Quantifying daily aerosol direct radiative effects in mainland China using a weather-aerosol normalized machine learning framework based on observational data, 1993−2020

Abstract. Aerosol direct radiative effect (ADRE) is a key component of the Earth’s radiation budget, yet its spatiotemporal variability and sensitivity to meteorological conditions remain insufficiently constrained across China. Here, we quantify daily ADRE at 72 radiation stations from 1993 to 2020 using a weather-aerosol normalization (WAN) machine learning framework, and examine its spatial pattern, seasonal cycle, and sensitivity to aerosol optical depth (AOD) and environmental factors. Physical consistency of the framework is validated at over 98% of stations via SHapley Additive exPlanations (SHAP) analysis. The nationwide daily mean ADRE is -0.761 MJ m⁻² (-8.81 W m⁻²), with strongest cooling in the Southern region (-0.904 MJ m⁻², -10.46 W m⁻²) and weakest in the Tibetan Plateau (-0.187 MJ m⁻², -2.16 W m⁻²). Seasonally, spring hosts the most peak-ADRE stations (50.7% of stations), whereas summer dominates regional mean intensity in northern, northwestern, and Tibetan Plateau regions; southern China remains strong year-round. The ADRE sensitivity to AOD spans -8.63 to -0.43 MJ m⁻² per unit AOD (highest in northwest China under frequent clear skies, dust aerosols, and high surface albedo), with negative AOD–ADRE correlations at all stations (median −0.66). Sensitivity peaks under clear skies (59.7% of stations) and low humidity, where cloud-shielding effects are minimal. Notably, positive ADRE events (1.4%-51.7%) occur preferentially at low AOD rather than high humidity, reflecting baseline-definition artifacts (AOD ≤ seasonal 5th percentile) and reduced signal-to-noise under clean backgrounds. This observationally constrained benchmark delineates dominant controls on daily ADRE and supports aerosol radiative forcing assessment in China.