Workshop: Tackling Climate Change with Machine Learning

Nowformer : A Locally Enhanced Temporal Learner for Precipitation Nowcasting

Jinyoung Park · Inyoung Lee · Minseok Son · Seungju Cho · Changick Kim


The precipitation video datasets have distinctive meteorological patterns where a mass of fluid moves in a particular direction across the entire frames, and each local area of the fluid has an individual life cycle from initiation to maturation to decay. This paper proposes a novel transformer-based model for precipitation nowcasting that can extract global and local dynamics within meteorological characteristics. The experimental results show our model achieves state-of-the-art performances on the precipitation nowcasting benchmark.

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