The output of ground-based, solar power generation systems is strongly dependent on cloud cover, which is the main contributor to solar power variability and uncertainty. Cloud optical properties are typically over-simplified in forecasting applications due to the lack of real-time, accurate estimates. In this work, we introduce a method, the Spectral Cloud Optical Property Estimation (SCOPE), for estimating cloud optical properties directly from high-resolution (5-min, 2 km) imagery from Geostationary Operational Environmental Satellite (GOES)-R, which is the newest generation of the GOES system. The SCOPE method couples a two-stream, spectrally resolved radiative model with the longwave GOES-R sensor output to simultaneously estimate the cloud optical depth, cloud top height, and cloud thickness during both day and night at 5-min intervals. The accuracy of SCOPE is evaluated using one year (2018) of downwelling longwave (DLW) radiation measurements from the Surface Radiation Budget Network, which consists of seven sites spread across climatically diverse regions of the contiguous United States. During daytime clear-sky periods, SCOPE predicts DLW within instrument uncertainty (10 W m−2) for four of the seven locations, with the remaining locations yielding errors of the order of 11.2, 17.7, and 20.2 W m−2. For daytime cloudy-sky, daytime all-sky (clear or cloudy), and nighttime all-sky periods, SCOPE achieves root mean square error values of 23.0–34.5 W m−2 for all seven locations. These results, together with the low-latency of the method (∼1 s per sample), show that SCOPE provides a viable solution to real-time, accurate estimation of cloud optical properties for both day and night.
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SCOPE: Spectral cloud optical property estimation using real-time GOES-R longwave imagery
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March 2020
Research Article|
April 14 2020
SCOPE: Spectral cloud optical property estimation using real-time GOES-R longwave imagery
David P. Larson
;
David P. Larson
1
Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, Center for Energy Research Center for Excellence in Renewable Resources and Integration, University of California San Diego
, La Jolla, California 92093-0411, USA
2
Electric Power Research Institute
, Palo Alto, California 94304, USA
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Mengying Li
;
Mengying Li
1
Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, Center for Energy Research Center for Excellence in Renewable Resources and Integration, University of California San Diego
, La Jolla, California 92093-0411, USA
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Carlos F. M. Coimbra
Carlos F. M. Coimbra
a)
1
Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, Center for Energy Research Center for Excellence in Renewable Resources and Integration, University of California San Diego
, La Jolla, California 92093-0411, USA
a)Author to whom correspondence should be addressed: [email protected]
Search for other works by this author on:
David P. Larson
1,2
Mengying Li
1
Carlos F. M. Coimbra
1,a)
1
Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering, Center for Energy Research Center for Excellence in Renewable Resources and Integration, University of California San Diego
, La Jolla, California 92093-0411, USA
2
Electric Power Research Institute
, Palo Alto, California 94304, USA
a)Author to whom correspondence should be addressed: [email protected]
J. Renewable Sustainable Energy 12, 026501 (2020)
Article history
Received:
December 28 2019
Accepted:
March 16 2020
Citation
David P. Larson, Mengying Li, Carlos F. M. Coimbra; SCOPE: Spectral cloud optical property estimation using real-time GOES-R longwave imagery. J. Renewable Sustainable Energy 1 March 2020; 12 (2): 026501. https://doi.org/10.1063/1.5144350
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