A LIM-LSTM hybrid model improves ENSO forecast skill in the low-data regime by learning the nonlinear residual of a linear inverse model, capturing warm-cold asymmetry at long leads.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A Hybrid Deep-Learning Model for El Ni\~no Southern Oscillation in the Low-Data Regime
A LIM-LSTM hybrid model improves ENSO forecast skill in the low-data regime by learning the nonlinear residual of a linear inverse model, capturing warm-cold asymmetry at long leads.