USGS · 70031604
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R. Bilham, S. Lodi, S. Hough, S. Bukhary, A.M. Khan, S.F.A. Rafeeqi. 2007. Seismic hazard in Karachi, Pakistan: Uncertain past, uncertain future. https://doi.org/10.1785/gssrl.78.6.601
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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
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.
Earth’s microseism wavefield dominates seismic background levels at periods between approximately 4 and 20 s, and reflects periodic and secular variations in ocean swell energy. Ocean wave energy couples to the seismic wavefield via distinct primary microseism and secondary microseism (PM and SM) source mechanisms, which are excited by basal swell tractions and seafloor pressure variations due to crossing seas, respectively. This study examines annual amplitude variations for the globally dominant PM (14–20 s) and SM (4–10 s) period bands. Annual harmonic variations are represented by four‐term Fourier series fits to vertical‐component seasonally smoothed acceleration time series from 73 stations in the Global Seismographic and GEOSCOPE networks with over 20 yr of recording and at least 75% data completeness. These annual periodic functions fit between 14%–95% (PM) and 22%–97% (SM) of signal variance. Station annual peak‐to‐peak variations range between 1.2–14.3 dB (PM) and 1.5–20.6 dB (SM). An asymmetry in microseism features exists between the Northern (NH) and Southern (SH) Hemispheres. High‐latitude NH stations show highly correlated PM and SM annual amplitude variations. This character dominates the wider extratropical NH but diminishes at tropical latitudes, and widespread relative PM–SM decorrelation is observed in the SH. These hemispheric characteristics reflect systematic differences in both extratropical storm activity and ocean wave state. Greater annual variation and seasonal predictability in the NH reflect the influence of the large continental landmasses that enhance both storm intensity seasonality and SM‐generating coastal wave reflection. Notable clusters of low PM–SM correlation stations are also observed in continental Antarctica due to seasonal sea ice influences, and in East Asia, reflecting unusual PM and SM source responses to South Asian monsoonal and tropical cyclone ocean wave influences.