanent stations within the Alaska Seismic Network, as well as stations of the Alaska Transportable Array. For these two networks, the stations are designed with fiberglass huts that house and protect equipment. Data losses at these networks because of bears are minor (<5%), though evidence suggests they are regularly visited by bears, and data disruptions are exclusively at remote stations. The primary goal of this study is to formally document the impacts of bears on seismic stations in Alaska and northwestern Canada. We propose that the threat of damage from bears to a station increases with the remoteness of the site and the density of bears, and it decreases with the strength and security of materials used. We suggest that low‐power electric fences be considered for seismic stations—especially for temporary experiments—to protect the equipment and to protect the bears. With the goal of 100% data returns, future seismic experiments in remote regions of bear country should carefully consider the impacts of bears. 

Abstract The Mw 7.1 47 km deep earthquake that occurred on 30 November 2018 had deep societal impacts across southcentral Alaska and exhibited phenomena of broad scientific interest. We document observations that point to future directions of research and hazard mitigation. The rupture mechanism, aftershocks, and deformation of the mainshock are consistent with extension inside the Pacific plate near the down‐dip limit of flat‐slab subduction. Peak ground motions >25%g were observed across more than 8000  km2, though the most violent near‐fault shaking was avoided because the hypocenter was nearly 50 km below the surface. The ground motions show substantial variation, highlighting the influence of regional geology and near‐surface soil conditions. Aftershock activity was vigorous with roughly 300 felt events in the first six months, including two dozen aftershocks exceeding M 4.5. Broad subsidence of up to 5 cm across the region is consistent with the rupture mechanism. The passage of seismic waves and possibly the coseismic subsidence mobilized ground waters, resulting in temporary increases in stream flow. Although there were many failures of natural slopes and soils, the shaking was insufficient to reactivate many of the failures observed during the 1964 M 9.2 earthquake. This is explained by the much shorter duration of shaking as well as the lower amplitude long‐period motions in 2018. The majority of observed soil failures were in anthropogenically placed fill soils. Structural damage is attributed to both the failure of these emplaced soils as well as to the ground motion, which shows some spatial correlation to damage. However, the paucity of instrumental ground‐motion recordings outside of downtown Anchorage makes these comparisons challenging. The earthquake demonstrated the challenge of issuing tsunami warnings in complex coastal geographies and highlights the need for a targeted tsunami hazard evaluation of the region. The event also demonstrates the challenge of estimating the probabilistic hazard posed by intraslab earthquakes.