By using an alternative processing method for satellite infrared remote sensing data and adopting the China Geostationary Meteorological Satellite (FY-2C) infrared remote sensing brightness temperature data, we studied the great 2008 Wenchuan Ms8.0 earthquake. Results indicate the obvious characteristic period and amplitude, and distribution of thermal infrared anomalies before the Wenchuan earthquake. And we discussed the mechanism of the observed pre-earthquake thermal anomalies. The characteristics of observed thermal infrared anomalies are easy to be recognized and applied, and could provide a criterion for thermal anomalies of earthquakes.Wenchuan Ms8.0 earthquake, Geostationary Meteorological Satellite infrared remote sensing, brightness temperature change Citation:Zhang Y S, Guo X, Zhong M J, et al. Wenchuan earthquake: Brightness temperature changes from satellite infrared information.

An Mw 5.9 thrust earthquake occurred on 21 January 2016 in the northeastern Tibetan plateau, where another similar earthquake had ruptured in 1986. Because of the complexity and close proximity of multiple faults in this area, the exact causative fault sources for these two events have not previously been determined. We determined the seismogenic fault structural geometry of the 2016 event by analyzing the coseismic deformation from Sentinel-1A images, aftershock relocations, and geological data. Furthermore, field investigations and the relocated aftershocks for the 1986 event were used to investigate its seismogenic fault and relation with the 2016 Menyuan earthquake. The results indicate that the reverse slip of both events was distributed on the southwest-dipping Minyue-Damaying fault, where the 2016 event ruptured the deep segment and the 1986 event ruptured the shallow segment. We envision that the depth segmentation played an important role in the occurrence of two moderate earthquakes rupturing the same active fault but separated by almost 30 yr, which is thought much shorter than the average earthquake recurrence cycle. Our study indicates that seismic risks could be underestimated if depth segmentation is not considered.

Taking the 2017 Mw6.5 Jiuzhaigou earthquake as a case study, ionospheric disturbances (i.e., total electron content and TEC) and thermal infrared (TIR) anomalies were simultaneously investigated. The characteristics of the temperature of brightness blackbody (TBB), medium-wave infrared brightness (MIB), and outgoing longwave radiation (OLR) were extracted and compared with the characteristics of ionospheric TEC. We observed different relationships among the three types of TIR radiation according to seismic or aseismic conditions. A wide range of positive TEC anomalies occurred southern to the epicenter. The area to the south of the Huarong mountain fracture, which contained the maximum TEC anomaly amplitudes, overlapped one of the regions with notable TIR anomalies. We observed three stages of increasing TIR radiation, with ionospheric TEC anomalies appearing after each stage, for the first time. There was also high spatial correspondence between both TIR and TEC anomalies and the regional geological structure. Together with the time series data, these results suggest that TEC anomaly genesis might be related to increasing TIR.

Based on the outgoing long‐wave radiation data of geostationary satellite and their variation characteristics, this paper proposes a method for extracting earthquake thermal infrared anomaly, namely, the relative variance rate of power spectrum estimation. The proposed method is applied to analyze OLR for the Wenchuan earthquake and other five Ms ≥ 6.5 earthquakes in Mainland China. The results indicate that the power spectrum amplitude of OLR increased to different degrees before the great earthquakes. The characteristic period and characteristic amplitude are short and small in moist (low altitude) areas respectively, while the period and amplitude are long and big in arid (high altitude) areas respectively. The characteristics of observed thermal infrared anomalies are easy to be recognized. The method is very effective for extracting useful information and can be used to the extraction and analysis of earthquake‐related information.