Computer Science Technical Reports
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A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation. I: Methodology

Sandu, Adrian and Singh, Kumaresh and Jardak, Mohamed and Bowman, Kevin and Lee, Meemong (2012) A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation. I: Methodology. Technical Report TR-12-13, Computer Science, Virginia Tech.

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Data assimilation obtains improved estimates of the state of a physical system by combining imperfect model results with sparse and noisy observations of reality. all observations used in data assimilation are equally valuable. The ability to characterize the usefulness of different data points is important for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future sensor systems. This paper focuses on the four dimensional variational (4D-Var) data assimilation framework. Metrics from information theory are used to quantify the contribution of observations to decreasing the uncertainty with which the system state is known. We establish an interesting relationship between different information-theoretic metrics and the variational cost function/gradient under Gaussian linear assumptions. Based on this insight we derive an ensemble-based computational procedure to estimate the information content of various observations in the context of 4D-Var. The approach is illustrated on a nonlinear test problem. In the companion paper (Singh et al., 2012a) the methodology is applied to a global chemical data assimilation experiment.

Item Type:Departmental Technical Report
Keywords:data assimilation; information theory
Subjects:Computer Science > Numerical Analysis
ID Code:1195
Deposited By:Sandu, Dr Adrian
Deposited On:04 August 2012

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