Moving beyond the Aerosol Climatology of WRF-Solar: A Case Study over the North China Plain
- Harbin Institute of Technology (China)
- Chinese Academy of Sciences (CAS), Beijing (China)
- Chengdu University of Information Technology (China)
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Univ. of North Carolina, Charlotte, NC (United States)
Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. Here, in this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m-2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m-2, the overestimation of the global radiation still reaches 160.2 W m-2. This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-76RL01830
- OSTI ID:
- 2552941
- Report Number(s):
- PNNL-SA-194527
- Journal Information:
- Weather and Forecasting, Journal Name: Weather and Forecasting Journal Issue: 5 Vol. 39; ISSN 0882-8156
- Publisher:
- American Meteorological SocietyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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