Precipitation Nowcasting

PreDiff: Precipitation Nowcasting with Latent Diffusion Models

We introduce a two-stage pipeline for probabilistic precipitation nowcasting. 1) We develop a latent diffusion model PreDiff. (2) We incorporate an auxiliary knowledge alignment mechanism, allowing the integration of domain expertise.

Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle Robinson, Yi Zhu, Mu Li, Yuyang Wang

PreDiff: Precipitation Nowcasting with Latent Diffusion Models

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

We propose Earthformer with novel generic building blocks “Cuboid Attention” to explore the design of space-time attention for Earth system forecasting problems, and achieve SOTA performance on two synthetic datasets and two real-world benchmarks.

Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

Deep Learning and the Weather Forecasting Problem: Precipitation Nowcasting

Precipitation nowcasting refers to the prediction of rainfall with high spatiotemporal resolutions in a timely and accurate manner for …

Zhihan Gao, Xingjian Shi, Hao Wang, Dit-Yan Yeung, Wang-chun Woo, Wai-Kin Wong

Deep Learning and the Weather Forecasting Problem: Precipitation Nowcasting

Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model

We propose Earthformer with novel generic building blocks “Cuboid Attention” to explore the design of space-time attention for Earth system forecasting problems, and achieve SOTA performance on two synthetic datasets and two real-world benchmarks.

Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo