The Weather4cast competition presented at NeurIPS 2023 focuses on topics of high impact and practical value for our society – predicting future weather and changes of our environment. Unusual weather is increasing all over the world, reflecting ongoing climate change, and affecting communities in agriculture, transport, public health and safety, etc.

Can you predict future rain patterns with modern machine learning algorithms? Apply spatio-temporal modelling to complex dynamic systems! Get access to unique large-scale data and demonstrate temporal and spatial transfer learning under strong distributional shifts! We provide a super-resolution challenge of high relevance to forecasting unusual local events, where you need to predict future weather as measured by ground-based hi-res rain radar weather stations. Exploit data fusion of high-resolution rain radar maps movies combined, large-scale multi-band satellite images, and static information like topology!

Winning models will advance key areas of methods research in machine learning, of relevance beyond the application domain. The authors of competitive submissions will be invited to present at the NeurIPS Competition Track (virtual) and contribute to a joint article in the NeurIPS Datasets and Benchmark Proceedings.

This year, besides data fusion, super-resolution, and generalization performance, we move from classification to zero-inflated regression. The 2023 challenge is to predict quantitative hi-res rain radar movies from lo-res multi-channel spectral satellite images in a highly unbalanced data scenario.

Sign up to the forums to stay in the loop!