Analysis on the Causes and Forecast Deviation of Rainstorm on the Eastern Foot of Qinling Mountains

Doppler radar, FY-4B satellite data, wind profile radar, ERA-5 reanalysis data, automatic weather station and other multi-source observation data are used to analyze the causes and forecast deviation of a rainstorm on the eastern foot of Qinling mountains in Shaanxi province of China on 19th July 2024, and the results indicated that the rainstorm had strong suddenness, locality and convection. The main water vapor and energy for the rainstorm were provided by the southwest low-level jet at 700 hPa, and the strengthening of the jet stream and the decrease in the height of the jet stream core had a good correlation with the occurrence of heavy precipitation. The mesoscale convective system(MCS) causing rainstorm was formed by the the merging and strengthening of locally generated cold clouds in the convergence and upward movement zone of 700 hPa jet stream front and mesoscale convective clouds moving from southwest to east. And the convective system continued to develop along the mountain direction, forming a "train effect" that strengthens local heavy rainfall. Topography played an important role in this rainstorm.  On the one hand, the Qinling Mountains block the low-level jet stream at 700hPa, causing water vapor to strongly accumulate on the windward slope and converge and rise. On the other hand, the Qinling Mountains produced a significant topographic uplift movement on the ground and southerly winds at 850 hPa, thereby strengthening precipitation together. The 24-hour precipitation forecast was significantly missed by several numerical models because of deviation of 700 hPa jet location and intensity, but the CMA-BJ model had good prediction on the falling area and intensity of heavy rainfall for 3 h. Conducting analysis of similar rainstorm events, summarizing the deviation characteristics of the numerical models, considering the triggering and maintenance mechanisms of convection, and the important role of terrain would help improve the forecasting and early warning capabilities of such rainstorm.