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Aerosol–cloud interactions (ACIs) have been widely recognized as a factoraffecting precipitation. However, they have not been considered in theoperational National Centers for Environmental Predictions Global ForecastSystem model. We evaluated the potential impact of neglecting ACI on theoperational rainfall forecast using ground-based and satellite observationsand model reanalysis. The Climate Prediction Center unified gauge-basedprecipitation analysis and the Modern-Era Retrospective analysis for Researchand Applications Version 2 aerosol reanalysis were used to evaluate theforecast in three countries for the year 2015. The overestimation of lightrain (47.84 %) and underestimation of heavier rain (31.83, 52.94, and65.74 % for moderate rain, heavy rain, and very heavy rain, respectively)from the model are qualitatively consistent with the potential errors arisingfrom not accounting for ACI, although other factors cannot be totally ruledout. The standard deviation of the forecast bias was significantly correlatedwith aerosol optical depth in Australia, the US, and China. To gain furtherinsight, we chose the province of Fujian in China to pursue a more insightfulinvestigation using a suite of variables from gauge-based observations ofprecipitation, visibility, water vapor, convective available potential energy(CAPE), and satellite datasets. Similar forecast biases were found:over-forecasted light rain and under-forecasted heavy rain. Long-termanalyses revealed an increasing trend in heavy rain in summer and adecreasing trend in light rain in other seasons, accompanied by a decreasingtrend in visibility, no trend in water vapor, and a slight increasing trendin summertime CAPE. More aerosols decreased cloud effective radii for caseswhere the liquid water path was greater than 100 g m<sup>−2</sup>. All findingsare consistent with the effects of ACI, i.e., where aerosols inhibit thedevelopment of shallow liquid clouds and invigorate warm-base mixed-phaseclouds (especially in summertime), which in turn affects precipitation. Whilewe cannot establish rigorous causal relations based on the analyses presentedin this study, the significant rainfall forecast bias seen in operationalweather forecast model simulations warrants consideration in future modelimprovements

Potential influences of neglecting aerosol effects on the NCEP GFS precipitation forecast