Abstract: This paper proposed a new method for identification of ionospheric TEC anomalies using prophet forecasting model based on Facebook. First, we compared the precision of this new method with the traditional time series forecasting method (Autoregressive Integrated Moving Average, ARIMA models) and the identification method of the classical ionospheric TEC anomalies (Inter Quartile Range, IQR method), in predicting the background values of ionospheric TEC modeling. The results show that the precision of the former is obviously better than the latter two methods: about 2.55 times higher than that of the ARIMA models, and about 10.74 times higher than that of the IQR method. Meanwhile, when the best prediction modeling interval is established, the comparison of precision values is RMSE_IQR=10.5841>RMSE_ARIMA=3.2780>RMSE_Prophet=0.846, indicating that the traditional detection methods have insufficiency in predicting modeling background values. Second, taking the August 8, 2017 Jiuzhaigou earthquake as example, we analyzed its ionosphere TEC anomalies and proved the effectiveness and accuracy of the new method. The results show that obvious ionosphere TEC negative anomalies appeared on the 10th and 2nd days before the earthquake, and obvious ionosphere TEC positive anomalies occurred on the 7th day before the earthquake. In addition, the comparative experiments show that the validity and accuracy of the Prophet forecasting model is significantly better than the IQR method

Key words: Ionospheric TEC anomaly, Prophet forecasting model, The 2017 Jiuahaigou earthquake