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Jacob Segall

Jake Segall

Jacob Segall.

Research
Associate II

jacob.h.segall@ou.edu
jacob.segall@noaa.gov
National Weather Center 3920D


  • MS, Atmospheric Science, SUNY-Stony Brook
  • BS, Meteorology, Penn State University

  • Storm-scale Convection and Radar Team

Jacob works in the Storm-scale Convection and Radar Team (SCRT) within the Warning Research and Development Division (WRDD) at CIWRO. His work initially focused on improving quality control (QC) methods within the Multi-Radar Multi-Sensor (MRMS) system for severe, particularly tornadic, storms. Additionally, he assisted with the integration of the Canadian network of new S-band radars into MRMS. Throughout his time at CIWRO, he has focused on the development of dual-pol radar-based algorithms designed for implementation in MRMS that could potentially improve forecaster’s ability to accurately nowcast severe hazards. More specifically, his current work focuses on the development of algorithms to identify and track size-sorting signatures such as the ZDR arc, KDP foot, and the ZDR-KDP separation vector so as to reduce the burden on forecasters. 

In addition to developing radar algorithms, he has also been an avid participant in many field campaigns. Since joining CIWRO, he has been involved in projects such as PERiLS, TORUS, TORUS-LITE, DELTA, and LIFT. Moreover, he was part of a team that collected data during the landfall of Hurricane Ian. During these projects, he has assisted with operations for NSSL’s mobile X-band radar NOXP, NSSL’s LIDAR, and NSSL’s Mobile Mesonets. Currently, he is co-PI for the project HAILSTONE, which is focused on capturing images of hail in freefall during storms. 


  • Storm-scale processes
  • Dual-pol radar
  • Mesoscale dynamics
  • Hail
  • Nowcasting

  • Weather Radar and Observations

  • Segall, J. H., M. M. French, D. M. Kingfield, S. D. Loeffler, and M. R. Kumjian, 2021: Storm-scale polarimetric radar signatures associated with tornado dissipation in supercells. Wea. Forecasting, 37,3-21, https://doi.org/10.1175/WAF-D-21-0067.1.
  • Segall, J. H., M. M. French, D. M. Kingfield, and J. C. Snyder, 2020: Storm-scale polarimetric radar signatures associated with tornado dissipation in supercells. Amer. Meteor. Soc. Annual Meeting, Boston, MA, Amer. Meteor. Soc., 368658.
  • Segall, J. H., M. M. French, D. M. Kingfield, and J. C. Snyder, 2021: Storm-scale polarimetric radar signatures associated with tornado dissipation in supercells. Virtual Conf. on Severe Local Storms, Virtual, Amer. Meteor. Soc..
  • Segall, J. H., and K. L. Ortega, 2022: Validation of the hail differential reflectivity using the severe hazards analysis and verification experiment (SHAVE) dataset. 2022 N. Amer. Hail Workshop, Boulder, CO, UCAR, P2.5.
  • Segall, J. H., A. E. Reinhart, K. L. Ortega, M. M. French, D. M. Kingfield, S. D. Loeffler, and M. R. Kumjian, 2022: An overview of an automated algorithm for identifying and tracking polarimetric radar signatures in real-time. 30th Conf. on Severe Local Storms, Santa Fe, NM, Amer. Meteor. Soc., 118.
  • Loeffler, S. D., J. H. Segall, M. B. Wilson, A. E. Reinhart, K. L. Ortega, M. M. French, and D. M. Kingfield, 2023: Comparison of algorithm performance assessing size-sorting signatures in polarimetric radar data. 40th Conf. on Radar Meteor., Minneapolis, MN, Amer. Meteor. Soc., 96.
  • Alford, A. A., J. Ringhausen, N. S. Brauer, V. C. Chmielewski, K. M. Calhoun, C. K. Ferguson, S. M. Waugh, M. Stock, V. Salinas, and J. H. Segall, 2023: Dual polarization observations of electrified deep convection during the landfall of Hurricane Ian. 40th Conf. on Radar Meteor., Minneapolis, MN.
  • Segall, J. H., S. D. Loeffler, M. B. Wilson, A. E. Reinhart, K. L. Ortega, M. M. French, and D. M. Kingfield, 2024: Comparison and evaluation of hydrometeor size sorting signature identification algorithms in tornadic and nontornadic supercells. 104th AMS Annual Meeting, Baltimore, MD.
  • J. H. Segall and K. L. Ortega, 2024: Verification of the hail differential reflectivity using the severe hazards analysis and verification experiment (SHAVE) dataset. 104th AMS Annual Meeting, Baltimore, MD.