Articles | Volume 16, issue 5
https://doi.org/10.5194/acp-16-3399-2016
https://doi.org/10.5194/acp-16-3399-2016
Research article
 | 
15 Mar 2016
Research article |  | 15 Mar 2016

Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

Thomas Schmidt, John Kalisch, Elke Lorenz, and Detlev Heinemann

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Cited articles

Bernecker, D., Riess, C., Angelopoulou, E., and Hornegger, J.: Continuous short-term irradiance forecasts using sky images, Sol. Energy, 110, 303–315, https://doi.org/10.1016/j.solener.2014.09.005, 2014.
Blanc, P. and Wald, L.: A Library for Computing the Relative Position of the Sun and the Earth, Tech. rep., GMES, Paris, France, 2011.
Bouguet, J.-Y.: Pyramidal implementation of the affine lucas kanade feature tracker description of the algorithm, Intel Corporation, 5, 1–10, 2001.
Bourges, B. D.: Yearly variations of the Linke turbidity factor, in: Climatic Data Handbook of Europe, Kluwer Academic Publishing, Dordrecht, the Netherlands, 61–64, 1992.
Cazorla, A.: Development of a Sky Imager for Cloud Classification and Aerosol Characterization, PhD thesis, Universidad de Granada, Granada, Spain, 2010.
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Short summary
We performed an irradiance forecast experiment based on analysis of hemispheric sky images and evaluated results on a large data set of 99 pyranometers distributed over 10 × 12 km. We developed a surface irradiance retrieval from cloud information derived from the images. Very high resolution forecasts were processed up to 25 min. A main finding is that forecast skill is enhanced in complex cloud conditions leading to high variability in surface irradiance.
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