USGS Science⌕ Search

USGS · 70125640

Seismic Station Installation Orientation Errors at ANSS and IRIS/USGS Stations

Abstract

Many seismological studies depend on the published orientations of sensitive axes of seismic instruments relative to north (e.g., Li et al., 2011). For example, studies of the anisotropic structure of the Earth’s mantle through SKS‐splitting measurements (Long et al., 2009), constraints on core–mantle electromagnetic coupling from torsional normal‐mode measurements (Dumberry and Mound, 2008), and models of three‐dimensional (3D) velocity variations from surface waves (Ekström et al., 1997) rely on accurate sensor orientation. Unfortunately, numerous results indicate that this critical parameter is often subject to significant error (Laske, 1995; Laske and Masters, 1996; Yoshizawa et al., 1999; Schulte‐Pelkum et al., 2001; Larson and Ekström, 2002). For the Advanced National Seismic System (ANSS; ANSS Technical Integration Committee, 2002), the Global Seismographic Network (GSN; Butler et al., 2004), and many other networks, sensor orientation is typically determined by a field engineer during installation. Successful emplacement of a seismic instrument requires identifying true north, transferring a reference line, and measuring the orientation of the instrument relative to the reference line. Such an exercise is simple in theory, but there are many complications in practice. There are four commonly used methods for determining true north at the ANSS and GSN stations operated by the USGS Albuquerque Seismological Laboratory (ASL), including gyroscopic, astronomical, Global Positioning System (GPS), and magnetic field techniques. A particular method is selected based on site conditions (above ground, below ground, availability of astronomical observations, and so on) and in the case of gyroscopic methods, export restrictions. Once a north line has been determined, it must be translated to the sensor location. For installations in mines or deep vaults, this step can include tracking angles through the one or more turns in the access tunnel leading to the vault (e.g., GSN station WCI in Wyandotte Cave, Indiana). Finally, the third source of error comes from the ability of field engineers to orient the sensor relative to the reference line. In order to quantify bounds on the errors in each step in the orientation process, we conducted a series of tests at the ASL using twelve GSN and ANSS field engineers. The results from this exercise allow us to estimate upper bounds on the precision of our ability to orient instruments, as well as identify the sources of error in the procedures. We are also able to identify systematic bias of various true‐north‐finding methods relative to one another. Although we are unable to estimate the absolute accuracy of our orientation measurements due to our inability to identify true north without some error, the agreement between independent methods for finding true north provides confidence in the different approaches, assuming no systematic bias. Finally, our study neglects orientation errors that are beyond the control of the field engineer during a station visit. These additional errors can arise from deviations in the sensitive axes of the instruments relative to the case markings, processing errors (Holcomb, 2002) when comparing horizontal orientations relative to other sensors (e.g., borehole installations), and deviations of the sensitive axes of instruments from true orthogonality (e.g., instruments with separate modules such as the Streckeisen STS‐1).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Adam T. Ringler, Charles R. Hutt, K. Persfield, Lind S. Gee. 2013-10-24. Seismic Station Installation Orientation Errors at ANSS and IRIS/USGS Stations. https://doi.org/10.1785/0220130072

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Time for an updated macroseismic scale

