Quantifying High‐Frequency Turbulence Energy in the Atmosphere and Its Impact on Near‐Surface Diffusion: Parameterization Scheme and Validation in WRF‐Chem

Abstract Atmospheric turbulence is a key meteorological factor influencing the diffusion of urban near‐surface air pollution. The turbulence energy spectrum characterizes the distribution of turbulent kinetic energy (TKE) across different eddy scales, with the total energy affecting the diffusion coefficient and pollutant dispersion. Current methods for calculating TKE are sensitive to the temporal resolution of wind speed data, and the limited sampling frequency of instruments is much lower than the dissipation scale. Thus, the high‐frequency turbulence energy is missed, and the total TKE is underestimated. To address this issue, this study used high (∼10 Hz) and low (∼0.05 Hz) frequency wind observations from the Beijing 325‐m meteorological tower to assess how sampling frequencies impact TKE calculations. The −5/3 law of the turbulence spectrum was applied to estimate the relationship between observed and theoretical total TKE, and a parameterization scheme was completed. Results showed that the underestimation due to sampling frequency limitations ranges from 10% to 37%, with higher proportions during night and winter. Then a correction factor (HTMC) was incorporated into the BouLac PBL scheme in WRF‐Chem. Sensitivity simulations of a heavy haze event in Shenyang were set. The experimental group (EXP) showed lower concentrations of PM 2.5 near the surface and higher in higher altitudes than those in control group (CTR) during night, indicating stronger vertical turbulent transport. The concentrations in EXP better match observations, with simulation bias reduced from 23.77% to 6.18%. This work provides new insights into urban turbulence transport mechanisms and benefits to improvements in air quality forecasting.