Sensitivity analysis of planetary boundary layer parameterization on meteorological simulations in the Yangtze river delta region, China†

The planetary boundary layer (PBL) plays a crucial role in determining meteorological fields and the diffusion of atmospheric pollutants. Therefore, accurate PBL simulation is necessary for precise meteorological and air quality simulations, and the choice of PBL scheme significantly influences the accuracy of simulation results. In this study, we investigate the seasonal and diurnal variations of typical meteorological variables over the Yangtze River Delta (YRD) region by using the Weather Research and Forecasting (WRF) model using four different closure schemes. These closure schemes include two non-local closure schemes, i.e., Yonsei University (YSU) and Asymmetric Convective Model version 2 (ACM2), as well as two local closure schemes named Mellor–Yamada–Janjic (MYJ) and Mellor–Yamada Nakanishi and Niino (MYNN). By comparing observations and model inter-comparisons, we discuss the similarities and differences in simulated results among different PBL schemes. The results indicate that local closure schemes, i.e., MYJ and MYNN, generally produce more realistic simulations of meteorological parameters. MYNN performs best in summer with a mean bias (MB) of 0.41 °C for temperature and 0.44 m s⁻¹ for wind speed, while MYJ shows better results under stable conditions during winter with a MB of 0.64 °C for temperature and −5.76% for relative humidity. YSU is found to have less bias in PBL height during summer with the highest R up to 0.81, while MYJ outperforms the three other schemes with the least MB of 38 m (R = 0.65) in winter. Each PBL closure scheme, i.e., the MYJ and MYNN local closure schemes, may not accurately capture all physical processes, leading to performance variations, especially during transitional seasons and under specific diurnal conditions. Thus, it is important to note that each scheme has its strengths and weaknesses, and the selection of the most appropriate scheme should depend on the specific variables and scenarios under consideration.