(1) Continued Operations of the U.S. Geological Survey Component of the Global Seismographic Network

The GSN is a permanent digital network of state-of-the art seismological and geophysical sensors connected by a telecommunications network. It serves as a multiuse scientific facility and societal resource for monitoring, research, and education. Per byte, the GSN comprises some of the most highly requested seismic stations in the world (fig. 8A–C). The GSN is used as a resource because of the wide frequency band that allows GSN stations to characterize high-frequency local seismicity and very low-frequency signals such as the background hum of the Earth or the deformation of the Earth from the gravitational attraction of the Moon and the Sun (fig. 9). Along with the high-quality data of the GSN’s stations, many are sited in extremely remote locations where very few other seismic stations operate. These stations, with their focus on low-latency, high data quality and global coverage, are used by the NEIC and other stakeholders (for example, the NOAA Tsunami Warning Centers) to carry out their mission.

Much of the technology developed for the GSN is adopted later by other networks (for example, data format and telemetry and installation methods). This means that other networks often adopt technological advances after they have been vetted at GSN stations. Therefore, continuing to investigate ways to improve data quality and station infrastructure at GSN sites, with the goal of implementing these new technologies in national and regional networks, could improve USGS seismic data.

(2) Global Seismographic Network Deferred Maintenance

Modernizing the GSN could allow it to continue to provide state-of-the-art, high-quality geophysical data. This could consist of modernizing the sensors that have not yet been upgraded in the existing borehole upgrade project. Future deferred maintenance could also comprise upgrading the GSN digitizers, including identifying, testing, and integrating a new digitizer into the GSN. These maintenance components are part of the requirements for continued operation of the GSN.

(3) Provide High-Quality, Near Real-Time Data in Support of the Advanced National Seismic System

The backbone stations of the ANSS and the N4 network provide a network of reference stations and coverage in regions where there are no dedicated ANSS regional networks. These stations need to be calibrated and oriented to ensure that they provide a solid reference so other regional networks can compare nearby station quality. These stations are used for NEIC monitoring in the United States, where the ANSS is required to detect and characterize all seismicity of magnitude (M_w) 2.5 and greater in the Central and Eastern United States, and M_w 3.0 and larger in the Western United States, Alaska, Hawaii, and United States Territories. The low noise and high quality of these stations also allow for the testing and development of new methods for characterizing seismicity at regional scales (fig. 7A–B). The continued long-term maintenance of these stations helps to ensure that the Nation has a level of monitoring capability even if a regional seismic network experiences a temporary outage.

(4) Continued Support of Instrumentation for Regional Networks Through the Advanced National Seismic System Equipment Depot

The ANSS Depot is housed at the ASL. It provides tested equipment for the ANSS regional seismic networks and allows for the exchange of instruments that no longer provide quality data because of failures. By having one location to support these regional seismic networks, the USGS can standardize equipment and provide replacements quickly. The testing facilities at ASL make it possible to efficiently test all equipment before it is shipped. This helps to ensure that equipment failures are not caused by vendors sending compromised instrumentation.

(5) Instrumentation Testing for Improvements in U.S. Geological Survey Operations

The ASL facilities for instrumentation testing and development have historically been considered to be among the gold-standard facilities in the world (Moore and others, 2019; fig. 5 and 6). To support the needs of the GSN and regional and national networks, the ASL can continue instrumentation testing. The ASL facilities include two quiet vaults, more than 20 boreholes of various depths, several reference sensors, an array of broadband stations (Anthony and others, 2020), and shake tables that can characterize horizontal, vertical, and rotational motions. These facilities are used to support the GSN Program and the EHP, and they also provide facilities and staff that can test and develop instrumentation in support of the broader USGS NHMA. For example, the ASL has tested and developed instrumentation for the Landslide Hazards Program (LHP) and the VHP. Through procurement testing, the ASL can vet the seismic equipment on its equipment contracts for use by the entire NHMA.

Moreover, the ASL is also able to test and characterize emerging technologies that could be of future interest to the USGS. For example, rotational instruments and distributed acoustic sensing instrumentation and configuration have been examined at the ASL. The low-noise environment at the ASL can be well-suited for these efforts.

(6) Continued Support for and Modernization of Aftershock Systems

The ASL maintains seismic equipment for deployment during major earthquake aftershock sequences. Each of the aftershock kits maintained by ASL has a broadband sensor, a strong-motion accelerometer, and equipment to provide real-time telemetry. By rapidly deploying temporary stations after earthquakes and other seismic activity, the ASL can provide near-field data with low latency. This benefits the NEIC in characterizing locations and magnitudes and can also benefit the greater scientific community (for example, McNamara and others, 2013; Boyd and others, 2024). As ASL aftershock data are telemetered in real time and made publicly available by EarthScope, these aftershock deployments provide the community with additional data feeds and station coverage. The aftershock stations installed by ASL are used for improving USGS aftershock forecasting products (fig. 10A–B). The continual modernization of instruments, recording equipment, and telemetry equipment helps to ensure that these systems can provide high-quality data and be deployed quickly. The ASL could consider ways to more quickly transport and install aftershock stations to the area of the deployment.

