Learn More
Assimilation of Doppler radar data into cloud models is an important obstacle to routine numerical weather prediction for convective-scale motions; the difficulty lies in initializing fields of wind, temperature, moisture, and condensate given only observations of radial velocity and reflectivity from the radar. This paper investigates the potential of the(More)
This study explores the assimilation of Doppler radar observations for cloud-resolving hurricane analysis, initialization and prediction with an ensemble Kalman filter (EnKF). The case studied is Hurricane Humberto (2007), the first landfalling hurricane in the US since the end of the 2005 hurricane season and the most rapidly intensifying near-landfall(More)
In previous works of this series study, an ensemble Kalman filter (EnKF) has been demonstrated to be promising for mesoscale and regional scale data assimilation in increasingly realistic environments. Parts I and II examined the performance of the EnKF by assimilating simulated observations under both perfect-and imperfect-model assumptions. Part III(More)
Previous analysis of Oklahoma City (OKC), Oklahoma, temperature data indicated that urban heat islands (UHIs) frequently formed at night and the observed UHI intensity was variable (18–48C). The current study focuses on identifying meteorological phenomena that contributed to the variability of nocturnal UHI intensity in OKC during July 2003. Two episodes,(More)
Through observing system simulation experiments, this two-part study exploits the potential of using the ensemble Kalman filter (EnKF) for mesoscale and regional-scale data assimilation. Part I focuses on the performance of the EnKF under the perfect model assumption in which the truth simulation is produced with the same model and same initial(More)
The performance of the ensemble Kalman filter (EnKF) in forced, dissipative flow under imperfect-model conditions is investigated through simultaneous state and parameter estimation where the source of model error is the uncertainty in the model parameters. A two-dimensional, nonlinear, hydrostatic, non-rotating, and incompressible sea-breeze model is used(More)
Mounting evidence has shown that induction of epithelial-mesenchymal transition (EMT) contributes to the the expression of CSC (cancer stem cell) markers. However, whether and how CSC markers could be involved in regulating EMT has rarely been reported. CD44, being one of the most commonly used CSC markers in hepatocellular carcinoma (HCC), has been(More)
[1] This study examines a hurricane prediction system that uses an ensemble Kalman filter (EnKF) to assimilate high‐ resolution airborne radar observations for convection‐ permitting hurricane initialization and forecasting. This system demonstrated very promising performance, especially on hurricane intensity forecasts, through experiments over all 61(More)
1 Through a WRF-based ensemble Kalman filter (EnKF) data assimilation system, the 2 impact of assimilating airborne radar observations for the convection-permitting analysis and 3 prediction of Hurricane Katrina (2005) is examined in this study. A forecast initialized from 4 EnKF analyses of airborne radar observations had substantially smaller hurricane(More)
Background. Inflammatory bowel diseases (IBD) are recurrent and refractory which include ulcerative colitis (UC) and Crohn's disease (CD). Clinical researches about acupuncture and moxibustion treatments for IBD are increasing, while systematic reviews about their efficacy remains in a shortage. This study sought to evaluate the efficacy of acupuncture and(More)