Abstract. We used aerosol data from surface-based AErosol RObotic NETwork (AERONET) and day-ahead aerosol optical depth (AOD) forecasts from the Copernicus Atmosphere Monitoring Service (CAMS) to examine the spatiotemporal variations in AOD at selected sites worldwide. We evaluated three methods for day-ahead AOD forecasting: AERONET 1 d (and 2 d) persistence or monthly mean, along with CAMS forecast. High values of daily mean AOD indicates larger day-to-day variability in AOD and lower predictability. Using radiative transfer modeling, we quantify deviations in forecasts of cloud-free direct normal irradiance (DNI) induced by errors in AOD forecasts. The performance of each AOD forecast method in DNI forecast is assessed and compared. Taking into account the characteristic aerosol types at selected locations, we also draw quantitative implications about the reliability and usability of CAMS AOD forecasts for DNI forecasts as alternatives to AOD forecasts based on approaches using ground-based measurements. For example, CAMS forecasts perform better at more sites than AERONET persistence approaches do, among them many urban-industrial aerosol sites. AERONET persistence forecasts AOD with lower errors at dust aerosol sites. To date, none of the forecast methods for AOD discussed here reliably achieve an accuracy of < 5 % deviation in day-ahead forecasts of direct normal irradiation (daily sum), but most of the sites can expect better DNI forecasts with a threshold of 20 % DNI deviation.
Hou et al. (Tue,) studied this question.