GraphAT Net: A Deep Learning Approach Combining TrajGRU and Graph Attention for Accurate Cumulonimbus Distribution Prediction
Ting Zhang,
Soung-Yue Liew,
Hui-Fuang Ng
et al.
Abstract:In subtropical regions, heavy rains from cumulonimbus clouds can cause disasters such as flash floods and mudslides. The accurate prediction of cumulonimbus cloud distribution is crucial for mitigating such losses. Traditional machine learning approaches have been used on radar echo data generated by constant altitude plan position indicator (CAPPI) radar systems for predicting cumulonimbus cloud distribution. However, the results are often too foggy and fuzzy. This paper proposes a novel approach that integra… Show more
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