Usability of records by China earthquake early warning network for ground motion modeling

作者：Wencai Wang, Junju Xie, Xiaojun Li · 发表于：Soil Dynamics and Earthquake Engineering · 年份：2025 · DOI：10.1016/j.soildyn.2025.109497 · 被引用次数：5 · 研究领域：Seismology and Earthquake Studies、Seismic Waves and Analysis、earthquake and tectonic studies

Since 2020, the China Earthquake Early Warning Network (CEEWN) has acquired extensive strong motion data using dense arrays of microelectromechanical system (MEMS) sensors and force-balanced accelerographs (FBAs), offering new opportunities for near-fault motion studies and regional ground motion model (GMM) development. However, reliability concerns about low-cost MEMS sensors hinder their adoption. We evaluate CEEWN data quality through noise analysis, useable bandwidth assessment, and influencing factors. Analyzing 9007 three-component records from 11 M > 4 earthquakes (7 MEMS models, 6 FBA models), we compared instrument performance, installation methods, and distance effects. Both sensor types showed PGA-correlated bandwidth expansion, with FBAs achieving wider ranges (10 −4 –0.1 cm/s 2 noise levels reflecting ambient conditions). MEMS records displayed clustered noise distributions dominated by instrumental noise, enabling classification into two groups: low-noise instruments (0.04–0.06 cm/s 2 ) and high-noise instruments showing comparable noise levels to California's Community Seismic Network. Wall-mounted configurations increased average noise by factors of 1–1.5 relative to ground installations, though vertical component noise showed marginal reduction. We developed a four-tier classification system for MEMS records: Very Broadband (VBBR), Broadband (BBR), Narrowband (NBR), and Rejected (REJ), with corresponding PGA thresholds for category differentiation. Magnitude...