Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Studying The Impact Of The Geospace Environment On Solar Lithosphere Coupling And Earthquake Activity, Dimitar Ouzounov, Galina Khachikyan
Studying The Impact Of The Geospace Environment On Solar Lithosphere Coupling And Earthquake Activity, Dimitar Ouzounov, Galina Khachikyan
Mathematics, Physics, and Computer Science Faculty Articles and Research
In solar–terrestrial physics, there is an open question: does a geomagnetic storm affect earthquakes? We expand research in this direction, analyzing the seismic situation after geomagnetic storms (GMs) accompanied by the precipitation of relativistic electrons from the outer radiation belt to form an additional radiation belt (RB) around lower geomagnetic lines. We consider four widely discussed cases in the literature for long-lived (weeks, months) RBs due to GMs and revealed that the 1/GMs 24 March 1991 with a new RB at L~2.6 was followed by an M7.0 earthquake in Alaska, 30 May 1991, near footprint L = 2.69; the 2/GMs …
Application Of Model-Based Time Series Prediction Of Infrared Long-Wave Radiation Data For Exploring The Precursory Patterns Associated With The 2021 Madoi Earthquake, Jingye Zhang, Ke Sun, Junqing Zhu, Ning Mao, Dimitar Ouzounov
Application Of Model-Based Time Series Prediction Of Infrared Long-Wave Radiation Data For Exploring The Precursory Patterns Associated With The 2021 Madoi Earthquake, Jingye Zhang, Ke Sun, Junqing Zhu, Ning Mao, Dimitar Ouzounov
Mathematics, Physics, and Computer Science Faculty Articles and Research
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 …