Influences of planetary boundary layer mixing parameterization on summertime surface ozone concentration and dry deposition over North China

Abstract

We present a regional modeling study that analyzes how planetary boundary layer (PBL) and surface layer parameterizations influence surface ozone concentrations and dry deposition fluxes over the Beijing-Tianjin-Hebei region in summer (July 2015). We use the Weather Research and Forecasting Model coupled to Chemistry (WRF-Chem) to simulate surface ozone concentration and dry deposition, and examine three PBL schemes: the Yonsei University (YSU), Mellor–Yamada–Janjić (MYJ), and Asymmetric Convective Model version 2 (ACM2) schemes. The model sensitivity to surface layer schemes is also tested by coupling the ACM2 PBL scheme with either the revised MM5-similarity scheme or the Pleim-Xiu surface layer scheme. Key physical and chemical factors for ozone dry deposition parameterization are analyzed to explore the root causes of model discrepancies. We find that all simulations overestimate the summertime daily mean ozone concentrations over North China (42 ppbv in observations vs. 43–50 ppbv in model results for July 2015) that are caused by high biases in daytime ozone and partly compensated by low biases in nighttime ozone. The YSU scheme has the largest overestimate in daily mean ozone concentration, but best reproduces the ozone diurnal cycle. The ACM2 scheme shows the largest underestimates of surface ozone over North China during nighttime, which can be explained by its weakest vertical mixing leading to high NOx concentrations and strong ozone titration near surface. The choices of PBL and surface layer schemes lead to over 20% differences in ozone dry deposition fluxes due to differences in simulated surface ozone concentrations and dry deposition velocities. We find the differences in dry deposition velocity are mainly caused by differences in Monin-Obukhov length during nighttime and surface temperature during daytime. Our study emphasizes the needs to better understand these key PBL and surface factors for reducing the uncertainties in model simulation of surface ozone concentration and dry deposition.