Azimuthal Dependence in Empirical Seismic Station Detection Threshold Models | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Azimuthal Dependence in Empirical Seismic Station Detection Threshold Models Dorian Golriz, David M. Steinberg, Yochai Ben-Horin, Yael Radzyner This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9534277/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Empirical models used to estimate seismic station detection thresholds commonly assume azimuthal symmetry by relying only on event magnitude and source–station distance. This simplification neglects directional variability arising from source radiation and propagation-path heterogeneity. We quantify the impact of including azimuth in empirical station-specific detection probability models using approximately two decades of International Monitoring System (IMS) seismic observations from 17 three-component primary stations. Station-level detection is defined using time-defining phases in the IDC Late Event Bulletin (LEB) under verified waveform availability conditions. For each station, Random Forest classifiers are trained to estimate the detection probability using (i) magnitude and distance and (ii) magnitude, distance, and azimuth. Detection thresholds are defined as the minimum magnitude at which estimated probability exceeds 75% within cells containing sufficient observations. Including azimuth systematically modifies empirical magnitude thresholds and reduces optimistic bias inherent in distance-only models. In some directions, threshold differences approach one magnitude unit. These results demonstrate that azimuthal variability is operationally relevant for station performance assessment and should be considered in empirical monitoring frameworks supporting CTBT verification. Seismic detectability Azimuthal variability International Monitoring System Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 09 May, 2026 Reviews received at journal 06 May, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers invited by journal 28 Apr, 2026 Editor assigned by journal 28 Apr, 2026 Submission checks completed at journal 28 Apr, 2026 First submitted to journal 26 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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