(7) Data Quality Innovation for Improvements in Network Operations for Government and University Stakeholders

The ability for the USGS and outside stakeholders to utilize data from the seismic networks operated by the ASL is limited by the quality of the data. For example, scatter in earthquake magnitude estimates is often a result of station noise and local site effects. Such noise limitations are not specific to earthquake magnitudes but are pervasive in many areas of observational seismology. Along with improving data quality by understanding local site effects, the characterization of the stations by metadata (for example, sensitivity, timing, and orientation) is also used. The GSN provides many of the stations used in understanding Earth’s inner core rotation because of the long deployment history and geographic locations of these stations. Scientists are making ever-increasing requests for GSN data (for example, seeking timing accuracy to less than a millisecond). To address these requests, the ASL has developed in situ metrics to quantify the quality of a station. These metrics help the ASL identify stations with subtle but problematic issues that can eventually compromise the quality of ASL-operated stations. For this information to be available to quality control analysts, the metrics are collected in the data quality analyzer (DQA; Ringler and others, 2015). For example, analysts can look at changes in noise levels during many years or identify potential misorientations by using metrics that compare the strong-motion accelerometer to the broadband sensor at a station (fig. 11A–F). The ASL continues to produce low-frequency synthetic seismograms and three-dimensional synthetic seismograms after magnitude 6.5 and greater occurrences. By doing data-to-synthetic comparisons (fig. 11A) for the entire frequency content of the synthetics (approximately 40 seconds [s] to 1000 s), frequency-dependent problems at a station can be identified (for example, changes in the amplitude response of the instrument).

(8) Support Education, Workforce, and Research Development in Seismology and Instrumentation

Producing high-quality, real-time data allows ASL to provide accurate data for the EHP and outside stakeholders. For USGS data to continue to provide innovations and improvements in science with the long-term goal of mitigating loss of life and property, new processing techniques and algorithms could be developed. Many new methods are first developed in an academic setting and later adapted for operational needs in the USGS. For example, the W-phase moment tensor solutions—a rapid and accurate measurement of earthquake size and fault mechanism that has been used by the USGS NEIC and the NOAA Tsunami Warning Center missions—make optimal use of the low-frequency, high-quality data provided by GSN stations. For these products to be developed, researchers evaluate the limitations of their data and understand some of their unexploited uses.

Through community support for educating scientists about details like the timing quality at seismic stations or the accuracy and precision of the signals being recorded, researchers can better develop new approaches to data processing (for example, Ringler and Evans, 2015; Ringler and others, 2023). As the ASL straddles the instrumentation of observational seismology and data quality, the ASL can identify and communicate to the community different uses of observational seismology and potential limitations in the data in addition to technological advances that could help circumvent these limitations.

Continuing the following foundational priorities may help ASL continue to provide exceptional service.

(1) Expand Albuquerque Seismological Laboratory Networks to Provide Multiple Geophysical Observations

As many areas of observational seismology are making use of nonseismic data streams (for example, temperature, magnetic field measurements, and pressure), ASL-operated stations can be used to provide these colocated geophysical measurements. For example, colocated pressure observations during the Hunga Tonga volcanic eruption (fig. 12) led to improvements in our understanding of large volcanic eruptions (Matoza and others, 2022). By understanding interactions between the atmosphere and solid Earth, it may be possible to identify and mitigate losses from rare but extreme geological hazards.

Often these colocated geophysical measurements can be recorded on already open digitizer channels and low-cost sensors. For example, the addition of low-cost magnetometers allows for improvements in spatial resolution to monitor space weather occurrences that could compromise the power grid. As resources allow, the ASL could expand its ability to provide additional, nonseismic data at ASL stations. Although this is often done at existing GSN stations, efforts could be considered to continue expanding these additional data channels to other ASL-operated stations, such as stations in the United States and N4 networks. Working with colleagues in the USGS Geomagnetism Program and VHP may help the USGS to prioritize key locations where additional, nonseismic sensors might be advantageous.

(2) Targeted Improvement of Remote Stations to Improve Coverage and Data Quality of the Global Seismographic Network

The GSN provides data from some of the remotest stations in the world (fig. 3). Although these stations are used by the NEIC and stakeholders that require global coverage, they pose operational and data-quality challenges. For example, many of these remote stations are on island sites that have high noise levels, and station outages can be lengthy because of lead times in getting to these stations for repairs and telemetry issues.

