A causal understanding of climatic interactions is of high societal relevance from identifying causes of extreme events to process understanding and weather forecasting. This competition comprises a number of multivariate time series datasets featuring major challenges of climate data from time delays and nonlinearity to nonstationarity and selection bias. The competition aims to open up new interdisciplinary research pathways by improving our scientific understanding of Earth’s climate, while also driving method development and benchmarking in the computer science community.
This NeurIPS challenge is co-organized by people from our Climate Informatics Group together with the Image and Signal Processing Group from the University of Valencia (Spain).
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