Feature-Informed Data Assimilation -- Definitions and Illustrative Examples

2022/11/01 by Wei Kang, Daniel M. Tartakovsky, Kang, Wei +3
Earth and Planetary Sciences · Engineering · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Electrical engineering #FOS: Mathematics #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks #Reservoir Engineering and Simulation Methods #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2211.00256

openalex publication_date 2022/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We introduce a mathematical formulation of feature-informed data assimilation (FIDA). In FIDA, the information about feature events, such as shock waves, level curves, wavefronts and peak value, in dynamical systems are used for the estimation of state variables and unknown parameters. The observation operator in FIDA is a set-valued functional, which is fundamentally different from the observation operators in conventional data assimilation. Demonstrated in three example, FIDA problems introduced in this note exist in a wide spectrum of applications in science and engineering.

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