Anomalies in Infrared Outgoing Longwave Radiation Data before the Yangbi Ms6.4 and Luding Ms6.8 Earthquakes Based on Time Series Forecasting Models

Abstract

Numerous scholars have used traditional thermal anomaly extraction methods and time series prediction models to study seismic anomalies based on longwave infrared radiation data. This paper selected bidirectional long short-term memory (BILSTM) as the research algorithm after analyzing and comparing the prediction performance of five time series prediction models. Based on the outgoing longwave radiation (OLR) data, the time series prediction model was used to predict the infrared longwave radiation values in the spatial area of 5° × 5° at the epicenter for 30 days before the earthquake. The confidence interval was used as the evaluation criterion to extract anomalies. The examples of earthquakes selected for study were the Yangbi Ms6.4-magnitude earthquake in Yunnan on 21 May 2021 and the Luding Ms6.8-magnitude earthquake in Sichuan on 5 September 2022. The results showed that the observed values of the Yangbi earthquake 15 to 16 days before the earthquake (5 May to 6 May) exceeded the prediction confidence interval over a wide area and to a large extent. This indicates a strong and concentrated OLR anomaly before the Yangbi earthquake. The observations at 27 days (9 August), 18 days (18 August), and 8 days (28 August) before the Luding earthquake exceeded the prediction confidence interval in a local area and by a large extent, indicating a strong and scattered OLR anomaly before the Luding earthquake. Overall, the method used in this paper extracts anomalies in both spatial and temporal dimensions and is an effective method for extracting infrared longwave radiation anomalies.