A Multi‐Model Ensemble Kalman Filter for Data Assimilation and Forecasting
A Multi‐Model Ensemble Kalman Filter for Data Assimilation and Forecasting
Abstract Data assimilation (DA) aims to optimally combine model forecasts and observations that are both partial and noisy. Multi‐model DA generalizes the variational or Bayesian formulation of the Kalman filter, and we prove that it is also the minimum variance linear unbiased estimator. Here, we formulate and implement a multi‐model …