Analysis of mesoscale characteristics and forecasting bias of severe torrential rain in western Hunan Province on 29 June 2023
Article
Figures
Metrics
Preview PDF
Reference
Related
Cited by
Materials
Abstract:
From 29 to 30 June 2023, a local abrupt torrential rainstorm occurred in the western region of Hunan Province, but the forecasters and numerical models both failed to forecast the rainfall intensity. Based on conventional surface and upper-air observation data, Doppler radar and FY-4A data, ERA5 reanalysis data and numerical forecast products, the mesoscale characteristics and forecast difficulties of this heavy rainfall event were analyzed. The results show that this is a severe torrential rain process under the background of the northwest airflow behind the upper-level trough. The northwest airflow drives the cold air behind the northeast cold vortex to the south, and merges with the southwester warm-humid air flows strengthened at night, which leads to the occurrence of this process. The severe torrential rain is caused by a back-building and quasi-stationary meso-α-scale convective system ( MCS ), which is composed of several strongly developing γ-scale MCSs. On the doppler radar image, the MCS shows as an organized linear echo band, and the echo belongs to the warm cloud precipitation echo of low centroid and high rainfall efficiency. Under the favorable environmental background, the long-term maintenance of the boundary layer convergence line,the wind velocity pulsation of the low-level jet and the vertical structure of low-level convergence and high-level divergence lead to the initiation and organization of the convective cells, the consolidation strengthening, backward propagation of MCS and convective cell train effect are important reasons for the severe torrential rains. The significant deviations in the subjective forecast of short-term timeliness was possibly caused by the forecasting deviation of the lower troposphere dynamic and thermal fields of the numerical models, the deficiency of forecaster"s ability to correct the model forecast and the uncertainty of the heavy rainstorm forecast increased by the complex topography in western Hunan.. Therefore, it is very crucial for forecasters to use the automatic weather station data, satellite data and radar data with high spatiotemporal resolutions to analyze the changes of the mesoscale environmental conditions, strengthen the short-term nowcasting, and issue early warning signals in time.