Ensemble Forecast Experiments of PM_2.5 Based on Multiple Boundary Layer Schemes in Tianjin

Based on the atmospheric chemical model WRF/Chem, four kinds of boundary layer schemes (YSU, BL, MYJ and MYN3) are used to simulate the evolution of PM_2.5 mass concentration of Tianjin in 2015. Effects of different boundary layer schemes on the simulation and prediction of PM_2.5 mass concentration are analyzed, and a set of prediction products with various boundary layer schemes are constructed to improve forecast effects. Results show that the best boundary layer scheme for the near surface temperature simulation is BL scheme, the best boundary layer scheme for relative humidity simulation is MYN scheme and YSU scheme, the best boundary layer scheme for wind speed simulation is YSU scheme, and four boundary layer schemes of atmospheric chemical model have good applicability in simulation of air quality. The correlation coefficient between the simulated value and the actual value can reach 0.76, and the relative error is between 31.7% and 33%. Among four boundary layer schemes, MYN scheme leads to highest simulated boundary layer height, and the simulated boundary layer height of BL scheme is the lowest. As for the correlation coefficient between boundary layer height and PM_2.5 mass concentration, BL scheme is the highest (0.64), comparing to 0.62 with YSU scheme and MYJ scheme, and only 0.5 with MYN scheme. No single scheme has significant advantages. BL scheme is better in sunny and windy weather, while YSU and MYJ schemes perform better in cloudy and breeze weather. The simulated PM_2.5 mass concentration in Tianjin shows a significant disturbance characteristic with different boundary layer schemes. The standard deviation of daily average PM_2.5 concentration is about 5.2 μg·m^-3, accounting for 8% of the mean, and its maximum can reach 23 μg·m^-3. The hourly standard deviation reaches 11.8%, which is greater than the daily standard deviation, especially in the process of mutual transformation between stable boundary layer and unstable boundary layer. To overcome these problems, air quality ensemble prediction tests of multiple boundary layer schemes are carried out in Tianjin. Based on the analysis of forecast value in 2015, the ensemble prediction of multiple boundary layer schemes and disturbance of multiple aerosol mechanisms can decrease the relative error and root mean square error of PM_2.5 mass concentration prediction by about 25%. It can also reduce the false negative rate of heavy pollution weather from 44% to 30% and improve the forecasting capabilities of air quality level by 3%-6%. When the computing resources are sufficient, it is also an effective means to enhance the forecast ability of PM_2.5 mass concentration.