Ensemble state estimation for nonlinear systems using polynomial expansions in the innovation

Monthly Weather Review

Volumn 139, Issue 11, 2011, Pages 3571-3588

  Hodyss, Daniel ^a  

^a NAVAL RESEARCH LABORATORY   (United States)

Author keywords

Data assimilation; Ensembles; Filtering techniques; Forecasting; Kalman filters

Indexed keywords

BAYESIAN FRAMEWORKS; DATA ASSIMILATION; ENSEMBLES; ESTIMATION PROBLEM; FILTERING TECHNIQUES; FORECAST ERRORS; LORENZ ATTRACTOR; MOMENTS OF THE DISTRIBUTION; NONLINEAR FUNCTIONS; NONNORMAL; POLYNOMIAL EXPANSION; POLYNOMIAL SERIES; PROBABILITY DENSITY FUNCTION (PDF); SCALAR SYSTEMS; STATE ESTIMATES;

DATA PROCESSING; DEMODULATION; ESTIMATION; EXPANSION; FORECASTING; KALMAN FILTERS; NONLINEAR ANALYSIS; NONLINEAR SYSTEMS; NORMAL DISTRIBUTION; POLYNOMIALS; PROBABILITY DENSITY FUNCTION;

STATE ESTIMATION;

BAYESIAN ANALYSIS; DATA ASSIMILATION; ENSEMBLE FORECASTING; ESTIMATION METHOD; KALMAN FILTER; PROBABILITY DENSITY FUNCTION; WEATHER FORECASTING;

EID: 84855772814     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/2011MWR3558.1     Document Type: Article

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