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Derek Stratman

Derek Stratman

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Research
Scientist II

stratman@ou.edu
derek.stratman@noaa.gov
National Weather Center 4349


  • PhD, Meteorology, University of Oklahoma
  • MS, Meteorology, University of Oklahoma
  • BS, Meteorology, Vaparaiso University

  • Data Assimilation & Modeling Team

Dr. Stratman has been a research scientist with CIWRO since 2017 and has been working within NSSL’s Warn-on-Forecast group since 2016. His research interests primarily focus on storm-scale ensemble data assimilation and short-term forecasts of severe convective weather, including data assimilation techniques, stochastic physics, phased-array radar data assimilation, storm-scale predictability, and forecast verification using spatial and object-based techniques. More broadly, his research largely aims to provide guidance for future generations of NSSL’s Warn-on-Forecast System (WoFS), including a 1-km version.

Some of his previous research at CIWRO and NSSL involves correcting storm displacement errors in WoFS using a feature-alignment technique he developed, developing a 1-km version of WoFS with other scientists at CIWRO, researching and developing stochastic physics methods and their potential beneficial impacts for WoFS, researching ways to best assimilate temporally-frequent (every ~1 min) phased-array radar (PAR) volumetric data into WoFS, and evaluating WoFS analyses and forecasts using novel verification techniques.


  • Severe and hazardous weather prediction
  • Ensembles
  • Storm-scale modeling
  • Short-term forecasts
  • Ensemble data assimilation
  • Stochastic physics
  • Phased-array radar data assimilation
  • Storm-scale predictability
  • Forecast verification

  • Mesoscale and Stormscale Modeling R&D

  • Stratman, D. R., N. Yussouf, C. A. Kerr, B. C. Matilla, J. R. Lawson, and Y. Wang, 2024: Testing Stochastic and Perturbed Parameter Methods in an Experimental 1-km Warn-on-Forecast System Using NSSL’s Phased-Array Radar Observations. Mon. Wea. Rev., 152, 433–454, https://doi.org/10.1175/MWR-D-23-0095.1.
  • Heinselman, P. L., and Coauthors, 2023: Warn-on-Forecast System: From Vision to Reality. Wea. Forecasting, 39, 75–95, https://doi.org/10.1175/WAF-D-23-0147.1.
  • Kerr, C. A., B. C. Matilla, Y. Wang, D. R. Stratman, T. A. Jones, and N. Yussouf, 2022: Results from a Realtime Next-Generation 1-km Warn-on-Forecast System Prototype. Wea. Forecasting, 38, 307–319, https://doi.org/10.1175/WAF-D-22-0080.1.
  • Wang, Y., N. Yussouf, C. A. Kerr, D. R. Stratman, B. C. Matilla, 2022: An Experimental 1-km Warn-on-Forecast System for Hazardous Weather Events, Mon. Wea. Rev., 150, Early Online Release, https://doi.org/10.1175/MWR-D-22-0094.1.
  • Stratman, D. R. and C. K. Potvin, 2022: Testing the Feature Alignment Technique (FAT) in an Ensemble-Based Data Assimilation and Forecast System with Multiple-Storm Scenarios, Mon. Wea. Rev., 150, 2033-2054, https://doi.org/10.1175/MWR-D-21-0289.1.
  • Putnam, B. J., Y. Jung, N. Yussouf, D. Stratman, T. Supinie, M. Xue, C. Kuster, and J. Labriola, 2021: The Impact of Assimilating ZDR Observations on Storm-Scale Ensemble Forecasts of the 31 May 2013 Oklahoma Storm Event. Mon. Wea. Rev., 149, 1919-1942, https://doi.org/10.1175/MWR-D-20-0261.1.
  • Weber, M., K. Hondl, N. Yussouf, Y. Jung, D. Stratman, and Coauthors, 2021: Towards the Next Generation Operational Meteorological Radar. Bull. Amer. Meteor. Soc., 102, E1357–E1383, https://doi.org/10.1175/BAMS-D-20-0067.1.
  • Stratman, D. R., N. Yussouf, Y. Jung, T. A. Supinie, M. Xue, P. S. Skinner, and B. J. Putnam, 2020: Optimal temporal frequency of NSSL phased-array radar observations for an experimental Warn-on-Forecast system. Wea. Forecasting, 35, 193–214, https://doi.org/10.1175/WAF-D-19-0165.1.
  • Stratman, D. R., C. K. Potvin, and L. J. Wicker, 2018: Correcting storm displacement errors in ensembles using the feature alignment technique (FAT). Mon. Wea. Rev., 146, 2125–2145, https://doi.org/10.1175/MWR-D-17-0357.1.
  • Stratman, D. R. and K. A. Brewster, 2017: Sensitivities of 1-km forecasts of 24 May 2011 tornadic supercells to microphysics parameterizations. Mon. Wea. Rev., 145, 2697–2721, https://doi.org/10.1175/MWR-D-16-0282.1.
  • Gallo, B. T., A. J. Clark, I. Jirak, J. S. Kain, S. J. Weiss, M. Coniglio, K. Knopfmeier, J. Correia, C. J. Melick, C. D. Karstens, E. Iyer, A. R. Dean, M. Xue, F. Kong, Y. Jung, F. Shen, K. W. Thomas, K. Brewster, D. Stratman, G. W. Carbin, W. Line, R. Adams-Selin, and S. Willington, 2017: Breaking New Ground in Severe Weather Prediction: The 2015 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment. Wea. Forecasting, 32, 1541–1568, https://doi.org/10.1175/WAF-D-16-0178.1.
  • Stratman, D. R., M. C. Coniglio, S. E. Koch, M. Xue, 2013: Use of multiple verification methods to evaluate forecasts of convection from hot- and cold-start convection-allowing models. Wea. Forecasting, 28, 119–138, https://doi.org/10.1175/WAF-D-12-00022.1.
  • American Meteorological Society