An ensemble Kalman filter for atmospheric data assimilation: Application to wind tunnel data

Atmospheric Environment

Volumn 44, Issue 13, 2010, Pages 1699-1705

  Zheng, D Q ^a   Leung, J K C ^b   Lee, B Y ^c  

^a JINAN UNIVERSITY   (China)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

^c HONG KONG OBSERVATORY   (Hong Kong)

Author keywords

Data assimilation; Dispersion model; Ensemble Kalman filter; Wind tunnel

Indexed keywords

3-D PARAMETER; ATMOSPHERIC DATA; DATA ASSIMILATION; DATA ASSIMILATION METHODS; DISPERSION MODELS; ENSEMBLE KALMAN FILTER; FIELD EXPERIMENT; MEASURED DATA; MONTE CARLO; RANDOM FIELDS; SOURCE TERMS; STANDARD DEVIATION; TECHNICAL NOTES; TURBULENCE INTENSITY; TWIN EXPERIMENTS; UNCERTAIN PARAMETERS; WIND DIRECTIONS; WIND TUNNEL EXPERIMENT; WIND-TUNNEL DATA;

AERODYNAMICS; DATA PROCESSING; EXPERIMENTS; KALMAN FILTERS; MONTE CARLO METHODS; THREE DIMENSIONAL; TURBULENCE; UNCERTAINTY ANALYSIS; WIND TUNNELS;

DISPERSIONS;

DATA ASSIMILATION; KALMAN FILTER; MONTE CARLO ANALYSIS; NUMERICAL MODEL; TURBULENCE; WIND DIRECTION; WIND TUNNEL;

ARTICLE; ATMOSPHERIC DISPERSION; CONTROLLED STUDY; DIGITAL FILTERING; INFORMATION PROCESSING; MONTE CARLO METHOD; NORMAL DISTRIBUTION; PREDICTION AND FORECASTING; PRIORITY JOURNAL; STOCHASTIC MODEL; WIND;

EID: 77949571681     PISSN: 13522310     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosenv.2010.01.020     Document Type: Article

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