OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI

Joe Yue-Hei Ng; Kevin McCloskey; Jian Cui; Vincent R. Meijer; Erica Brand; Aaron Sarna; Nita Goyal; Christopher Van Arsdale; Scott Geraedts

arXiv · 2304.02122

OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI

Joe Yue-Hei Ng·Kevin McCloskey·Jian Cui·Vincent R. Meijer·Erica Brand·Aaron Sarna·Nita Goyal·Christopher Van Arsdale·Scott Geraedts

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Abstract

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

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Joe Yue-Hei Ng, Kevin McCloskey, Jian Cui, Vincent R. Meijer, Erica Brand, Aaron Sarna, Nita Goyal, Christopher Van Arsdale, Scott Geraedts. 2023-04-04. OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI. https://arxiv.org/abs/2304.02122

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