Annual Report 2008.pdf - SAMSI

• Bayarri, M.J., J. Berger, F. Liu, R. Paulo and P. Reichert. ”Using Computer Model
Derivatives to Improve Emulators and Extrapolating Predictions"
• Bondell, H., Reich,B., Fuentes, M., Hacker, J., and Tardif, R. “On Incorporating a
Stochastic Parameterization into a Numerical Weather Prediction Model” in preparation.
• Cintron-Arias, A., Banks, H.T., Lloyd, A., Castillo-Chavez, C., Bettencourt, L.
“Estimation of Seasonal Influenza Reproductive Numbers” In preparation. (2007)
• Cintron-Arias, A., Banks, H.T., Lloyd, A., Reichert, P. “Analysis of Oscillatory Patterns
in Disease Transmission” In preparation. (2007)
• Cintron-Arias, A., Castillo-Chavez, C., Wang, X., Sanchez, F. “The Role of Nonlinear
Relapse on Contagion Amongst Drinking Communities” In preparation. (2007)
• Cintron-Arias, A., P. Reichert, A. L. Lloyd, and H. T. Banks, “An Estimation
Methodology for Seasonal Transmissibility”, in preparation.
• DeVault K.J., P.A. Gremaud. “Analysis and Numerical Analysis of Impedance Boundary
Conditions for Hemodynamics”
• DeVault, K.J., P.A. Gremaud, V. Novak, M.S. Olufsen. “Computational Study of the
Effects of Strokes on Cerebral Perfusion”
• Govindarajan, S., S. Chakraborty, P. K. Agarwal, M. C. Dietze, J. S. Clark, and Michael
S. Wolosin. “Light Competition in Forest Canopies”
• Guillas, S., A. Gelfand and S. Sahu, “Bayesian Downscaling of an Air Quality Model". In
this work, uncertainties are naturally assessed by the Bayesian approach. Meteorological
variables are used to locally improve the regional forecasts, using strong priors to give
preference to the chemistry transport model.
• Guillas, S., L. Lefton, Y. Choi, Y. Wang. “Calibration of a 3-D air quality model". We
use the Bayesian calibration method to find the best values for 5 parameters of interest in
a pollution model.
• Guillas, S., Chunsheng Ma. “Space-time Downscaling of Regional Ozone Forecasts with
Nonseparable Covariance Models". In this work we introduce a new type of space-time
covariances that enable us to better with the differences between model outputs and
observations. The resulting downscaling should improve on the result for time series.
• Hacker, J., Tardif, R., Shows, J., Fuentes, M., and Bondell, H. “Stochastic
Parameterization of WRF-1D”, in preparation.