Assessing Raindrop Size Distribution Parameterization for Enhanced Prediction of Heavy Precipitation Process in Xinjiang

Utilizing the raindrop spectrum observation data from Urumqi, Xinjiang, collected between 3 July and 3 October 2018, this study aimed to enhance the WRF Single-Moment 6-class (WSM6) scheme in the Urumqi regional high-resolution numerical prediction system. The improved scheme’s effectiveness in predicting heavy precipitation events was evaluated in Xinjiang from 1200 BJT (Beijing time) on 15 June to 0000 BJT on 17 June 2021. The results indicated that the average diameter (D₀), maximum diameter (D_max), and mass-weighted average diameter (D_m) of raindrops in Urumqi were 0.65 mm, 1.60 mm, and 0.93 mm, respectively. Furthermore, the refined WSM6-new scheme, which considered the fitting relationship between parameters lgN_w and D_m in Xinjiang, enhanced the prediction capability for precipitation intensity and strong center ranges to some extent. Evaluation metrics, such as TS, BR, ETS, and TSS, revealed that the WSM6-new scheme significantly improved the prediction accuracy as precipitation grade increased, specifically for heavy and torrential rainfall. Different raindrop size distribution parameter schemes influenced precipitation cloud systems characteristics, vertical velocities, atmospheric stratification, and divergence field. Moreover, the effect on cloud microphysical processes primarily manifested in rainwater content and distribution. The WSM6-new scheme incorporated the statistical characteristics of Xinjiang’s raindrop spectrum, rendering the raindrop size distribution in the model more accurate. The number concentration of larger raindrops in the raindrop spectrum increased significantly, along with terminal raindrop velocity and enhanced drag effects. This facilitated the intensification and maintenance of downdraft below the freezing level. The strong downdraft generated a powerful divergent outflow near the ground layer, which intensified air convergence in the ground-level convection area, promoting updraft development and strengthening. Consequently, a more intense precipitation process occurred at the surface, and the prediction capability for heavy rain and torrential rain was remarkably enhanced.