文章基本信息

标题：The Prediction of Day-to-Day Occurrence of Low Latitude Ionospheric Strong Scintillation Using Gradient Boosting Algorithm
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作者：Xiukuan Zhao ; Guozhu Li ; Haiyong Xie 等
期刊名称：Space Weather
印刷版ISSN：1542-7390
出版年度：2021
卷号：19
期号：12
页码：1-14
DOI：10.1029/2021SW002884
语种：English
出版社：American Geophysical Union
摘要：Ionospheric scintillations caused by equatorial plasma bubbles (EPBs) can seriously affect various high technology systems based on Global Navigation Satellite System (GNSS) signals at equatorial and low latitudes. A reliable prediction of ionospheric scintillation occurrence is critical to relieve the effect. Using the long-term ground-based GNSS receiver and ionosonde data collected in the Brazilian longitude sector during 2012–2020, an ionospheric strong scintillation prediction model based on the gradient boosting algorithms extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and CatBoost is created and tested. It is for the first time that the XGBoost, LightGBM, and CatBoost are utilized to predict the day-to-day occurrence of regional ionospheric scintillation during post-sunset hours. The relative importance of different parameters affecting EPB/scintillation occurrence for building the prediction model is examined. A comparison of daily scintillation occurrence from the modeled and observed results during 2014 (solar maximum) and 2020 (solar minimum) shows that the gradient boosting algorithms are effective for predicting strong scintillations over low latitude, with a prediction accuracy of ∼85%. The results suggest that the trained model with input of total electron content, equatorial F layer peak height and critical frequency before sunset could be well employed to predict the occurrence/nonoccurrence of intense scintillations over low latitude after sunset on a daily basis.