ELIFAN, an algorithm for the estimation of cloud cover from skyimagers

Abstract. In the context of an atmospheric network of multi-instrumented sites equipped with skycamera for cloud monitoring, we present an algorithm named ELIFAN which aims at estimating the cloud coveramount from full skyvisible daytime images with a common principle and procedure. ELIFAN was initially developped for a self-made full skyimage 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 skypixels of the image, and on the use of a blue skylibrary. Both an absolute (without use of reference image) and a differential (based on a blue skyreference 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 sunriseand sunsettransitions. 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 skyat 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/ sunsetperiods and in some specific conditions. The use of the clear skylibrary gives generally better results than the absolute process. Especially, it better detects the thin cirrusclouds. But the absolute thresholdingprocess turns out to be sometimes better, for example in fully cloudy skies. The combination of pyranometer, ceilometerand skycamera illustrates the performance of ELIFAN, and reveals the comple-mentarity of the three instruments. We especially show that a similar cloud coveramount is deduced from both the skyimager and the ceilometerwhen the clouds are low (below 3 km). But they can lead to significantly different cloud coverestimates when the clouds are high. In this case, we find that the skyimager catches more appropriately the cloud coverestimate, due to its 2D integrated point of view and to the loss of sensitivity of the ceilometerabove 7 km.