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Cite Details

A. Srivastava, W. Kang and D. M. Tartakovsky, "Feature-informed data assimilation", J. Comput. Phys., vol. 493, doi:10.1016/, pp. 112499, 2023


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 that involves a search process over a function of state variables, which is fundamentally different from the observation operators in conventional data assimilation. We present three numerical experiments, in which shocks and expanding waves are observed features. These examples serve to demonstrate FIDA's ability to estimate model parameters from such noisy observations.

BibTeX Entry

author = {A. Srivastava and W. Kang and D. M. Tartakovsky},
title = {Feature-informed data assimilation},
year = {2023},
urlpdf = {},
journal = {J. Comput. Phys.},
volume = {493},
doi = {10.1016/},
pages = {112499}