Atrial Fibrillation (AF) is one of the most common sustained arrhythmia, which can increase the risk of heart failure and stroke. Understanding the complex electrical dynamics of AF and correctly targeting AF sources for ablation therapies remain challenging in clinical practice. This is due to the incapability to reconstruct the electrical dynamic of AF, and lack of efficient approach for AF source identification. This paper builds a multi-sale framework for modeling of the abnormal electrical propagation in AF initiated by triggers from Pulmonary Veins (PVs). A new algorithm is developed to detect the propagating direction of electrical wavefronts. The detection algorithm is further validated using modeling results. The developed multi-scale framework and the detection algorithm will contribute to AF diagnosis and potentially improve the treatment outcomes of AF ablations.