Andrew E. Mercer
Associate Professor
Department of Geosciences
Mississippi State University

PhD in Meteorology
University of Oklahoma, 2008

Web: geosciences.msstate.edu

Email: mercer@hpc.msstate.edu
Phone: 662-325-2913

Research Interests
My previous and current research interests lie in the application of advanced statistical modeling and artificial intelligence to meteorology. Specifically, I am interested in applying artificial intelligence methods such as neural networks and support vector machines to hurricane prediction. My secondary interests include synoptic meteorology and mesoscale phenomenon, such as mountain windstorms.

Current Research Projects
I am interested in studying several different meteorological topics involving advanced statistical methods. I would like to develop a new seasonal hurricane prediction scheme based on artificial intelligence, as well as use artificial intelligence pattern recognition techniques to aid in the development of a better hurricane tracking algorithm. I am also interested in reinventing the model output statistics (MOS) that result from different numerical weather prediction simulations based on advanced regressions, including support vector regression.

Most Current Publications:
Shafer, C. M., A. E. Mercer, C. A. Doswell, M. B. Richman, and L. M. Leslie, 2009: Evaluation of tornadic and nontornadic outbreaks when initialized with synoptic scale input. Mon. Wea. Rev., 137, 1250-1271.

Mercer A. E., M. B. Richman, H. B. Bluestein, and J. M. Brown, 2008: Statistical modeling of downslope windstorms in Boulder, Colorado. Wea. Forecasting: 23, 1176-1194.

Mercer, A. E., C. M. Shafer, C. A. Doswell, L. M. Leslie, and M. B. Richman, 2008: Composite analysis of severe weather outbreaks. 24th Conference on Severe and Local Storms, Savannah, Georgia.

Mercer, A. E., M. B. Richman, H. B. Bluestein, and J. M. Brown, 2008: Application of statistical models to Boulder windstorm prediction. 13th Conference on Mountain Meteorology, Whistler, British Columbia.

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