Association of land surface temperature anomalies from GOES/ABI, MSG/SEVIRI, and Himawari-8/AHI with land earthquakes between 2010 and 2021

Abstract

AbstractEvery year, earthquakes cause numerous casualties and billions of dollars in economic damages, and so far, it is impossible to predict them. Many researchers have studied the land surface temperature (LST) anomalies as promising potential earthquake precursors. In this work, more than 30,000 land earthquakes with a Magnitude (Mw) larger than 4 have been studied from 2010 to 2021. Global LST nighttime (0–6 am) data from Meteosat Second Generation (MSG), Himawari-8, and the Geostationary Operational Environmental Satellite (GOES) satellites have been used to evaluate the LST anomalies in the zones affected by earthquakes with spatial resolutions of 1, 2, and 4 km, respectively. The time series moving standard deviation (STD) and Interquartile (IQT) have been used to estimate the LST anomalies. The Confusion Matrix (CM), the receiver operating curve (ROC), and some other figures of merit are computed to assess the goodness of positive LST anomalies and detection thresholds as potential proxies of earthquake occurrence. A positive LST anomaly is typically observed a few days [1–7 d] before the earthquake’s occurrence, followed by a negative LST anomaly afterwards [1–3 d].

Keywords

• Big data analytics
• correlation study
• earthquake precursors
• LST anomalies