Earthquake Spatio-Temporal Patterns Around Precursory Thermal Infrared (TIR) Anomalies

Hui Lin, Ying Zhang, Jizhe Zhou, Xuejiao Wang, Hao Jin, Congcong Wen

Abstract: In this work, we analyze outgoing longwave radiation (OLR) data from the National Oceanic and Atmospheric Administration (NOAA) to extract thermal infrared (TIR) anomalies over mainland China from 2007 to 2019. These anomalies are statistically significantly correlated with earthquakes of magnitude $\geq 4.5$ , 5.0 and 5.5. We then calculate the distance ( $d/^{\circ } $ ) and time lag $(t/\text {days})$ between each TIR anomaly and the corresponding earthquake. By examining the distribution of earthquakes in $t \times d$ space, our results show that the normalized frequency of earthquakes as a function of distance and time follows a power-law distribution: $f(d,t,M)=\phi (M) *t^{-d_{t}(M)}*d^{-d_{d}(M)}$ , where $f(d,t,M)$ represents the frequency of earthquakes with magnitude ${\geq }M$ occurring within the time-space unit $(t, d)$ around TIR anomalies. The coefficient $\phi (M)$ is negatively correlated with magnitude $[\phi (4.5)=0.31,\phi (5.0)=0.30,\phi (5.5)=0.28]$ , while $d_{d}(M)$ and $d_{t}(M)$ are two positive coefficients $[d_{t}(4.5)=1.59,d_{t}(5.0)=1.58,d_{t}(5.5)=1.50;d_{d}(4.5)=2.76,d_{d}(5.0)=2.66,d_{d}(5.5)=2.59]$ . A larger $\phi $ suggests that earthquakes are more spatially and temporally concentrated around TIR anomalies, while $d_{d}$ and $d_{t}$ represent the decay rates of frequency with distance and time, respectively. These findings imply that earthquakes are more likely to occur near TIR anomalies, and the model $f(d,t,M)$ could potentially be used to construct a probabilistic earthquake forecasting system based on TIR anomalies.