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Allen, John

Associate Professor

FACULTY

Biography

Dr. John Allen is an Associate Professor of Meteorology, originally from Sydney, Australia, and serves as the Associate Director for the NSF Artificial Intelligence Institute for Environmental Sciences (AI2ES). He completed his B.S. Degree in Earth Sciences (Meteorology and Applied Mathematics) at the University of Melbourne, Australia, completing further research and a doctorate at the same institution. From 2013-2016 he was Postdoctoral Research Scientist and Associate Research Scientist, joining CMU in the summer of 2016.

Dr. Allen’s research primarily focuses on global severe weather observations and modeling, links between severe weather and the larger climate system, machine learning and statistical prediction of severe weather, and providing community and cross-disciplinary relevant risk and hazard resilience information. His ongoing work includes serving as one of the co-leads for the summer 2025 NSF-funded ICECHIP hail field campaign. Dr. Allen also currently serves as an Editor for the American Meteorological Society journals Weather and Forecasting, and Artificial Intelligence for the Earth Systems.

More about John Allen

Selected Publications in the Last 5 Years

Hosek, M. J, Hoogewind, K. A., Clark, A. J., Justin*, A. J., and J. T. Allen, 2025: A 16-year Climatology of WPC-Analyzed Drylines with and without Severe Convection. In Press, Journal of Climate. doi: 10.1175/JAMC-D-24-0124.1

Justin*, A. D., McGovern, A., and J. T. Allen, 2025: FrontFinder AI: Efficient Identification of Frontal Boundaries over the Continental United States and NOAA's Unified Surface Analysis Domain using the UNET3+ Model Architecture. Artificial Intelligence for the Earth Systems, 4, e240043, doi: 10.1175/AIES-D-24-0043.1

Das%, S. and J. T. Allen, 2024: Bayesian Estimation of the Likelihood of Extreme Hail Sizes over the United States. NPJ Natural Hazards, 1, 47, doi: 10.1038/s44304-024-00052-5

Schmidt*, T. G., McGovern, A., Allen, J. T., Potvin, C. K., Chase, R., Wiley, C., McGovern-Fagg, W., Flora, M. L., Homeyer, C., Williams, J. K., 2024: Gridded Severe Hail Nowcasting Using 3D U-Nets, Lightning Observations and the Warn-on-Forecast System. Artificial Intelligence for the Earth Systems, 3, 240026, doi: 10.1175/AIES-D-24-0026.1.

Gopalakrishnan%, D., Cuervo-Lopez*, C. M., Allen, J. T., Trapp, R. J, and E. Robinson, 2024: A comprehensive evaluation of thermodynamic and kinematic biases in CMIP6 models over the United States. Journal of Climate, 38, 947–971, doi: 10.1175/JCLI-D-24-0165.1

Nixon*, C., Allen, J. T., Wilson, M., Bunkers, M., 2024: Cell Mergers, Boundary Interactions and Convective Systems in Cases of Strong Tornadoes and Large Hail. Weather and Forecasting, 39, 1435–1458, doi: 10.1175/WAF-D-23-0117.1

Nixon*, C., Allen, J. T., Taszarek, M. 2023: Hodographs and Skew-Ts of Hail-Producing Storms, Weather and Forecasting, 38, 2217–2236. doi: 10.1175/WAF-D-23-0031.1.

Dos Santos*, L. O, Nascimento, E., and Allen J. T., 2023: Discriminant Analysis for Severe Storm Environments in South-central Brazil. Monthly Weather Review, 151, 2659–2681, doi: 10.1175/MWR-D-22-0347.1.

Scarino, B., Itterly, K,,Bedka, K., Homeyer, C., Allen, J. T., Bang, S., and D. Cecil, 2023: Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network. Artificial Intelligence for the Earth Systems, 2, 220042, doi: 10.1175/AIES-D-22-0042.1

Justin*, A. D., Willingham, C., McGovern, A., and J. T. Allen, 2023: Toward Operational Real-time Identification of Frontal Boundaries Using Machine Learning. Artificial Intelligence for the Earth Systems, 2, e220052, doi: 10.1175/AIES-D-22-0052.1.

Nixon*, C. J., Allen, J. T., 2022: Distinguishing between Hodographs of Severe Hail and Tornadoes. Weather and Forecasting, 37, 1761–1782. doi: 10.1175/WAF-D-21-0136.1

Elmore, K., J. T. Allen and A. Gerard, 2022: Sub-severe and Severe Hail. Weather and Forecasting, 37, 1357-1369. doi: 10.1175/WAF-D-21-0156.1

Zhou, Z., Q. Zhang, J. T. Allen, X. Ni and C. Ng, 2021: How many types of severe hailstorm environments are there globally? Geophysical Research Letters, 48, e2021GL095485. doi: 10.1029/2021GL095485

Lepore, C., Abernathy, R., Henderson, N., Allen J. T., Tippett, M. K., 2021: Future Global Convective Environments in CMIP6 Models. Earth’s Future, 9, e2021EF002277. doi: 10.1029/2021EF002277

Taszarek, M., Allen J. T., Marchio, M. and H. E. Brooks, 2021: Global Climatology and Trends in convective environments from ERA5 and rawinsonde data. NPJ Climate and Atmospheric Science, 4, 1-11. doi: 10.1038/s41612-021-00190-x

