Online-Coupled Aerosol Effects on Cloud Microphysics and Surface Solar Irradiance in WRF-Solar

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Abstract
The online coupling of aerosols and clouds and its effect on surface global horizontal irradiance (GHI) has not yet been thoroughly investigated in the Weather Research and Forecasting Model with Solar extensions (WRF-Solar), despite its potential significance for solar energy applications. This study addresses this critical gap by implementing a computationally efficient, coupled aerosol–cloud scheme and evaluating its impacts on GHI predictability. Simulations with online aerosol–cloud coupling are systematically compared to uncoupled simulations during March 2021, a period marked by two distinct pollution episodes over north China. The online coupling enhances aerosol optical depth (AOD) simulations, increasing the correlation coefficient from 0.19 to 0.51 while reducing the absolute bias from 0.54 to 0.48 and root mean square error from 0.82 to 0.72, compared to uncoupled simulations. Enhanced cloud microphysics (droplet concentration, water path) yields better cloud optical depth estimates, reducing all-sky GHI bias by 14.5% (63.5 W/m2 for the uncoupled scenario and 54.3 W/m2 for the coupled scenario) through improved aerosol–cloud–meteorology interactions. Notably, the simultaneous spatiotemporal improvement of both AOD and GHI suggests enhanced internal consistency in aerosol–cloud–radiation interactions, which is crucial for operational solar irradiance forecasting in pollution-prone regions. The results also highlight the practical value of incorporating online aerosol coupling in solar forecasting models.
Funding Information
  • National Natural Science Foundation of China (42305202, 42141019, 42261144687, 42430611, 42405145, 2024RYY03, 2024YFB3908701, 2024NSFSC0770)
  • Intelligent Perception and Control Key Laboratory of Sichuan Province (42305202, 42141019, 42261144687, 42430611, 42405145, 2024RYY03, 2024YFB3908701, 2024NSFSC0770)
  • National Key Research and Development Program of China (42305202, 42141019, 42261144687, 42430611, 42405145, 2024RYY03, 2024YFB3908701, 2024NSFSC0770)
  • Natural Science Foundation of Sichuan Province (42305202, 42141019, 42261144687, 42430611, 42405145, 2024RYY03, 2024YFB3908701, 2024NSFSC0770)

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