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Dr. Alexander Gluhovsky

Professor Emeritus Dr. Alexander Gluhovsky

aglu@purdue.edu
Curriculum Vitae
Associated website(s):
Google Scholar , Atmospheric Science , Climate Change and Computational Science , Geodata Science Initiative


Education
  • Ph.D. - USSR Academy of Sciences (Applied Mathematics)
  • M.S. - Moscow State University (Mathematics/Statistics)
Research Interests
  • Geophysical Fluid Dynamics. Atmospheric and climate low-order models, convection, coherent structures in turbulent flows.
  • Computational Statistics. Atmospheric and climate time series analysis (resampling methods, long memory, trends and extremes).
  • Complexity in Atmospheric and Climate Dynamics.
Teaching Interests
  • STAT 225 Introduction to Probability Models
  • STAT 301T Elementary Statistical Methods
  • STAT 350 Introduction to Statistics
  • STAT 416 / MA 416 Probability
  • STAT 420 Introductory Time Series
  • STAT 503 Statistical Methods for Biology
  • STAT 511 Statistical Methods
  • ATMS 591 Chaotic Dynamics
  • EAS 591S Statistical Methods for Atmospheric Sciences
  • EAS 591/STAT 598 Statistics of Extremes
  • EAS 591/STAT 598 Trends, Extremes, and Predictability
  • EAS 591/STAT 598 Chaos and Complexity in Atmospheric and Climate Dynamics
  • EAS 591/STAT 598 Climate Time Series Analysis
  • EAPS 509 Data Analysis Techniques in Earth and Atmospheric Sciences
  • EAPS 310 Indroductory Statistics in Geosciences
Selected Publications - Google Scholar Page for a complete list of publications
  • Gluhovsky, A. (2017):  A gyrostatic low-order model for the El Ñino-Southern Oscillation. Complexity , 2017, 6176045. PDF
  • Gluhovsky, A. , and K. Grady (2016): Effective low-order models for atmospheric dynamics and time series analysis . Chaos: An Interdisciplinary Journal of Nonlinear Science, 26, 023119 . PDF
  • Gluhovsky, A. (2014) Comment on ‘‘Minimal atmospheric finite-mode models preserving symmetry and generalized Hamiltonian structures, Physica D 240 (2011) 599-606”. Physica D , 268, 118-120. PDF
  • Gluhovsky, A. , and T. Nielsen (2012): Improving the actual coverage of subsampling confidence intervals in atmospheric time series analysis. Nonlin. Processes Geophys. , 19, 473-477. PDF
  • Gluhovsky, A . (2011): Statistical inference from atmospheric time series: detecting trends and coherent structures. Nonlin. Processes Geophys. , 18, 537-544. PDF
  • Fall, S., D. Niyogi, A. Gluhovsky, R. A. Pielke Sr., E. Kalnay and G. Rochon (2010): Impacts of land surface properties on temperature trends using North American regional reanalysis over the USA. Int. J. Climatol. , 30, 1980-1993.
  • Gluhovsky, A ., and E. M. Agee (2009) Estimating higher-order moments of nonlinear time series. J. Appl. Meteorol. Climatol., 48, 1948-1954.
  • Trapp, R. J., N. S. Diffenbaugh, and A. Gluhovsky (2009): Transient response of severe thunderstorm forcing to elevated greenhouse gas concentrations, Geophys. Res. Lett . , 36, L01703
  • Gluhovsky, A (2008): Subsampling methodology for the analysis of nonlinear atmospheric time series. Nonlinear Time Series Analysis in the Geosciences . Lecture Notes in Earth Sciences, Vol. 112. R. V. Donner, S. M. Barbosa, Eds., Springer, 3-16.
  • Gluhovsky, A. , C. Tong, and E. Agee (2002) Selection of modes in convective low-order models. J. Atmos. Sci ., 59,1383-1393.

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