Cooperative Institute for Mesoscale Meteorological Studies

RESEARCH

 

NOAA Strategic Goal 3: Serve Society’s Need for Weather and Water Information

Basic Convective and Mesoscale Research

Other Agency – Mesoscale Dynamics and Mesoscale Applications of Information Theory

Xu (primary – NSSL), Lei, Gao, collaborators at NSSL and Institute of Atmospheric Physics (IAP) in Beijing

Funding Type: NSF, Office of Naval Research, FAA, NSSL Director’s Discretionary Research Fund

Objectives
Explore various instability mechanisms that will provide possible explanations for initiation of some observed mesoscale rainbands and severe storm elements embedded in frontal rainbands, including but not limited to studies of modal and non-modal growths and structures in the presence of symmetric stability and instability.

Accomplishments
The relative entropy is compared with the previously used Shannon entropy difference as a measure of the amount of information extracted from observations by an optimal analysis in terms of the changes in the probability density function (pdf) produced by the analysis with respect to the background pdf. It is shown that the relative entropy measures both the signal and dispersion parts of the information content from observations, while the Shannon entropy difference measures only the dispersion part. When the pdfs are Gaussian or transformed to Gaussian, the signal part of the information content is given by a weighted inner-product of the analysis increment vector and the dispersion part is given by a non-negative definite function of the analysis and background covariance matrices. When the observation space is transformed based on the singular value decomposition of the scaled observation operator, the information content becomes separable between components associated with different singular values. Densely distributed observations can be then compressed with minimum information loss by truncating the components associate with the smallest singular values. The differences between the relative entropy and Shannon entropy difference in measuring information content and information loss are analyzed in details. Illustrative examples are given for the velocity observations from the NSSL phased array radar with the background field from the Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System.

This project is ongoing.

Publications
Xu, Q., 2007: Modal and non-modal symmetric perturbations. Part 1. Modal solutions and partial orthogonality. J. Atmos. Sci., 64, 1745-1763.

Xu, Q., 2007: Measuring information content from observations for data assimilation: Relative entropy versus Shannon entropy difference. Tellus, 59A, 198-209.

Xu, Q., T. Lei, and S. Gao, 2007: Modal and non-modal