Review for NeurIPS paper: SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology

Four knowledgeable reviewers all appreciated the contributions of this paper and rated it as above the bar for publication at NeurIPS. Reviewers acknowledged that the primary contribution was the curation of a dataset and benchmark tasks on the data set, and not novel methods, but felt that the curation of a large, high-quality data set for real tasks in atmospheric/earth sciences is important and could spur AI work in this area. The authors deserve credit for this. Additionally, the reviewers appreciated that the baseline methods developed for the benchmark tasks were themselves thoughtful and significant, if not highly novel from a methods perspective. The reviewers asked a number of questions about justification and details of the data set construction, evaluation metrics, and baselines.