Ensemble Kalman Filter

The Ensemble Kalman Filter is a statistical method used to estimate the true state of a system—like weather conditions—by combining predictions with new observations. It uses multiple simulations (called an ensemble) to represent possible states, updating these with actual measurements to refine accuracy. This process helps manage uncertainty and provides more reliable estimates, especially in complex, dynamic systems. Essentially, it’s a sophisticated way to improve forecasts by continuously blending model predictions with real-world data, ensuring the estimates stay as close to reality as possible.