Changes in Tropospheric Ozone Associated With Strong Earthquakes and Possible Mechanism

The index of ozone anomaly (IOA) has been proposed to detect changes in tropospheric ozone associated with strong earthquakes. The tropospheric ozone prior and after the 2008 Wenchuan earthquake has been analyzed using IOA. Atmospheric infrared sounder ozone volume mixing ratio (O3 VMR) at different pressure levels (600, 500, 400, 300, 200 hPa) for an 18-year period 2003–2020 has been considered to identify the unique behavior associated with the strong earthquakes. Our results show distinct enhancement in tropospheric ozone occurred 5 d (7 May 2008) prior to the main event and distributed along the Longmenshan fault zone. An enhancement in IOA has also been observed around the time of the 2013 Lushan and 2017 Jiuzhaigou earthquakes, but with the different emergence time, which indicates that the unusual behavior of tropospheric ozone depends on the tectonic and geological environment, focal mechanism, focal depth, meteorological conditions, and other factors. The location of increased tropospheric ozone indicates the epicenter of earthquakes. The magnitude of earthquake could be one of the important factors affecting the appearance of the anomalous tropospheric ozone. The possible mechanism for the increased tropospheric ozone associated with strong earthquakes is discussed in this article. The quasi-synchronous changes of tropospheric ozone and other parameters in the lithosphere/atmosphere/ionosphere have been found by combining with the other published results related to the Wenchuan earthquake, which show the existence of coupling during the earthquake preparation phase associated with the lithosphere–atmosphere–ionosphere coupling

Land – Atmosphere – Meteorological Coupling Associated with the 2015 Gorkha (M 7.8) and Dolakha (M 7.3) Nepal Earthquakes

Multiple parameters (brightness temperature, soil moisture, surface latent heat flux, surface air temperature and carbon monoxide) before and after the 2015 Nepal M7.8 Gorkha main earthquake and M7.3 Dolakha aftershock were analysed using satellite observation data. The thermal anomalies from optical and microwave data appear about two months prior to the 2015 Gorkha earthquake. Some of the parameters show anomalous changes at different altitudes about 20 days prior to the main earthquake event and 10 days prior to the strong aftershock. Our results show that pre-earthquake anomalous signals propagate from the in situ to the top of atmosphere, and the anomalies in the atmosphere often observed prior to an impending earthquake. The changes on the land surface and corresponding changes in meteorological and atmospheric parameters show existence of strong coupling during the seismogenic period, although the transfer mechanism of seismic/electromagnetic is still has to be investigated and understood

Application of Model-Based Time Series Prediction of Infrared Long-Wave Radiation Data for Exploring the Precursory Patterns Associated with the 2021 Madoi Earthquake

Taking the Madoi MS 7.4 earthquake of 21 May 2021 as an example, this paper proposes using time series prediction models to predict the outgoing long-wave radiation (OLR) anomalies and study short-term pre-earthquake signals. Five time series prediction models, including autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM), were trained with the OLR time series data of the aseismic moments in the 5° × 5° spatial range around the epicenter. The model with the highest prediction accuracy was selected to retrospectively predict the OLR values during the aseismic period and before the earthquake in the area. It was found, by comparing the predicted time series values with the actual time series value, that the similarity indexes of the two time series before the earthquake were lower than the index of the aseismic period, indicating that the predicted time series before the earthquake significantly differed from the actual time series. Meanwhile, the temporal and spatial distribution characteristics of the anomalies in the 90 days before the earthquake were analyzed with a 95% confidence interval as the criterion of the anomalies, and the following was found: out of 25 grids, 18 grids showed anomalies—the anomalies of the different grids appeared on similar dates, and the anomalies of high values appeared centrally at the time of the earthquake, which supports the hypothesis that pre-earthquake signals may be associated with the earthquake

Research on thermal infrared anomaly characteristics of moderate strong earthquakes in northeast China

In this article, the daily brightness temperature data from January 2006 to May 2020 of China’s geostationary meteorological satellite FY-2E/G were used to identify the brightness temperature differences before deep and shallow earthquakes in the study area using wavelet transform and the relative wavelet power spectrum (RWPS) methods. The objective was to explore the characteristics of thermal infrared (TIR) radiation anomaly changes before deep and shallow earthquakes in Northeast China by carrying out anomaly extraction and data analysis. The research has shown that five significant earthquakes experienced TIR radiation anomalies in the vicinity of the epicenter approximately 1–2 months before the event. The amplitude of the anomaly ranged from seven to twenty times higher than average, and the anomaly lasted about 3 months. The infrared radiation anomaly characteristics before the earthquake were especially significant in the case of two earthquakes in the Songyuan area. From the research, it was concluded that the TIR radiation anomaly could act as a short-term precursor for earthquake prediction. The method employed in this study would provide great support for predicting deep and shallow earthquakes in Northeast China using satellite thermal infrared technology

