Optical Flow derived winds from overlapping LEO granules
Project description
windflow_leo
A package for deriving atmospheric winds from overlapping granules of satellites in a LEO (low earth orbit) train formation, using dense feature tracking of CrIS retrievals of specific humidity (JPSS) or AVHRR imagery (MetOp).
This package runs inference on a pre-trained model based on WindFlow: Dense feature tracking of atmospheric winds with deep optical flow:
Vandal, T., Duffy, K., McCarty, W., Sewnath, A., & Nemani, R. (2022). Dense feature tracking of atmospheric winds with deep optical flow, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
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