Uncertainty Analysis of the Extreme Rainstorm in Beijing on July 2023 Based on the Convection-Allowing Ensemble Forecast System of North China

Abstract In July 2023, Beijing and southern Hebei experienced exceptionally heavy rainfall due to the remnants of Typhoon “Dussuri.” This study aims to investigate the factors influencing the forecast performance of numerical models for this event and the sources of forecast uncertainty. Initially, the operational convection-allowing ensemble forecast system (CAEFS) of North China was evaluated for its forecast accuracy. Based on ensemble forecast results, ensemble sensitivity analysis and ensemble group difference analysis were conducted to understand the variability among ensemble members. The findings highlight several influencing factors, notably the position of the high pressure system and the role of low-level jet streams, and there is significant uncertainty surrounding the large-scale circulation near the inverted trough. Ensemble member disparities reveal that good members accurately pinpoint the positions of the inverted trough and jet streams, facilitating substantial moisture transport, whereas less effective members struggle with understanding large-scale circulation dynamics and moisture factors. Given the pivotal role of large-scale circulation in this event, a scheme was devised to reconstruct background and lateral boundary conditions. This approach utilizes high-quality global deterministic forecasts to enhance the large-scale ensemble driving fields for CAEFS. Results from this new reconstruction method demonstrate marked improvements in both the location and intensity forecasts of this event, underscoring its promising application potential.