ELIFAN, an algorithm for the estimation of cloud cover from sky imagers

Abstract. In the context of an atmospheric network of multi-instrumented sites equipped with sky camera for cloud monitoring, we present an algorithm named ELIFAN which aims at estimating the cloud cover amount from full sky visible daytime images with a common principle and procedure. ELIFAN was initially developped for a self-made full sky image system presented in this article, and adapted to a set of other systems in the network. It is based on red over blue ratio thresholding for the distinction of cloudy and clear sky pixels of the image, and on the use of a blue sky library. Both an absolute (without use of reference image) and a differential (based on a blue sky reference image) red/blue ratio thresholding are used. An evaluation of the algorithm based on a one-year long series of images shows that the proposed algorithm is very convincing for most of the images, with more than 95 % of relevance in the process, outside the sunrise and sunset transitions. During those latter periods though, ELIFAN has large difficulties to appropriately process the image, due to a drastic difference of color composition and a potential confusion between clear and cloudy sky at that time. The two thresholding methodologies, the absolute and the differential red/blue ratio thresholding processes, agree very well with departure usually below 8 %, except in sunrise/sunset periods and in some specific conditions. The use of the clear sky library gives generally better results than the absolute process. Especially, it better detects the thin cirrus clouds. But the absolute thresholding process turns out to be sometimes better, for example in fully cloudy skies. The combination of pyranometer, ceilometer and sky camera illustrates the performance of ELIFAN, and reveals the comple-mentarity of the three instruments. We especially show that a similar cloud cover amount is deduced from both the sky imager and the ceilometer when the clouds are low (below 3 km). But they can lead to significantly different cloud cover estimates when the clouds are high. In this case, we find that the sky imager catches more appropriately the cloud cover estimate, due to its 2D integrated point of view and to the loss of sensitivity of the ceilometer above 7 km.