Istvan Szunyogh
  • Professor

Biography

Professional Links


Additional Information

Experience

  • Professor, September 2012-Present; Department of Atmospheric Sciences, Texas A&M University
  • Professor, February 2009-Present; Department of Atmospheric Sciences, Texas A&M University
  • Associate Research Scientist, July 2005–January 2009; Institute for Physical Science and Technology and Department of Atmospheric and Oceanic Science (formerly Department of Meteorology), Member of the Applied Mathematics and Scientific Computation Graduate Program and the Burgers Program for Fluid Dynamics, University of Maryland
  • Assistant Research Scientist, February 2001–June 2005; Institute for Physical Science and Technology and Department of Meteorology, University of Maryland
  • Visiting Scientist, September 1997–February 2001; University Corporation for Atmospheric Research (UCAR), based at the Environmental Modeling Center, National Centers for Environmental Prediction (formerly NMC), National Weather Service 
  • Postdoctoral Associate, March 1997–September 1997; Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, based at NCEP
  • Postdoctoral Visiting Scientist, September 1996–February 1997; Mesoscale and Microscale Meteorology Division,National Center for Atmospheric Research, Boulder, Colorado, based at NCEP
  • Visiting Scientist at the Program “Mathematics of the Atmosphere and Ocean Dynamics” (July 1996-September 1996), Isaac Newton Institute for Mathematical Sciences, Cambridge, United Kingdom
  • Magyary Zoltan Postdoctoral Fellow, September 1995–August 1996; Department of Meteorology, E¨otv¨os Lorand University, Budapest, Hungary
  • Research Scientist, September 1998–September 1999 (on leave); Department of Meteorology, Eotvos Lorand University, Budapest, Hungary
  • Research Associate, September 1991–September 1998 (on leave after September 1995), Department of Meteorology, Eotvos Lorand University, Budapest, Hungary

Research Interests

My group employs advanced numerical, machine learning (ML), and statistical techniques to improve numerical weather prediction models and products. The focus of my research is on the Earth's atmosphere, but the techniques my group develops are also applicable to a wide range of complex physical systems. Our work involves both theoretical investigation and experimentation with simple idealized and complex state-of-the-art models. We carry out research in the following specific areas:  

  • Numerical weather prediction (NWP)
  • Earth system modeling (ESM)
  • Data assimilation (DA)
  • Machine learning (ML)
  • Predictability of the atmosphere, ocean, and other complex systems

Outreach

Educational Background

  • Ph.D., Earth Sciences, Hungarian Academy of Sciences, Budapest, Hungary
  • Diploma, Meteorology, Eotvos Lorand University, Budapest, Hungary

Awards & Honors

  • College of Geosciences 2017 Distinguished Achievement Award: Faculty Excellence in Research
  • Certificate of Recognition, January 5, 2015 from the U.S. THORPEX Executive Committee. For his international leadership and predictability and data assimilation research contributions to U.S. participation in the World Meteorological Organization's THORPEX Weather Research Program
  • Certificate of Appreciation, November 17, 2014 from the World Weather Research Programme (WWRP) of the World Meteorological Organization (WMO). In recognition of an outstanding contribution to the WMO THORPEX program for the years 2005-2014.

Selected Publications

  • For a full list of publications, please see CV at the Links Section

    * indicates a student and ** indicates a postdoctoral associate, whose research was advised or co-advised by I. S.

    Books and Book Chapters

    • Szunyogh, I., 2014: Applicable Atmospheric Dynamics: Techniques for the Exploration of Atmospheric Dynamics. World Scientific, Singapore, pp. 588.
    • Kalnay, E., B. Hunt, E. Ott, and I. Szunyogh, 2006: Ensemble forecasting and data assimilation: two problems with the same solution? In Predictability of Weather and Climate. Eds. T. Palmer and R. Hagedorn. Cambridge University Press. Cambridge,157-180. 

    Selected Articles in Peer-reviewed Journals

    • Pathak*, J., A. Wikner*, B. Hunt, I. Szunyogh, M. Girvan, and E. Ott, 2021: Using data assimilation to train a hybrid forecast system that combines machine-learning and knowledge-based components (under review).
    • Szunyogh, I., E. Forinash*, G. Gyarmati, Y. Jia, P. Chang, and R. Saravanan, 2021: Evaluation of a coupled modeling approach for the investigation of the effects of SST mesoscale variability on the atmosphere (under review). Preprint: https://doi.org/10.1002/essoar.10504810.1.
    • Arcomano*, T., I. Szunyogh, J. Pathak*, A. Wikner*, B. Hunt, and E. Ott, 2020: A machine learning-based global atmospheric forecast model. Geophys. Res. Lett., 47, e2020GL087776.
    • Wikner*, A., J. Pathak*, B. Hunt, M. Girvan, T. Arcomano*, I. Szunyogh, A. Pomerance, and E. Ott, 2020: Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systems. Chaos, 30, 053111.
    • Zagar, N., and I. Szunyogh, 2020: Comments on “What is the predictability limit of midlatitude weather?” by Zhang et al., J. Atmos, Sci., 76, 1077-1091. J. Atmos. Sci., 77, 781-785.
    • Jia, Y., P. Chang, I. Szunyogh, R. Saravanan, and J. T. Bacmeister, 2019: A modeling strategy for the investigation of the effect of mesoscale SST feedback to the atmosphere. Geophys. Res. Lett., 46, 3982-3989.
    • Kavulich*, M. J., I. Szunyogh, G. Gyarmati, and R. J. Wilson, 2013: Local dynamics of baroclinic waves in the Martian atmosphere. J. Atmos. Sci., 70, 3415–3447.
    • Szunyogh, I., E. J. Kostelich, G. Gyarmati, E. Kalnay, B. R. Hunt, E. Ott, E. Satterfield*, and J. A. Yorke, 2008: A Local Ensemble Transform Kalman Filter data assimilation system for the NCEP global model. Tellus, 60A, 113-130.
    • Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: a Local Ensemble Transform Kalman Filter. Physica D, 230, 112-126.
    • Ott, E., B. R. Hunt, I. Szunyogh, A. V. Zimin*, E. J. Kostelich, M. Corazza*, E. Kalnay, D. J. Patil, and J. A. Yorke, 2004: A local ensemble Kalman filter for atmospheric data assimilation. Tellus, 56A, 415-428.
    • Zimin*, A. V., I. Szunyogh, D. J. Patil, B. R. Hunt, and E. Ott, 2003: Extracting envelopes of Rossby wave packets. Mon. Wea. Rev., 131, 1011-1017.
    • Szunyogh, I., Z. Toth, R. E. Morss, S. J. Majumdar, B. J. Etherton, and C. H. Bishop, 2000: The effect  of targeted dropsonde observations during the 1999 Winter Storm Reconnaissance program. Mon. Wea. Rev., 128, 3520-3537.
    • Szunyogh I., E. Kalnay, and Z. Toth, 1997: A comparison of Lyapunov and optimal vectors in a low-resolution GCM. Tellus, 49A, 200-227.
    • Szunyogh I., 1993: Finite-dimensional quasi-Hamiltonian structure in simple model equations. Meteorology and Atmospheric Physics, 52, 49-57.