Role of convection representation across the gray zone in forecasting warm season extreme precipitation over Shanghai from two typical cases

This study investigates the role of convection representation across the gray zone in the multigrid nesting Weather Research and Forecasting (WRF) model based on two extreme precipitation events in Shanghai during the warm season. The precipitation forecast sensitivity and physical processes are examined using three convective treatments: (1) the traditional Kain-Fritsch (KF), (2) scale-aware Grell-Freitas (GF) cumulus parameterization, and (3) explicit convection (EC) solution and different nesting configurations consisting of grid spacings of 27, 15, 9, 5, 3, and 1 km using single, double, and triple nestings. At coarser grids (> 10 km), GF produces wet biases with delayed rainfall peaks, while KF produces dry biases with largely underestimated rainfall peaks. At a 9-km grid spacing, these biases were largely reduced, and using cumulus parameterizations (CUPs) shows specific advantages over the EC in the diurnal variation in extreme precipitation. GF performs better in simulating primary rainfall peak intensity, but KF performs better in simulating diurnal timing, albeit with underestimated intensity. The utilization of CUPs is beneficial at the 5-km grid in simulating both extreme intensity and diurnal variations, but it shows mixed effects at 3 km. When the 1-km grid with explicit convection was nested directly into their outermost 15-km or 9-km grids using KF CUP, avoiding treatment in the gray zone (5 km or 3 km), the primary rainfall peak at noon was best reproduced, but a secondary peak with a weak forcing was not detected. This peak was identified with local moisture divergence and a stable atmosphere.

Automated summary

This study investigates the impact of convection representation in the WRF model on extreme precipitation events in Shanghai, finding that the GF parameterization performs better in simulating primary rainfall intensity peaks, while the KF parameterization is more accurate in capturing diurnal timing of precipitation events.