Short-term prediction of localized cloud motion using ground-based sky imagers
This work addresses the need for fine-scale cloud motion prediction to improve solar energy generation and satellite communications, but it is incremental as it applies existing optical flow methods to a specific domain.
The paper tackled the problem of predicting short-term, localized cloud motion in tropical regions like Singapore using ground-based sky imagers, achieving good prediction accuracy for up to 5 minutes lead time.
Fine-scale short-term cloud motion prediction is needed for several applications, including solar energy generation and satellite communications. In tropical regions such as Singapore, clouds are mostly formed by convection; they are very localized, and evolve quickly. We capture hemispherical images of the sky at regular intervals of time using ground-based cameras. They provide a high resolution and localized cloud images. We use two successive frames to compute optical flow and predict the future location of clouds. We achieve good prediction accuracy for a lead time of up to 5 minutes.