Ma, YimingAnastasiou, AndreasMontiel, Fabien2026-05-282026-05-282025-12-13Geophysical Journal International, ISSN: 0956-540X (Print); 1365-246X (Online), Oxford University Press (OUP), 244(3), ggaf517-. doi: 10.1093/gji/ggaf5170956-540X1365-246Xhttp://hdl.handle.net/10292/21284Inferring from the occurrence pattern of slow slip events (SSEs) the probability of triggering a damaging earthquake within the nearby velocity weakening portion of the plate interface is critical for hazard mitigation. Although robust methods exist to detect long-term SSEs consistently and efficiently, detecting short-term SSEs remains a challenge. In this study, we propose a novel statistical approach, called singular spectrum analysis isolate-detect (SSAID), for automatically estimating the start and end times of short-term SSEs in GNSS data. The method recasts the problem of detecting SSEs as that of identifying change-points in a piecewise non-linear signal. This is achieved by obscuring the deviation from piecewise-linearity in the underlying SSE signals using added noise. We verify its effectiveness on a range of synthetic SSE data with different noise levels, and demonstrate its superior performance compared to two existing methods. We illustrate its capability in detecting short-term SSEs in observed GNSS data from 36 stations in southwest Japan via the co-occurrence of non-volcanic tremors, hypothesis tests and fault estimation.© The Author(s) 2025. Published by Oxford University Press on behalf of The Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.https://creativecommons.org/licenses/by/4.0/37 Earth Sciences40 Engineering3706 Geophysics0403 Geology0404 Geophysics0909 Geomatic EngineeringGeochemistry & Geophysics3705 Geology4013 Geomatic engineeringSatellite geodesyTransient deformationTime-series analysisEarthquake ground motionsEpisodic tremor and slipJournal ArticleOpenAccess10.1093/gji/ggaf517