Digital twinUS & West
Physics-Informed Neural Networks for Climate-Aware Digital Twins
This study evaluates a physics-informed neural network for potential-temperature forecasting under incomplete thermal observations, constrained by a pressure-coordinate advection-source equation and a diabatic-source closure frozen after the preceding 12 hours. Validation uses hourly ERA5 reanalysis at three pressure levels for one-, two- and three-hour horizons against persistence, local-trend, and two neural baselines.