Sparse-Observation Atmospheric Thermal Forecasting with Physics-Informed Neural Networks for Climate-Aware Digital Twins

arXiv:2609.27290 · cs.AI, cs.NA, math.AP, math.NA · Submitted 2026-09-23 · Read on arXiv

cs.AI, cs.NA, math.AP, math.NA

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/Tannaz-Chegini/pinn-atmospheric-heat-transfer

Terminology

• Robustness — 8× in this paper · explained in 5 episodes
• Digital Twin — 7× in this paper · explained in 4 episodes
• Inverse Problem — 4× in this paper · explained in 2 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• PDE residual — 3× in this paper · explained in 2 episodes
• Sparsity — 3× in this paper · explained in 4 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Physical Constraints — 2× in this paper · explained in 7 episodes
• Physics-Informed Constraints — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptive Weighting — 1× in this paper · explained in 1 episode
• Embeddings — 1× in this paper · explained in 2 episodes
• European Centre for MediumRange Weather Forecasts — 1× in this paper
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Physics-Informed Neural Network (PINN) — 1× in this paper · explained in 3 episodes
• Physics-Informed Neural Networks (PINNs) — 1× in this paper · explained in 6 episodes
• Transferability — 1× in this paper · explained in 4 episodes

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