Geosystemics View of Earthquakes

Earthquakes are the most energetic phenomena in the lithosphere: their study and comprehension are greatly worth doing because of the obvious importance for society. Geosystemics intends to study the Earth system as a whole, looking at the possible couplings among the different geo-layers, i.e., from the earth’s interior to the above atmosphere. It uses specific universal tools to integrate different methods that can be applied to multi-parameter data, often taken on different platforms (e.g., ground,marine or satellite observations). Itsmain objective is to understand the particular phenomenon of interest from a holistic point of view. Central is the use of entropy, together with other physical quantities that will be introduced case by case. In this paper, we will deal with earthquakes, as final part of a long-term chain of processes involving, not only the interaction between different components of the Earth’s interior but also the coupling of the solid earth with the above neutral or ionized atmosphere, and finally culminating with the main rupture along the fault of concern. Particular emphasis will be given to some Italian seismic sequences.Publishedid 4121A. Geomagnetismo e PaleomagnetismoJCR Journa

Transient effects in atmosphere and ionosphere preceding the 2015 M7.8 and M7.3 Gorkha–Nepal earthquakes

We analyze retrospectively/prospectively the transient variations of six different physical parameters in the atmosphere/ionosphere during the M7.8 and M7.3 earthquakes in Nepal, namely: 1) outgoing longwave radiation (OLR) at the top of the atmosphere (TOA); 2) GPS/TEC; 3) the very-low-frequency (VLF/LF) signals at the receiving stations in Bishkek (Kyrgyzstan) and Varanasi (India); 4) Radon observations; 5) Atmospheric chemical potential from assimilation models; and; 6) Air Temperature from NOAA ground stations. We found that in mid-March 2015, there was a rapid increase in the radiation from the atmosphere observed by satellites. This anomaly was located close to the future M7.8 epicenter and reached a maximum on April 21–22. The GPS/TEC data analysis indicated an increase and variation in electron density, reaching a maximum value during April 22–24. A strong negative TEC anomaly in the crest of EIA (Equatorial Ionospheric Anomaly) occurred on April 21, and a strong positive anomaly was recorded on April 24, 2015. The behavior of VLF-LF waves along NWC-Bishkek and JJY-Varanasi paths has shown abnormal behavior during April 21–23, several days before the first, stronger earthquake. Our continuous satellite OLR analysis revealed this new strong anomaly on May 3, which was why we anticipated another major event in the area. On May 12, 2015, an M7.3 earthquake occurred. Our results show coherence between the appearance of these pre-earthquake transient’s effects in the atmosphere and ionosphere (with a short time-lag, from hours up to a few days) and the occurrence of the 2015 M7.8 and M7.3 events. The spatial characteristics of the pre-earthquake anomalies were associated with a large area but inside the preparation region estimated by Dobrovolsky-Bowman. The pre-earthquake nature of the signals in the atmosphere and ionosphere was revealed by simultaneous analysis of satellite, GPS/TEC, and VLF/LF and suggest that they follow a general temporal-spatial evolution pattern that has been seen in other large earthquakes worldwide

Coarse-graining research of the thermal infrared anomalies before earthquakes in the Sichuan area on Google Earth engine

Seismo-induced Thermal infrared (TIR) anomalies has been proposed as a significant precursor of earthquakes. Several methods have been proposed to detect Thermal infrared anomalies that may be associated with earthquakes. However, there is no comparison of the influence for Thermal infrared extraction methods with a long time statistical analysis. To quantify the effects of various techniques used in Thermal infrared anomaly extraction, in this paper, we offer a complete workflow of their comparative impacts. This study was divided into three parts: anomaly detection, statistical analysis, and tectonic factor research. For anomaly detection, daily continuous nighttime surface temperature (ConLST) data was obtained from the Google Earth Engine (GEE) platform, and each different anomaly detection method was used to detect Thermal infrared outliers in the Sichuan region (27°-37°N, 97°-107°E). During statistical analysis, The heated core model was applied to explore Thermal infrared anomalies which is to filter anomalies unrelated to earthquakes by setting time-space-intensity conditions. The 3D error diagram offers scores to assume the best parameter set using training-test-validation steps. In the final part, we considered information on stresses, active faults, and seismic zones to determine the optimal parameters for extracting the Thermal infrared anomalies. The Kalman filter method detected the highest seismic anomaly frequency without considerating the heating core condition. The Autoencoder and Isolation Forest methods obtain the optimal alert type and parameter set to determine if the anomaly is likely earthquake-related. The RST method performs optimally in the final part of the workflow when it considers physical factors such as active faults, seismic zones, and stresses. However, The six methods we have chosen are not sufficient to contain the entire Thermal infrared anomaly extraction. The consideration of tectonic factors in the research remains poorly developed, as statistical methods were not employed to explore the role of constructive factors. Nevertheless, it is a significant factor in comparing anomaly extraction methods and precursor studies