Learning joint probabilistic weather forecasts from station observations alone
CLARA learns joint Gaussian predictive distributions for five surface variables using only station observations, ignoring external weather models. It uses an attention mechanism with advection-routing to capture spatial dependencies and predicts both the mean and covariance structure. This method outperforms traditional statistical models and other learned AI models in forecasting accuracy.