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Assessing the ability of global and regional models to describe aerosol\udoptical properties is essential to reducing uncertainty in aerosol direct\udradiative forcing in the contemporary climate and to improving confidence in\udfuture projections. Here we evaluate the performance of high-resolution\udsimulations conducted using the Weather Research and Forecasting model with\udcoupled with Chemistry (WRF-Chem) in capturing spatiotemporal variability of\udaerosol optical depth (AOD) and the Ångström exponent (AE) by\udcomparison with ground- and space-based remotely sensed observations.\udWRF-Chem is run over eastern North America at a resolution of 12 km for a\udrepresentative year (2008). A systematic positive bias in simulated AOD\udrelative to observations is found (annual mean fractional bias (MFB) is 0.15\udand 0.50 relative to MODIS (MODerate resolution Imaging Spectroradiometer)\udand AERONET, respectively), whereas the spatial variability is well captured\udduring most months. The spatial correlation of observed and simulated AOD\udshows a clear seasonal cycle with highest correlation during summer months\ud(<i>r</i> = 0.5–0.7) when the aerosol loading is large and more observations are\udavailable. The model is biased towards the simulation of coarse-mode aerosols\ud(annual MFB for AE  =  −0.10 relative to MODIS and −0.59 for AERONET),\udbut the spatial correlation for AE with observations is 0.3–0.5 during most\udmonths, despite the fact that AE is retrieved with higher uncertainty from\udthe remote-sensing observations. WRF-Chem also exhibits high skill in\udidentifying areas of extreme and non-extreme aerosol loading, and its ability\udto correctly simulate the location and relative intensity of extreme aerosol\udevents (i.e., AOD  >  75th percentile) varies between 30 and 70 % during\udwinter and summer months, respectively

Evaluating the skill of high-resolution WRF-Chem simulations in describing drivers of aerosol direct climate forcing on the regional scale