UC San Diego

Many solar forecast algorithms based on ground based sky imagery apply

the red-blue ratio (RBR) method to classify image pixels as clear or cloudy, by

comparing the current image with the corresponding image from a clear sky

library (CSL). The CSL needs to be updated regularly due to change in clear sky

conditions over time caused by aerosols and imager dome properties. This clear

sky library is typically created by visually scrutinizing daily sky videos and

selecting appropriate clear sky periods. This practice takes a significant amount of

time and manual intervention can result in human errors. To avoid this, an

automated CSL algorithm (ACSL) was developed which filters each image for clear

sky features such as maximum green pixel brightness, average RBR, and red

channel difference. The relative root mean square error (RMSE) between the

image RBR of the manually created CSL and the one created using ACSL for

November 2013 at UC San Diego was observed to be less than 5% over the range

of solar zenith angles and it was found to be more representative of clear

conditions than its manual counterpart.