Seasonal Characteristics of Forecasting Uncertainties in Surface PM2.5 Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region

Abstract

Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts. However, the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known. In this study, a series of forecasts with different forecast lead times for January, April, July, and October of 2018 are conducted over the Beijing-Tianjin-Hebei (BTH) region and the impacts of meteorological forecasting uncertainties on surface PM_2.5 concentration forecasts with each lead time are investigated. With increased lead time, the forecasted PM_2.5 concentrations significantly change and demonstrate obvious seasonal variations. In general, the forecasting uncertainties in monthly mean surface PM_2.5 concentrations in the BTH region due to lead time are the largest (80%) in spring, followed by autumn (~50%), summer (~40%), and winter (20%). In winter, the forecasting uncertainties in total surface PM_2.5 mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles. In spring, the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds, thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust. In summer, the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates, which are associated with the reduction of near-surface wind speed and precipitation rate. In autumn, the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles, which is associated with changes in the large-scale circulation.