Multi-parameter GNSS analysis reveals atmospheric, ionospheric and crustal precursors seven days before the 2016 Mw 7.8 Ecuador megathrust earthquake

Abstract

In this study, the atmospheric, ionospheric and crustal precursors of the Mw 7.8 Ecuador megathrust earthquake of April 16, 2016 is examined using comprehensive multiparameter GNSS analysis. Seven consecutive days of 30-second interval data from IGS stations ESMR and QUI3 (25–200 km from epicenter) are processed using CSRS-PPP software. Our analysis encompasses coordinate differences, receiver clock offsets, tropospheric parameters and co-seismic characteristics with rigorous statistical validation through Z-score analysis and Mann-Whitney U hypothesis testing. Results reveal systematic precursor signals with distinct temporal progression: clock offset anomalies emerge first (April 13), followed by coordinate variations (April 14–15) and tropospheric changes (April 15–16). QUI3 station demonstrates progressive anomaly intensification with Z-scores increasing from 2.449 to 5.634 over four consecutive days, while ESMR exhibits contrasting patterns reflecting different positioning relative to the earthquake preparation zone. Statistical analysis confirms significant anomalies across all parameters (p < 0.001) with detection rates of 2.57–4.48% (± 2σ), substantially exceeding random variation expectations. In this study, a primary precursor window of 2–3 days for this megathrust earthquake is identified, contrasting with the longer periods reported for moderate-magnitude continental events. This reflects rapid stress accumulation and strong interplate coupling in subduction environments. External factor validation confirms observations occurred during geomagnetically quiet conditions, eliminating space weather artifacts. Multi-parameter correlation analysis (r = 0.620) demonstrates effectiveness of integrated GNSS monitoring for earthquake precursor detection, providing methodological frameworks applicable to early warning system development in seismically active subduction zones.