U.S. Environmental Protection Agency	Voice: (919) 541-7655
MD E243-01	Fax: (919) 541-1379
Research Triangle Park, NC 27711 USA	Swall.Jenise@epa.gov

Professional experience

National Oceanic and Atmospheric Administration, Research Triangle Park, NC

(on assignment to the U.S. EPA's Atmospheric Modeling Division)

I develop and apply statistical methods appropriate for evaluating the performance of air quality models and for assessing air quality trends. Based on limited monitoring data, I have used spatial statistical modeling strategies to estimate pollutant levels and then to assess the air quality model's performance. In another project, advanced time series analysis techniques were used to account for the effects of meteorology in the estimation of ozone trends. I continue to develop and apply spatial and spatio-temporal modeling techniques to better characterize air quality, including the assessment of long-range trends and variability. These methods reflect new, state-of-the-art Bayesian hierarchical modeling approaches. This research requires extensive knowledge of statistical theory, applied methodology, algorithms, and computing.

I conduct research as a member of various interdisciplinary teams and advise atmospheric scientists, meteorologists, and other environmental scientists on statistical and numerical issues that arise in the course of larger research efforts. In addition, I consult with scientists individually on statistical matters, such as appropriate techniques for inference and interpretation of the results of statistical procedures, and on statistical computing issues, including selection of statistical software packages and appropriate use of statistical algorithms.

Kenyon College, Gambier, OH
Assistant Professor of Mathematics, July 2001-June 2003

Developed and taught courses in elementary statistics, data analysis, design and analysis of experiments, probability, and mathematical statistics. (Teaching load: 2-3 courses per semester)

Continued research into non-stationary spatial models, with an emphasis on incorporation of censored data, model comparison, Markov chain Monte Carlo (MCMC) convergence issues, and improvement of computational efficiency.

Responsible for providing own UNIX system administration, maintenance, and back-ups.

Los Alamos National Laboratory, Los Alamos, NM
Visiting Faculty Program, June 2002-July 2002

Developed model comparison methodologies for various spatial modeling strategies. Contributed to other on-going projects at LANL.

Duke University, Durham, NC
Visiting Assistant Professor, January 2000-June 2001

Designed and taught a new calculus-based statistics course for economics majors, with an enrollment of over 100 students each semester. Developed an archive of teaching materials for use by future faculty teaching this course.

Continued research into non-stationary spatial processes, with a particular emphasis on modeling correlation dependence structure as a mixture of a set of weighted "basis" kernels. Increased computational efficiency beyond that achieved by many previous methods, without requiring assumptions of stationarity or isotropy.

SAS Institute, Cary, NC
Assistant Applications Developer, June 1996-August 1997

Served as member of consulting team on variety of projects, including applications in banking, human resources management, and educational administration. Designed and implemented SAS software solutions for clients, with emphasis on providing user-friendly interfaces, maintaining data security, managing databases, generating reports easily and efficiently.

Education

Duke University, Institute of Statistics and Decision Sciences, Durham, NC
Ph.D. in Statistics and Decision Sciences, December 1999

Advisor: David Higdon, Ph.D.

Massachusetts Institute of Technology, Cambridge, MA
B.S. in Mathematics (applied emphasis), May 1994
Completed degree in three years.

Research interests

Bayesian statistics, modeling spatial processes, statistical computing, statistics in environmental applications

Selected publications

Swall, J. L., Foley, K. M. The impact of incommensurability on model evaluation strategies: Moving beyond the comparison of matched observations and model grid cells. (submitted)

Irwin, J., Civerlo, K., Hogrefe, C., Appel, K., Foley, K., Swall, J., 2008. A procedure for inter-comparing the skill of regional-scale air quality model simulations of daily maximum 8-hour ozone values. Atmospheric Environment, Vol. 42, No. 21, 5403-5412.

Cooter, E., Gilliam, R., Swall, J., Mickley, L. Comparison of current U.S. global reanalysis 700 hPa wind patterns to downscaled climate model results using cluster analysis. (in revision)

Cooter, E., Gilliam, R., Swall, J. Comparison of downscaled current and future 700 hPa wind patterns using cluster analysis. (in review)

Cooter, E., Gilliam, R., Benjey, W., Nolte, C., Swall, J., Gilliland, A. Examining the impact of changing climate on regional air quality over the U.S. Developments in Environmental Sciences, Chp. 6.1, Vol. 6, 2007.

Cooter, E., Swall, J., Gilliam, R., 2007. Comparison of 700 hPa NCEP-R1 and AMIP-R2 wind patterns over the continental U.S. using cluster analysis. Journal of Applied Meteorology and Climatology, Vol. 46, No. 11, pp. 1744-1758.

Zheng, J., Swall, J. L., Cox, W. M., Davis, J. M., 2007. Interannual variation in meteorologically adjusted ozone levels in the eastern United States: a comparison of two approaches. Atmospheric Environment, Vol. 41, No. 4, 705-716

Koracin, D., Panorska, A., Isakov, V., Touma, J., Swall, J.., 2007. A statistical approach for estimating uncertainty in dispersion modeling: An example of application in southwestern U.S. Atmospheric Environment, Vol. 41, No. 3, 617-628

Swall, J. L. Davis, J. M., 2006. A Bayesian statistical approach for the evaluation of CMAQ. Atmospheric Environment, Vol. 40, No. 26, 4883-4893.

Ching, J., Herwehe, J., Swall, J., 2006. Paradigm using joint deterministic grid modeling and sub-grid variability stochastic descriptions as a template of model evaluation. Atmospheric Environment, Vol. 40, No. 26, 4935-4945.

Hogrefe, C., Porter, P.S., Gego, E., Gilliland, A., Gilliam, R., Swall, J., Irwin, J., Rao, S.T, 2006. Temporal features in observed and predicted meteorology and air quality over the Eastern United States. Atmospheric Environment, Vol. 40, No. 26, 5041-5055.

Davis, J. M., Swall, J. L., 2006. An examination of the CMAQ simulations of the wet deposition of ammonium from a Bayesian perspective. Atmospheric Environment, Vol. 40, No. 24, 4562-4573.

Yu, S., Dennis, R., Roselle, S., Nenes, A., Walker, J., Eder, B., Schere, K., Swall, J., Robarge, W., 2005. An assessment of the ability of 3-D air quality models with current thermodynamic equilibrium models to predict aerosol NO₃^-. Journal of Geophysical Research, 110, D07S13, doi:10.1029/2004JD004718.

Swall, J. L., 1999. Non-stationary spatial modeling using a process convolution approach, Ph.D. Dissertation, Duke University

Higdon, D., Swall, J., Kern, J. Non-Stationary Spatial Modeling. Bayesian Statistics 6, Oxford University Press, 1999

Professional service

Member, Atmospheric Environment editorial advisory board, Jan. 2008 - present

Committee on Student Awards and Travel Fellowships, Section on Statistics and the Environment, American Statistical Association

Chair, 2007

Member, 2005-2007

Reviewer

Atmospheric Environment

Journal of the American Statistical Association

Ecology

Statistical Science

Professional organizations

American Statistical Association

Section on Bayesian Statistical Science

Section on Statistics and the Environment

Section on Statistical Computing

Computing

Operating systems: Linux, UNIX, Windows, Mac OS
Programming languages: C, R, S-Plus, SAS
Document preparation: LaTeX, Microsoft Office, HTML