Mitigating Masked Pixels in a Climate-Critical Ocean Dataset
Angelina Agabin,
J. Xavier Prochaska,
Peter C. Cornillon
et al.
Abstract:Clouds and other data artefacts frequently limit the retrieval of key variables from remotely sensed Earth observations. We train a natural language processing (NLP)-inspired algorithm with high-fidelity ocean simulations to accurately reconstruct masked or missing data in sea surface temperature (SST) fields—one of 54 essential climate variables identified by the Global Climate Observing System. We demonstrate that the resulting model, referred to as Enki, repeatedly outperforms previously adopted inpainting … Show more
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