Atmospheric duct is an anomalous atmospheric structure that affects electromagnetic wave propagation. The important characteristics of the atmospheric ducts include duct probability, duct height, duct strength, and the thickness of the trapping layer. To investigate the statistical characteristics of atmospheric ducts over the American mainland, four stations in different regions are chosen. The seasonal and diurnal variation of the characteristics of ducts is presented. The mechanism of the seasonal and variation of ducts is revealed and the relationship between the characteristics is researched. The duct strength correlates positively with the thickness of the trapping layer, and the duct height correlates with them negatively. Moreover, the duct relationship with precipitation over different stations is clarified. It is found that the precipitation correlates positively with the probability of ducts caused by the vertical moisture gradient, and the relation is negative when the ducts are caused by temperature inversion. This work is of great value to the statistical characteristics of atmospheric ducts over the American mainland.
The atmospheric duct (AD) is an anomalous structure in which electromagnetic waves can make transhorizon propagation. ADs often occur in the formation, development and disappearance of tropical cyclones (TCs). In this work, the eXtreme Gradient Boosting (XGBoost) model is used to predict TC ducts and a relatively high accuracy of 81.3% is obtained. Shapely additional explanations (SHAP) values of the features including TC parameters and local meteorological parameters are employed to interpret XGBoost model predictions of the TC ducts existence. Furthermore, the importance ranking of the features is revealed, among which the distance between dropsondes and TC eyes is the most important. In addition, the detailed relationships between the AD existence and the features are presented. Hence, this work can not only improve the knowledge of the relationship between TC ducts and the features, but also be of great value to the ducts prediction.
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