# EnsAI

Ammonia emissions inversions rely on ensembles to carry meteorology-dependent error covariances, but each ensemble means repeatedly running the GEM-MACH chemistry model. EnsAI replaces that with a U-Net that maps ammonia emissions perturbations plus temperature and wind fields directly to surface concentration perturbations, producing a week of simulated data per member in 7 seconds against roughly 6.5 hours for GEM-MACH on 720 nodes. Inversions using the EnsAI ensemble gave annual total emissions 2.6% lower than the GEM-MACH ensemble inversions, with monthly totals within 10% for every month.

Ammonia emissions inversions rely on ensembles to carry meteorology-dependent error covariances, but each ensemble means repeatedly running the GEM-MACH chemistry model. EnsAI replaces that with a U-Net that maps ammonia emissions perturbations plus temperature and wind fields directly to surface concentration perturbations, producing a week of simulated data per member in 7 seconds against roughly 6.5 hours for GEM-MACH on 720 nodes. Inversions using the EnsAI ensemble gave annual total emissions 2.6% lower than the GEM-MACH ensemble inversions, with monthly totals within 10% for every month.