Pre-Seismic Temporal Integrated Anomalies from Multiparametric Remote Sensing Data

Pre-seismic anomalies have the potential to indicate imminent strong earthquakes in short medium terms. However, an improved understanding of statistical significance between and is required develop operational forecasting systems. We developed a temporal integrated anomaly (TIA) method obtain trends multiparametric derived from Atmospheric Infrared Sounder (AIRS) product before earthquakes. A total 169 global that occurred 2006 2020 had magnitudes ?7.0 focal depths ?70 km were used test this new retrospective manner. In addition, synthetic randomly generated demonstrate suppression capacity TIA for false alarms. identified four different according characteristics positive negative TIAs. Long-term correlation analyses show recognition ability was 12.4–28.4% higher true than (i.e., random guess). Incorporating 2–5 kinds TIAs offered best chance recognizing shocks, highlighting importance multiparameter anomalies. Although trend not unique, we certain unexplained pre-seismic phenomena within remote sensing data. The results provide insight into relationships earthquakes; moreover, proposed approach exceeds guessing.