3 papers
physics.ao-ph2025
Knowledge-guided machine learning for disentangling Pacific sea surface temperature variability across timescales
Kyle J. C. Hall, Maria J. Molina, Emily F. Wisinski +2
Global weather and climate patterns are strongly influenced by dominant modes of anomalous Pacific sea surface temperature (SST) variability, including the El Niño-Southern Oscilla…
cs.LG2024
A Hybrid Deep-Learning Model for El Niño Southern Oscillation in the Low-Data Regime
Jakob Schloer, Matthew Newman, Jannik Thuemmel +2
While deep-learning models have demonstrated skillful El Niño Southern Oscillation (ENSO) forecasts up to one year in advance, they are predominantly trained on climate model simul…
physics.ao-ph2024
Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction
Zijie Guo, Pumeng Lyu, Fenghua Ling +8
Accurate ocean dynamics modeling is crucial for enhancing understanding of ocean circulation, predicting climate variability, and tackling challenges posed by climate change. Despi…