The ASL could look at methods to improve coverage and data quality at these remote sites and consider moving problematic sites without losing coverage. This could come from improved infrastructure with backup telemetry and power and additional onsite sensors. For example, a local array could provide redundant sensors at these remote sites, and noise levels could be mitigated using array techniques. In contrast, low-footprint sites with robust communication could provide moderate-quality data in remote locations that would be less likely to be compromised because of vandalism.

(3) Improve Testing Capabilities for Nonseismic Geophysical Instruments

With the integration of nonseismic sensors into seismic networks, data quality is considered for these types of sensors (for example, magnetometers, barometric pressure, and weather stations) and the best practices for installing them and verifying their associated metadata. ASL testing of these types of sensors is mostly functional and done to identify the basic quality of their data. As such, the accuracy and precision of these sensors aren’t quantified, and more refined quality control methods could be necessary.

As the USGS and outside stakeholders make ever-increasing requests for data produced by the GSN and the ANSS, the quality of the nonseismic geophysical instruments could be evaluated and improved. This may require calibrating laboratory reference sensors and developing methods for characterizing the sensors when deployed. For example, by improving magnetometer calibrations, it may be possible to quantify magnetic field data produced at ASL stations that are used by the Geomagnetism Program. This type of calibration and quality control could allow outside stakeholders to have confidence in these data for nonseismic applications (for example, space weather monitoring).

(4) Improve Detection Threshold Monitoring and Quality Control in Near Real Time

The ASL has developed capabilities to quantify network thresholds for detections and magnitude estimates (Wilson and others, 2022; Ringler and others, 2024). These methods enable us to understand how additional stations can improve monitoring efforts. Current (2025) methods require already having knowledge of the background noise levels at the station, which can make it difficult to understand improvements in network thresholds in near real time. For example, when new stations go online during aftershock deployments, it is not possible to quantify the improvement in detection capabilities until a few days of background data have been recorded. This is further complicated when installing stations in active regions where aftershocks are frequent and possibly skewing the background noise statistics. Previous studies have also been limited by only considering specific types of magnitudes (for example, Wilson and others, 2022; Ringler and others, 2024).

By utilizing more sophisticated real-time background noise estimation techniques, it could be possible to understand changes in network thresholds in near real time, allowing scientists to identify when monitoring efforts could become compromised because of various changes in station status (for example, regional outages, elevated noise from human-made sources). Near real-time network threshold quantification would have the additional advantage of helping in the decision-making process during aftershock deployments. For example, it could be possible to look at the improvements in detection thresholds after each station is added to the network. This could also help to identify station locations that might be ideal for various USGS real-time products (for example, improved azimuth coverage or depth constraints).

(5) Expand Data Quality Analysis to All Channels Used by the National Earthquake Information Center

The NEIC utilizes approximately 1,500 real-time broadband seismic stations operated by universities and other countries (fig. 5). By utilizing many diverse stations, the NEIC can ensure that it can meet its hazard monitoring missions. Not all seismic stations produce data that meet standard quality levels. This can be due to flawed metadata, elevated noise levels, or other station issues that compromise the quality of the data being used by the NEIC.

Utilizing the DQA to provide in situ measurements of the data quality for stations used by the NEIC could allow the NEIC to provide near real-time updates of stations that might compromise USGS products produced by the NEIC (fig. 11). This large-scale data quality analysis could also help the USGS communicate these problems to network operators that might be otherwise unaware of the compromised data quality because their network focuses on other applications, or they do not have the resources to do robust data quality control.

(6) Improve Rapid Aftershock Deployments

The ASL aftershock equipment pool contains about 30 kits that have a broadband and strong-motion accelerometer along with telemetry equipment to provide low-latency real-time data. Future aftershock deployments could make use of new instrumentation or approaches. For example, improving station coverage by deploying many low-cost midband instruments that improve azimuthal coverage and speed up the deployment of aftershock kits has been considered at the possible cost of station noise levels. This is only one possible scenario, as utilizing quickly deployed arrays of sensors could provide improved benefits for aftershock monitoring using array processing techniques.

Along with considering different deployment strategies, developing tools and techniques can help quantify the quality of our aftershock systems and how they improve upon existing stations in the area. For example, aftershock deployments in regions with high background noise levels might benefit from broadband stations farther away. Alternatively, placing stations directly above a fault could result in improved estimates of the depth of earthquakes in a sequence.

Regardless of the scientific focus of the study, being able to quantify and identify the optimal deployment strategies could help improve data quality and reduce costs in labor and equipment by having more targeted deployment strategies. Using previously deployed aftershock kits, along with theoretical modeling, could help in identifying metrics for quantifying aftershock station data quality, which could also help us quantify the quality of aftershock deployments as well as guide future deployments. The following are aspirational tasks.