A detailed analysis of the dynamic frequency spectrum characteristics of gravity waves (GWs) during a local heavy rainfall event on 20-21 November 2016 in Foshan, China, is presented. The results of this analysis, which was based on high-precision microbarograph data, indicate that GWs played a key role in generating the rainstorm. The GWs experienced two intermittent periods of amplitude enhancement and period widening. The largest amplitudes of the GWs were 80-160 Pa, with a corresponding period range of 140-270 min, which were approximately 4 h ahead of the rainstorm. The severe storms appeared to affect the GWs by augmenting the wave amplitudes with center amplitudes of approximately 80-100 Pa and periods ranging between 210 and 270 min; in particular, the amplitudes increased to approximately 10 Pa for GWs with shorter periods (less than 36 min). The pre-existing large-amplitude GWs may be precursors to severe storms; that is, these GWs occurred approximately 4 h earlier than the time radars and satellites identified convections. Thus, these results indicate that large-amplitude GWs constitute a possible mechanism for severe-storm warning.

This article proposed a new quality control method (CS-MSF) to identify potential outliers in the surface temperature observations. The CS-MSF method employed cosine similarity and moving surface fitting to obtain the estimated value of the target station. For the regions with complex terrain and low weather station density, another quality control method (CE-GBDT) was employed to compensate for the shortcomings of CS-MSF. Compared to the spatial regression test method (SRT) and inverse distance weighting method (IDW), the results indicated that CS-MSF outperformed SRT and IDW in all the cases. And CE-GBDT was superior to the other methods for the regions with complex terrain and low weather station density. The comparison results led to the recommendation that the two proposed methods are effective quality control methods in identifying the seeded errors for the surface temperature observations.

Based on high-resolution pressure data collected by a microbarograph and Fourier transform (FFT) data processing, a detailed analysis of the frequency spectra characteristics of gravity waves during a hailstone event in the cold vortex of Northeast China (NECV) on 9 Sep 2021 is presented. The results show that the deep NECV served as the large-scale circulation background for the hailstone event. The development of hailstones was closely related to gravity waves. In different hail stages, the frequency spectra characteristics of gravity waves were obviously different. One and a half hours before hailfall, there were gravity wave precursors with periods of 50–180 min and corresponding amplitudes ranging from 30 to 60 Pa. During hailfall, the center amplitudes of the gravity waves were approximately 50 Pa and 60 Pa, with the corresponding period ranges expanding to 60–70 min and 160–240 min. Simultaneously, hailstones initiated shorter periods (26–34 min) of gravity waves, with the amplitudes increasing to approximately 12–18 Pa. The relationship between hailstones and gravity waves was positive. After hailfall, gravity waves weakened and dissipated rapidly. As shown by the reconstructed gravity waves, key periods of gravity wave precursors ranged from 50–180 min, which preceded hailstones by several hours. When convection developed, there was thunderstorm high pressure and an outflow boundary. The airflow converged and diverged downstream, resulting in the formation of gravity waves and finally triggering hailfall. Gravity wave predecessors are significant for hail warnings and artificial hail suppression.