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Key Points:• Total cloud cover from various methods is in 65-85% within ±1 okta• Sky camera overestimates cloudiness with respect to other automatic methods • Clouds can be correctly classified in 50-90% of cases using sky cameras Supporting Information:• Figure S1 • Movie S1 Abstract We present observations of total cloud cover and cloud type classification results from a sky camera network comprising four stations in Switzerland. In a comprehensive intercomparison study, records of total cloud cover from the sky camera, long-wave radiation observations, Meteosat, ceilometer, and visual observations were compared. Total cloud cover from the sky camera was in 65-85% of cases within ±1 okta with respect to the other methods. The sky camera overestimates cloudiness with respect to the other automatic techniques on average by up to 1.1 ± 2.8 oktas but underestimates it by 0.8 ± 1.9 oktas compared to the human observer. However, the bias depends on the cloudiness and therefore needs to be considered when records from various observational techniques are being homogenized. Cloud type classification was conducted using the k-Nearest Neighbor classifier in combination with a set of color and textural features. In addition, a radiative feature was introduced which improved the discrimination by up to 10%. The performance of the algorithm mainly depends on the atmospheric conditions, site-specific characteristics, the randomness of the selected images, and possible visual misclassifications: The mean success rate was 80-90% when the image only contained a single cloud class but dropped to 50-70% if the test images were completely randomly selected and multiple cloud classes occurred in the images.

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International audienceNowcasting of high resolution maps of direct normal irradiance (DNI) is of interest to efficiently operate Concentrated Solar Power plants. The paper presents a state-of-the-art and innovative methodology, developed in the framework of the FP7 DNICast project, to derive nowcasting of DNI maps from fish-eye cameras in stereoscopic mode. This methodology has been applied at the Plataforma Solar de Almeria: fish-eye cameras at distances from each other between 500 m and 900 m have been used in stereoscopic mode to produce nowcasted 1-min time series of decametric DNI maps

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