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Anthony Reinhart

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RRDD Division Staff

Job Title:Phased Array Radar R&D Program Lead

Affiliation:Federal

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Anthony is the Phased Array Radar R&D Program Lead at NSSL. Dr. Reinhart blends his expertise in computer engineering, severe weather research, and application development. Dr. Reinhart's research interests are in the research to operations and operations to research paradigm, radar meteorology, numerical weather prediction of severe convective storms, tornado dynamics, mesoscale processes, data assimilation, performance and verification of numerical weather prediction systems, dryline processes, air mass boundaries, radar tools and techniques for operational use by NWS and private partners.

Education
Degree (Ph.D, M.S, B.A, etc.) Major Subject University or College Name Year (YYYY) (optional)
Ph.D. Geosciences Texas Tech University 2016
M.S. Geosciences University of Nebraska- Lincoln 2009
B.S. Meteorology Purdue University 2007
Research Interests
  • Radar Meteorology
  • Severe Convection
  • Cloud Computing
  • Multi-Radar Multi-Sensor (MRMS)
  • Data Assimilation
  • Tornado Dynamics
  • Mesoscale Processes
  • Programing
Professional Activities
  • NOAA Spectrum Working Group
  • NOAA OAR Cloud Tiger Team
Honors & Awards
Award Name Year
Larry R. Johnson Award, NWA 2016
Selected Publications

Anderson, M. E., D. G. Schneider, J. L. Buckles, D. J. Bodine, A. E. Reinhart, M. A. Satrio, T. Maruyama, 2022: Terrain effects on the 13 April 2018 Mountainburg, Arkansas EF2 tornado. Journal of Operational Meteorology, 10, 2, 18–29, doi:10.15191/nwajom.2022.1002.

Sandmæl, T. N., B. R. Smith, A. E. Reinhart, I. M. Schick, M. C. Ake, J. G. Madden, R. B. Steeves, S. S. Williams, K. L. Elmore, T. C. Meyer, 2023: The Tornado Probability Algorithm: A Probabilistic Machine Learning Tornadic Circulation Detection Algorithm. Weather and Forecasting, 38, doi:10.1175/WAF-D-22-0123.1.

Williams, S. S., K. L. Ortega, T. M. Smith, A. E. Reinhart, 2022: Comprehensive Radar Data for the Contiguous United States: Multi-Year Reanalysis of Remotely Sensed Storms. Bulletin of the American Meteorological Society, 103, 3, E838–E854, doi:10.1175/BAMS-D-20-0316.1.