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

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.

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Publication Details

Journal
Remote Sensing
Published
2025-08-14
DOI
https://doi.org/10.3390/rs17162829
Citations
2
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
2.21

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article

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

Xiangao Xia, Husi Letu, Cuina Li, Su Wang et al.
2 citations
Remote Sensing
Atmospheric aerosols and clouds
2.21
article

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

Xiangao Xia, Husi Letu, Cuina Li, Su Wang, Run Ma, Tie Dai
article en
2 citations

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.

Remote SensingVol. 17(16)
China Meteorological Administration (CN), Chinese Academy of Sciences (CN), Nanjing University of Information Science and Technology (CN), Yibin University (CN), Aerospace Information Research Institute (CN), Institute of Atmospheric Physics (CN), University of Chinese Academy of Sciences (CN), State Key Laboratory of Remote Sensing Science (CN), Sichuan University of Science and Engineering (CN)
Social Science Research Council, National Natural Science Foundation of China, Natural Science Foundation of Sichuan Province, National Key Research and Development Program of China
Openalex Percentile: Top 12%
Atmospheric aerosols and clouds
2.21
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