Influence of meteorological reanalysis field on air quality modeling in the Yangtze River Delta, China

Abstract

The meteorological reanalysis field is one of the key inputs to drive mesoscale meteorology simulations. To investigate the impacts of different reanalysis data on predictions of the meteorology parameters, as well as predictions of air quality, this study utilized the Weather Research and Forecasting/Community Multiscale Air Quality modeling system (WRF/CMAQ) with two sets of meteorological reanalysis inputs, the NCEP Final Operational Global Analysis (FNL) and the ECMWF Reanalysis v5.0 (ERA5) to predict the concentrations of ozone (O3) and fine particulate matter (PM2.5) in the Yangtze River Delta (YRD) in 2018. The results showed that ERA5 outperformed FNL in simulating 2-m temperature and relative humidity, while FNL demonstrated better accuracy in predicting wind fields. Both FNL and ERA5 underestimated the PM2.5 in spring and summer while overestimating it in autumn and winter. Furthermore, the Normalized mean bias (NMB) value for ERA5 exceeded the standard in winter (0.34), and the Normalized mean error (NME) value exceeded the standard in autumn (0.54). Both FNL and ERA5 underestimated the PM2.5 concentration during the pollution episodes, and FNL's simulations of PM2.5 concentrations were closer to observations than ERA5's as pollution levels intensified. Regarding O3 concentrations, ERA5 exhibited better performance than FNL, with the NMB (0.30, 0.27) and NME (0.39, 0.37) of FNL and ERA5 both exceeding the standard only in wintertime.