A recent study suggests that earthquake prediction might be possible using satellite data to identify environmental anomalies. Analyzing data from the 2023 High Atlas Mountains earthquake, the study found abnormal fluctuations in atmospheric and ionospheric parameters up to 9 days before the event. Can scientists predict earthquakes days before they happen? According to a new study conducted by researchers from Pakistan, China, Saudi Arabia, and Egypt, it might be possible to predict earthquakes using satellite data to identify precursors. These precursors refer to measurable changes in environmental parameters that occur before a main shock, like a powerful earthquake. To investigate this possibility, researchers analyzed data from the M6.8 earthquake that struck the High Atlas Mountains in Morocco on September 8, 2023. This devastating earthquake resulted in 3,000 fatalities and affected nearly 2.8 million people. The study, published on August 2 in the peer-reviewed journal Science Direct, examined atmospheric and ionospheric anomalies that occurred prior and days after the earthquake. Scientists employed a combination of statistical methods and deep learning to analyze data from multiple satellites, including GNSS (Global Navigation Satellite System) and remote sensing satellites. «Global Navigation Satellite System (GNSS) and Remote Sensing (RS) satellite applications have provided valuable insights into observing potential earthquake precursors at various altitudes across seismic zones before the occurrence of future main shocks», the study reads. Abnormal fluctuations in atmospheric and ionospheric parameters Researchers investigated several atmospheric parameters, such as Outgoing Longwave Radiation (OLR), Relative Humidity (RH), Air Pressure (AP), and Air Temperature (AT), as well as ionospheric data to identify anomalies preceding the earthquake. The analysis uncovered abnormal fluctuations in OLR, RH, and TEC data within 8-9 days before the earthquake near the epicenter. Additionally, geomagnetic anomalies in the ionosphere were detected 6 days prior to and 4 days after the earthquake, coinciding with active geomagnetic storm days. «Both statistical and deep learning methods revealed abnormal fluctuations as precursors occurring within 8–9 days before the earthquake near the epicenter», the researchers stated. «We detected geomagnetic anomalies in the ionosphere 6 days prior to and 4 days after the earthquake, coinciding with active geomagnetic storm days», they added. The study suggests that earthquakes can trigger disturbances that travel upwards through the Earth's layers, affecting the atmosphere and ionosphere. By identifying these disturbances, scientists may develop better earthquake prediction and early warning systems. It is important to note that the researchers utilized freely available data from resources such as the USGS (United States Geological Survey) and NASA (National Aeronautics and Space Administration). While this research is promising, predicting earthquakes with high accuracy remains a significant challenge.
