Multi-scale GNSS-TEC and GIM investigation of ionospheric perturbations triggered by the 28 March 2025 Myanmar earthquake preceded by geomagnetic storm

Abstract

This study investigates variability in ionospheric Total Electron Content (TEC) associated with the 28 March 2025 moment magnitude <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"> <mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>w</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> 7.7 Sagaing (Myanmar) earthquake within the low-latitude environment of Southeast Asia. A primary challenge in this region is identifying seismogenic perturbations during the residual recovery phase of two successive geomagnetic storms (25–26 March), which produced large-scale TEC fluctuations of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"> <mml:mrow> <mml:mo>±</mml:mo> <mml:mn>35</mml:mn> </mml:mrow> </mml:math> TEC units (TECU). To isolate potential seismic signatures, we implemented a multi-scale “Filter-to-Focus” framework. This approach uses regional Center for Orbit Determination in Europe (CODE) Global Ionospheric Maps (GIMs) as a spatial filter to separate broad storm-driven trends from localized lithospheric forcing. Subsequently, localized Global Navigation Satellite System (GNSS) TEC time series from station CMUM (located 390 km from the epicenter) were analyzed to provide high-resolution spectral focus. Statistical rigor was established using a non-parametric <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m3"> <mml:mrow> <mml:mn>1.5</mml:mn> <mml:mo>×</mml:mo> </mml:mrow> </mml:math> interquartile range (IQR) threshold combined with control-day validation, confirming that differential TEC (dTEC) remained within stable limits prior to the seismic event. Despite the dominant storm-time background, distinct localized perturbations were detected. These included an observed pre-event enhancement of +3.2 TECU 8–12 h prior to the mainshock—though definitively isolating this from late-stage storm dynamics remains complex—and significant coseismic enhancements of 15–25 TECU occurring approximately 18 min after rupture. Continuous Wavelet Transform (CWT) analysis confirmed that these coseismic perturbations exhibited wave-like oscillations within the 10–25 min period range ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m4"> <mml:mrow> <mml:mo>∼</mml:mo> </mml:mrow> </mml:math> 0.7–1.7 mHz), consistent with the internal gravity wave component of the acoustic-gravity wave (AGW) spectrum. Importantly, the CWT distinguished these specific seismogenic signatures from the broader, lower-frequency fluctuations typical of the geomagnetic recovery phase. These results demonstrate that seismogenic signals can be retrieved from geophysically noisy environments using combined spatial and frequency-domain filtering. This study provides a robust methodology for investigating lithosphere–atmosphere–ionosphere (LAI) coupling, offering a significant refinement for anomaly detection within the highly dynamic crest of the Equatorial Ionization Anomaly (EIA).