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Contrails (condensation trails) are line-shaped ice clouds caused by aircraftand are likely the largest contributor of aviation-induced climate change.Contrail avoidance is potentially an inexpensive way to significantly reducethe climate impact of aviation. An automated contrail detection system is anessential tool to develop and evaluate contrail avoidance systems. In thispaper, we present a human-labeled dataset named OpenContrails to train andevaluate contrail detection models based on GOES-16 Advanced Baseline Imager(ABI) data. We propose and evaluate a contrail detection model thatincorporates temporal context for improved detection accuracy. The humanlabeled dataset and the contrail detection outputs are publicly available onGoogle Cloud Storage at gs://goes_contrails_dataset.

OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI