Two-pathway spatiotemporal representation learning for extreme water temperature prediction

Jinah Kim, Taekyung Kim, Jaeil Kim

Abstract: Highlights•Development of two-pathway spatiotemporal representation learning framework for consecutive multi-step-ahead SST prediction.•Spatiotemporal representation learning to capture the temporally correlated regional to local spatial dependencies.•Notable predictability of extreme coastal SST for consecutive 7-day ahead spatiotemporal forecasts.•Visualization of attention map to secure domain knowledge-based validity and explainability of model predictions.•Discovering spatiotemporal teleconnections of SST variability and its consistency with ocean dynamics.