Browsing OU - Dissertations by Subject "Kalman filtering"
Now showing items 1-8 of 8
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APPLICATIONS OF ENSEMBLE KALMAN FILTER DATA ASSIMILATION: FROM CONVECTIVE THUNDERSTORMS TO HURRICANES
(2010)For the numerical prediction of severe thunderstorm and hurricane, data assimilation is one of the necessary tools to obtain accurate initial conditions. Ensemble Kalman filter (EnKF) is a state of the art data assimilation ... -
ASSIMILATION OF ATTENUATED DATA FROM X-BAND NETWORK RADARS USING ENSEMBLE KALMAN FILTER
(2013)To use reflectivity data from X-band radars for quantitative precipitation estimation and storm-scale data assimilation, the effect of attenuation must be properly accounted for. Traditional approaches try to make correction ... -
Data Assimilation Using The Ensemble Kalman Filter With Emphasis On The Inequality Constraints
(2010)The reliability of reservoir models generally increases as more data are included during their construction. In the recent past, the ensemble Kalman lter (EnKF) technique has established itself as a viable data assimilation ... -
Ensemble Kalman Filter Data Assimilation in the Presence of Large Model Error
(2010)Though assimilation of synthetically generated surface flux "observations" into numerical forecast models has been attempted, the topic of observed flux data assimilation over land has received little attention. This may ... -
History Matching of 3D Reservoir Models with Complex Non-Gaussian Distributions of the Model Parameters
(2010)Although the first application of the ensemble Kalman filter (EnKF) as a technique for sequential assimilation of noisy measurements was to a numerical weather prediction problem, remarkable research progress has been made ... -
IMPROVING THE EnKF FOR HISTORY MATCHING: MULTISCALE PARAMETERIZATION AND BOOTSTRAP-BASED SCREENING
(2010)Although the ensemble Kalman filter (EnKF) has been remarkably successful for history matching and quantifying uncertainty in petroleum reservoirs, there have been problems with the use of small ensembles, and occasionally ... -
KALMAN FILTER BASED TECHNIQUES FOR ASSIMILATION OF RADAR DATA
(2010)The assimilation of radar data in storm-scale numerical weather prediction models is essential for improved forecasts of thunderstorm events. The huge computational cost of assimilating the high temporal and spatial ... -
STATE AND PARAMETER ESTIMATION USING POLARIMETRIC RADAR DATA AND AN ENSEMBLE KALMAN FILTER
(2008)The US National Weather Service plans to upgrade the entire operational radar network to polarimetric capability early in the next decade. The goal of this dissertation is to develop methodologies that use polarimetric ...