Allen, J. T., E. R. Allen, H. Richter and C. Lepore, 2021: Australian Tornadoes in 2013: Implications for Climatology and Forecasting. Monthly Weather Review, 149, 1211-1232. doi: 10.1175/MWR-D-20-0248.1

Taszarek, M., Pilluj, N., Allen J. T., Gensini, V. A. Brooks, H. E., and P. Szuster, 2021: Comparison of convective parameters derived from ERA5 and MERRA2 with sounding data over Europe and North America. Journal of Climate, 34, 3211-3237. doi: 10.1175/JCLI-D-20-0484.1

Raupach, T. H, Martius, O., Allen, J. T., Kunz, M., Lasher-Trapp, S., Mohr, S., Rasmussen, K. L., Trapp, R. J., and Q. Zhang, 2021: The effects of climate change on hailstorms. Nature Reviews Earth and Environment, 2, 213-226. doi: 10.1038/s43017-020-00133-9

Nixon*, C. J., Allen, J. T., 2020: Anticipating Deviant Tornado Motion Using a Simple Hodograph Technique. Weather and Forecasting, 36, 219-235. doi: 10.1175/WAF-D-20-0056.1

Taszarek, M., Allen, J. T., Pucik, T., Hoogewind, K., and H. E. Brooks, 2020: Severe Convective Storms Across Europe and the United States. Part 2: Environments accompanying lightning, large hail, severe wind and tornadoes. Journal of Climate, 33, 10263-10286. doi: 10.1175/JCLI-D-20-0346.1

Molina*, M., J. T. Allen, A. Prein, 2020: Moisture Attribution and Sensitivity Analysis of a Winter Tornado Outbreak. Weather and Forecasting, 35, 1263-1288 . doi: 10.1175/WAF-D-19-0240.1

Gensini, V., Barrett, B., Allen, J. T., Gold, D., and P. Sirvatka, 2020: The Extended-Range Tornado Acitivity Forecast (ERTAF) Project. Bulletin of the American Meteorological Society, 101, E700-709. doi: 10.1175/BAMS-D-19-0188.1

Allen, J. T., Q. Zhang, I. Giammanco, M. Kumjian, P. Groenemeijer, K. Ortega, M. Kunz, H. Punge 2019: Understanding Hail in the Earth System. Reviews of Geophysics, 57, doi: 10.1029/2019RG000665.

Molina, M. J.* and J. T. Allen, 2019: On the Moisture Origins of Tornadic Thunderstorms. Journal of Climate, 32, 4321-4346. doi: 10.1175/JCLI-D-18-0784.1

Allen, J. T., 2018: Climate Change and Severe Thunderstorms. Oxford Research Encyclopedia of Climate Science. 67pp. doi: 10.1093/acrefore/9780190228620.013. Ed.: Dr. Harold Brooks

*denotes graduate student,

% denotes postdoctoral author

Review a complete bibliography of Dr. Allen's publications on either Google Scholar or the Allen Research Group website.

  • 2020 National Science Foundation CAREER Award
  • 2019/2020 Central Michigan University Provost’s Award for Outstanding Research and Creative Activity
  • 2019 Central Michigan University College of Science & Engineering Award for Outstanding Research
  • 2015 AGU Editors' Citation for Excellence in Refereeing - Geophysical Research Letters
  • 2015 Co-recipient European Severe Storms Laboratory Heini Tooming Award
  • 2022 American Meteorological Society STAC Outstanding Early Career Award, Weather Analysis & Forecasting Committee
  • 2022 American Meteorological Society Editor’s Award for Reviews in service to the journals Weather and Forecasting, Monthly Weather Review, and Journal of Applied Meteorology and Climatology
  • Ph.D., Earth Sciences (Meteorology), The University of Melbourne, 2013
  • B.S., Research Honours (Meteorology), The University of Melbourne, 2008
  • B.S., Meteorology and Applied Mathematics, The University of Melbourne, 2007
  • 2022 American Meteorological Society STAC Outstanding Early Career Award, Weather Analysis & Forecasting Committee.
  • 2022 American Meteorological Society Editor’s Award for Reviews in service to the journals Weather and Forecasting, Monthly Weather Review, and Journal of Applied Meteorology and Climatology.
Tornadoes, Hail, Climatology, Cyclogenesis, Climate Variability and Change, Crowdsourcing of Meteorological Datasets, Field Observations of Severe Thunderstorms
Severe thunderstorms have shaped the development of communities worldwide, and how these events respond to climatic variations remains an open question. The primary goal of my research program is to understand how severe thunderstorms respond to climate variability and, in doing so, improve quantification of potential risk to life, property and agriculture from the present and future climate perspective. However, to achieve this goal, there are several directions. One of these focuses is expanding and exploring our understanding of the climatology of severe thunderstorms both in the United States and globally, finding new ways to leverage developing or existing technology and observations to contribute to our outstanding. Other areas of interest include the physical mechanisms of how climate change and variability can impact extreme events, including severe thunderstorm frequency or intensity, deriving forecasting insight and guidance from lessons learned using climatology, and applications of our understanding of severe thunderstorms to their impacts on agriculture and the built environment.

Courses Taught

  • MET 140: Severe & Unusual Weather
  • MET 310: Atmospheric Thermodynamics
  • MET 450: Mesoscale Meteorology
  • MET 480: Atmospheric Modeling