Deep learning for multi-year ENSO forecasts

By Y. Ham, Jeong-Hwan Kim, Jing Luo. Nature, 2019

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How researchers see this paper

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Earthformer: Exploring Space-Time Transformers for Earth System Forecasting (2022, methodology): “Such technique has demonstrated success in several applications, including precipitation nowcasting [30, 6] and ENSO forecasting [15].”
Deep-learning-based information mining from ocean remote-sensing imagery (2020, background): “In very recent times, a deep-learning model has successfully made skillful forecasts of El Niño/Southern Oscillation, showing great potential in solving this complex scientific problem [24].”
WeatherBench: A Benchmark Data Set for Data‐Driven Weather Forecasting (2020, methodology): “sk or dataset, for example, climate model simulations, and then ﬁnetuned on the actual data. This is common practice in computer vision and has been successfully applied to seasonal ENSO forecasting (Ham et al., 2019). Another common method to prevent overﬁtting is data augmentation, which in tradit”