Definition of Term: Data Assimilation

Data assimilation is a term that is widely used in the context of using observations of the real-world process to update a simulator. It generally applies to a dynamic simulator that models a real-world process that is evolving in time. At each time step, the simulator simulates the current state of the system as expressed in the state vector. In data assimilation, observation of the real-world process at a given time point is used to learn about the true status of the process and hence to adjust the state vector of the simulator. Then the simulator’s next time step starts from the adjusted state vector, and should therefore predict the system state better at subsequent time steps.

Data assimilation is thus also a dynamic process. It is similar to calibration in the sense that it uses real-world observations to learn about simulator parameters, but the term calibration is generally applied to imply a one-off learning about fixed parameters/inputs.