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Maria J. Molina
,
Travis A. O’Brien
,
Gemma Anderson
,
Moetasim Ashfaq
,
Katrina E. Bennett
,
William D. Collins
,
Katherine Dagon
,
Juan M. Restrepo
, and
Paul A. Ullrich

.g., Ham et al. 2019 ; Mayer and Barnes 2021 ; Martin et al. 2022 ; Gordon and Barnes 2022 ). For example, Ham et al. (2019) trained a convolutional neural network to predict ENSO at lead times beyond 1 yr with skill that exceeds state-of-the-art dynamical forecast models. Mayer and Barnes (2021) predicted the sign of geopotential height anomalies on subseasonal time scales (i.e., from 2 weeks to 2 months) using an artificial neural network (ANN). These studies also went beyond generating

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