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Philip Sura

Philip Sura

Associate Professor, Metereology, Florida State University

Phone: (850) 644-1268

Fax: (850) 644-9642

1017 Academic Way
Tallahassee, FL 32306-4520

http://www.met.fsu.edu/index.pl/personnel/faculty/sura

Education:

University of Hamburg, 2000

Research Interests:

Professor Sura’s current research is focused on the stochastic-dynamical understanding of extreme events in climate. Extreme events in climate (such as hurricanes, droughts, windstorms etc.) are by definition rare, but they can have a significant impact on affected people and countries. In non-technical terms, an extreme event is a high-impact, hard-to-predict phenomenon that is beyond our normal (Gaussian bell curve) expectations. In technical terms, an extreme event is often defined as the non-normal (non-Gaussian) tail of the data’s probability density function (PDF). Understanding extremes has become an important objective in climate variability research because climate (and weather) risk assessment depends on knowing and understanding the non-Gaussian tails of PDFs.

Publications List:

  • Sardeshmukh, P. D., and P. Sura, 2008: Reconciling non-Gaussian climate statistics with linear dynamics. J. Climate, submitted.
  • Sura, P., and P. D. Sardeshmukh, 2008: A global view of non-Gaussian SST variability. J. Phys. Oceanogr., Vol. 38, 639-647.
  • Sura, P., and M. Newman, 2008: The impact of rapid wind variability upon air-sea thermal coupling. J. Climate, Vol. 21, 621-637.
  • Sardeshmukh, P. D., and P. Sura, 2007: Multi-scale impacts of variable heating in climate. J. Climate, Vol. 20, 5677-5695.
  • Sura, P., M. Newman, and M. A. Alexander, 2006: Daily to decadal sea surface temperature variability driven by state-dependent stochastic heat fluxes. J. Phys. Oceanogr., Vol. 36, 1940-1958.
  • Sura, P., M. Newman, C. Penland, and P. D. Sardeshmukh, 2005: Multiplicative noise and non-Gaussianity: A paradigm for atmospheric regimes? J. Atmos. Sci., Vol. 62, 1391-1409.
  • Sura, P., and S. T. Gille, 2003: Interpreting wind-driven Southern Ocean variability in a stochastic framework. J. Mar. Res., Vol. 61, 313-334.