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grid (about 200 km). On longer climate time scales (decades to centuries), Dagon et al. (2022) detected weather fronts (e.g., cold, warm, occluded, and stationary fronts) using a convolutional neural network and then quantified their association with extreme precipitation over North America along with projected changes in a future climate; thus, feature detection was used to extract precursors to extreme precipitation events. Skillful ML-based prediction of weather and climate has garnered broad
grid (about 200 km). On longer climate time scales (decades to centuries), Dagon et al. (2022) detected weather fronts (e.g., cold, warm, occluded, and stationary fronts) using a convolutional neural network and then quantified their association with extreme precipitation over North America along with projected changes in a future climate; thus, feature detection was used to extract precursors to extreme precipitation events. Skillful ML-based prediction of weather and climate has garnered broad
