Using GEOS-5 forecast products to represent aerosol optical depth in operational day-ahead solar irradiance forecasts for the southwest United States
Publisher
AMER INST PHYSICSCitation
Bunn, P. T., Holmgren, W. F., Leuthold, M., & Castro, C. L. (2020). Using GEOS-5 forecast products to represent aerosol optical depth in operational day-ahead solar irradiance forecasts for the southwest United States. Journal of Renewable and Sustainable Energy, 12(5), 053702.Rights
© 2020 Author(s).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
This study aims to improve operational day-ahead direct normal irradiance (DNI) forecasts in clear-sky conditions using the Weather and Research Forecasting model. To create three different forecasting methods targeting the direct effect of aerosols on radiation, we use three different types of aerosol optical depth (AOD) data: (1) the Tegen aerosol climatology, (2) the persistence of measured AERONET AOD, and (3) the Goddard Earth Observing System model version 5 (GEOS-5) gridded forecasts of AOD. We evaluate each method at the Solana Generating Station, a concentrating solar power plant near Gila Bend, Arizona, and the University of Arizona, Tucson. We perform a retrospective DNI forecast analysis and find that including GEOS-5 forecast AOD improved the DNI forecast compared to using an aerosol climatology at both locations. At Tucson, where AOD is measured, we find that the persistence of measured AOD gives the best DNI forecast. However, the accuracy of that measured AOD reduces when translating it 225 km to Solana to forecast DNI 48 hours later. We then include the GEOS-5 AOD forecasts in one member of an operational forecast system and evaluate it against the other ensemble members that use the aerosol climatology. In clear-sky conditions, including GEOS-5 forecast AOD instead of the Tegen aerosol climatology, reduces the DNI forecast root mean square error by 27% at Solana. We found no significant differences during all-sky conditions because the relatively poor performance during cloudy conditions outweighs the improvements made in clear-sky conditions. Published under license by AIP Publishing.Note
12 month embargo; first published online 18 September 2020ISSN
1941-7012EISSN
1941-7012Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1063/5.0020785