Geosystemic signatures of the seismic preparatory phase: Insights from the 2024 Wushi and 2025 Myanmar Earthquakes

Large recent earthquakes offer an opportunity to investigate the seismic preparatory phase from a geosystemic, multiparametric perspective, integrating lithospheric, atmospheric and ionospheric observations within the Dobrovolsky region. Using the Mw 7.1 Wushi (Xinjiang, 22 January 2024) and Mw 7.7 Myanmar (Sagaing Fault, 28 March 2025) earthquakes as natural laboratories, we jointly analyze medium‑term lithospheric signals (multi‑year) and short‑term atmospheric/ionospheric anomalies (days to months before the mainshocks). In the Wushi case, about 60 anomalies are detected: lithospheric changes persist for about one year, whereas atmospheric and ionospheric perturbations cluster within the last three months, including outgoing longwave radiation anomalies from four days before to four days after the mainshock, consistent with imminent‑stage precursors. For the Myanmar event, eleven classes of candidate precursors exhibit a characteristic sigmoid evolution in time, typical of a critical system approaching failure, and their space–time concentration supports the lithosphere–atmosphere–ionosphere coupling (LAIC) framework. A focused analysis of Swarm satellite magnetic data over the Myanmar Dobrovolsky area reveals Y‑component anomalies on 22 of 85 half‑orbits up to eight days before the earthquake; empirical magnitude estimates based on anomaly–epicentre distance yield M ≈ 7.2, in reasonable agreement with the observed M 7.7, while anomaly “energy” values cluster within a narrow range, suggesting a possible characteristic signature of seismic‑related disturbances. Overall, these case studies indicate that (i) multi‑scale, multi‑parameter anomalies often accelerate following exponential or sigmoid trends towards the mainshock, (ii) combined ground‑ and satellite‑based observations can help constrain the location of an impending event, and (iii) satellite magnetic and radiative anomalies may provide valuable input for short‑term forecasting schemes, although systematic validation on larger datasets is required before operational use.

The present work has been funded by the Italian Ministry of University and Research (Pianeta Dinamico - Unitary Project) and ASI (Space It Up and LIMADOU EXPO Projects).