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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.