Macroseismology plays a crucial role in earthquake hazard and risk analyses, linking past earthquake occurrences and impacts with those of the present and future. The popularity of internet-based community contributions and the usefulness of intensities for communicating seismic hazards, early warning, and impacts to the public have all bolstered the use of macroseismology beyond its traditional utility in characterizing sources and shaking from historical and modern earthquakes (Wald et al., 2023). Nevertheless, many modern approaches for collecting building damage data and assigning macroseismic intensities suffer limitations. Many countries do not or no longer routinely collect such data, and even after significant and even catastrophic earthquakes, building damage data are often not collected or shared systematically, nor are field-based macroseismic intensities professionally assigned. Additionally, the United States (U.S.), Canada, and other nations still use variations of the Modified Mercalli Intensity (MMI) scale (Wood and Neumann, 1931) for assigning macroseismic intensities. At nearly 100 years old, the MMI scale predates most modern building types. As a result, the scale is silent about and blind to building damage that now matters to most domestic occupants. It says nothing about single- or multi-unit wood-frame buildings, the predominant type of residential structure in the US and Canada, whose damage is a particularly important indicator of shaking intensity, nor about the collapse or safety of modern building types. Importantly, the dependence on the U.S. Geological Survey’s “Did You Feel It?” (DYFI) for domestic intensity data collection limits their accuracy type at higher, damaging intensity levels, where attention to building type is requisite. The MMI and some of its widely used variants are often poorly documented; there is no official version, nor is it even clear which version of the scale was employed in many studies (Musson, 2002). The MMI scale is consistent with—but is more limited than—the 1998 European Macroseismic Scale (EMS-98, Grünthal, 1998). The new International Macroseismic Scale of 2025 (IMS-25; Grünthal et al., 2025) builds on EMS-98—a well-documented, modern scale already widely used in Europe and well beyond. IMS-25 further expands EMS-98 internationally by enhancing the EMS-98 vulnerability table and damage grade collections to include more worldwide building types and their evolving design codes. Because the IMS requires well-defined vulnerability classes and damage grades specific to various structural types, its worldwide adoption will help unify post-event data collection on building damage. Similarly, the IMS requires statistical analyses of damage levels for specific structural types, ensuring that building damage sampling is sufficient for other important engineering analyses, such as the derivation of fragility functions, calibration of loss models, and the assessment of losses and damages after significant events

Seismological Research Letters↗

Intensity prediction equations for intraslab earthquakes in the Cascadia Subduction Zone

In the U.S. Pacific Northwest (PNW), intraslab earthquakes located within the subducting Juan de Fuca slab are responsible for most of the region’s moderate‐magnitude seismicity. Historically, these earthquakes have caused significant damage, such as the 2001 M 6.8 Nisqually, 1965 M 6.5 Seattle, and 1949 M 6.8 Olympia events. Intensity prediction equations (IPEs) aim to relate source‐to‐site distance and earthquake magnitude to the resultant felt shaking intensity at a particular location, and help to estimate hazard from earthquakes. We find that a commonly used IPE developed by Atkinson et al. (2014) does not accurately describe shaking intensity from most intraslab events in the PNW, likely because it was developed using primarily crustal fault earthquakes. In this study, we develop two new IPEs that provide an improved fit to observed intensities from Cascadia subduction zone intraslab earthquakes. To develop our IPEs, we compute linear mixed‐effects regressions using community decimal intensity data from the U.S. Geological Survey’s ‘Did You Feel It?’ program from 36 intraslab events that occurred in British Columbia, Canada, Washington, Oregon, and northern California from 2000 to 2025. We also investigate the relationship between the new intraslab IPEs and select parameters related to near‐surface conditions and deeper geologic structure that may be related to ground‐motion intensities, but find no correlations. These new IPEs provide a better fit to observations of intraslab earthquakes in the PNW than Atkinson et al. (2014) , particularly within 300 km of the epicenter. They also provide a better fit to the 2018 M 7.1 Anchorage, Alaska, intraslab earthquake, suggesting that they may have broader applicability to global subduction zones.

California, Oregon, Washington↗

Amploc: A complete Python workflow for amplitude-based locations

Amplitude‐based locations are well suited for characterizing long‐duration seismic sources that may migrate with time, such as debris flows, avalanches, rockfall, and volcanic tremor. Although amplitude‐based location methods have existed for decades, their adoption in real‐time monitoring systems remains limited. We present a complete Python‐based workflow that includes station corrections, amplitude‐based location algorithms, and interactive review tools that are appropriate for real‐time use. The algorithms themselves are not new; however, Amploc integrates several previously published methods into a unified operational framework. The workflow also introduces a browser‐based graphical interface that allows users to review real‐time location results using formats familiar to many observatories. By integrating calibration, location algorithms, and visualization tools, Amploc lowers the barrier to operational use of amplitude‐based locations and improves characterization of phenomena that inform hazard assessments such as long‐period earthquakes, volcanic tremor, and debris flows.

British Columbia, Oregon, Washington↗