Enhancing earthquake magnitude determination: leveraging cumulative absolute absement for early warning systems using low-cost sensors

Abstract Background The reliable earthquake magnitude estimation is a critical component of earthquake early warning (EEW) systems. Conventional P-wave–based amplitude parameters, such as peak vertical displacement ( P d ), are widely used but often suffer from saturation and instability, particularly for larger earthquakes and when low-cost MEMS sensors are employed. The cumulative absolute absement (CAA), a time-integrated displacement parameter, has recently emerged as a promising alternative for improving early magnitude estimation. Methods This study analyzes strong-motion records from the dense P-Alert low-cost MEMS sensor network in Taiwan to evaluate the performance of CAA for earthquake magnitude estimation. CAA values were computed using P-wave windows ranging from 1 to 5 s after P-wave arrival, using stations within a hypocentral distance of 70 km as well as the nearest six stations. Empirical regression relations were developed to estimate magnitude from CAA and P d , and the resulting magnitudes were compared with the catalog moment magnitude ( M w ). A generalized moment magnitude ( M wg ) was additionally used to assess magnitude-scale consistency and bias in small to moderate earthquakes. Results The standard deviation between CAA-derived magnitude ( M caa ) and M w decreases systematically with increasing window length, from ±0.383 for a 3 s window to ±0.333 for a 5 s window when using all stations within 70 km. In contrast, P d -derived magnitudes ( M pd ) show larger deviations, reducing from ±0.504 (3 s) to ±0.398 (5 s). Reliable magnitude estimates are also achieved using only the nearest six stations, with standard deviations of ±0.341 (CAA) and ±0.460 ( P d ) for the 5 s window. CAA exhibits a stable scaling with earthquake magnitude, while P d tends to stagnate and underestimate events approaching M w 7.0. Magnitude scale consistency tests using M wg confirm the robustness of the proposed CAA relations after correcting for M w bias. Conclusions The results demonstrate that CAA provides a more stable and reliable early magnitude estimator than P d , particularly for low-cost MEMS sensor networks and limited station availability. The reduced dispersion, lower saturation tendency, and robustness across different window lengths highlight the strong potential of CAA for operational on-site EEW systems using dense, cost-effective seismic networks.