Steven J. Greybush Publications

2020-2024 | 2014-2019 | 2007-2013
*Grad Student Advised by SJG, ^Student or Postdoc Mentored by SJG

2020-2024

  1. Fan, D.*, S. J. Greybush, D. J. Gagne, and E. E. Clothiaux, 2024: Physically Explainable Deep Learning for Convection Initiation Nowcasting Using GOES-16 Satellite Observations. Artificial Intelligence for the Earth Systems, in press, doi:10.1175/AIES-D-23-0098.1.
  2. Gillespie, H. E.*, D. J. McCleese, A. Kleinboehl, D. M. Kass, S. J. Greybush, and R. J. Wilson, 2024: Water Transport in the Mars Polar Atmosphere: Observations and Simulations. JGR Planets, 129, 5, doi:10.1029/2023JE008273.
  3. Greybush, S. J., T. D. Sikora, G. S. Young, Q. Mulhern^, R. D. Clark, and M. Jurewicz, 2024: Elevated Mixed Layers during Great Lake Lake-effect Events: An Investigation and Case Study from OWLeS. Monthly Weather Review, 152(1), 79-95, doi:10.1175/MWR-D-22-0344.1.
  4. Naegele, S. M.*, J. A. Lee, S. J. Greybush, S. E. Haupt, and G. S. Young, 2024: Identifying Wind Regimes Near Kuwait Using Self-Organizing Maps. Journal of Renewable and Sustainable Energy, 17, 02651, doi:10.1063/5.0152718.
  5. Mykolajtchuk, P. D.^, K. C. Eure^, Y. Zhang, D. J. Stensrud, F. Zhang, S. J. Greybush, and M. R. Kumjian, 2023: Diagnosing a missed convective initiation forecast by assimilating GOES-16 satellite radiances and WSR-88D radar observations. Weather and Forecasting, 38(10), 1935-1951, doi:10.1175/WAF-D-23-0010.1.
  6. Eure, K. C.^, P. D. Mykolajtchuk^, Y. Zhang, D. J. Stensrud, F. Zhang, S. J. Greybush, and M. R. Kumjian, 2023: Simultaneous Assimilation of Radar and Satellite Observations to Improve Ensemble Forecasts of Severe Weather. Monthly Weather Review, 151(3), 795-813, doi:10.1175/MWR-D-22-0188.1.
  7. Wang, Y.^, M. Gueye^, S. J. Greybush, H. Greatrex, A. J. Whalen, P. Ssentongo, F. Zhang, G. Jenkins, and S. J. Schiff, 2023: Verification of Operational Numerical Weather Prediction Model Forecasts of Precipitation Using Satellite Rainfall Estimates over Africa. Meteorological Applications, 30(1), 22p, https://doi.org/10.1002/met.2112.
  8. Fan, D.*, S. J. Greybush, X. Chen, Y. Lu, G. S. Young, and F. Zhang, 2022: Exploring the Role of Deep Moist Convection in the Wavenumber Spectra of Atmospheric Kinetic Energy and Brightness Temperature. Journal of the Atmospheric Sciences, 79(10), 2721-2737, doi:10.1175/JAS-D-21-0285.1.
  9. McMurdie, L. A., G. M. Heymsfield, J. E. Yorks, S. A. Braun, G. Skofronick-Jackson, R. Rauber, S. Yuter, B. Colle, G. M. McFarquahr, M. Poellot, D. R. Novak, T. J. Lang, R. Kroodsma, M. McLinden, M. Oue, P. Kollias, M. R. Kumjian, S. J. Greybush, A. J. Heymsfield, J. A. Finlon, V. McDonald, S. Nicholls, 2022: Chasing Snowstorms: The Investigation of Microphysics and Preciptation for Atlantic Coast-threatening Snowstorms (IMPACTS) Campaign. BAMS, 103(5), E1243-E1269, doi:10.1175/BAMS-D-20-0246.1.
  10. Mooring, T. A., G. E. Davis, and S. J. Greybush, 2022: Low-level jets and the convergence of Mars data assimilation algorithms. J. Geophys. Res. Planets, 127, 2, doi:10.1029/2021JE006968.
  11. Seibert, J. J.*, S. J. Greybush, J. Li, Z. Zhang, and F. Zhang, 2022: Applications of the Geometry-Sensitive Ensemble Mean for Lake-Effect Snowbands and Other Weather Phenomena. Mon. Wea. Rev., 150, 2, 409-429, doi:10.1175/MWR-D-21-0212.1.
  12. Zhang, Y., S. B. Sieron, Y. Lu, X. Chen, R. G. Nystrom*, M. Minamide, M.-Y. Chan, C. M. Hartman^, Z. Yao,J. H. Ruppert, Jr., A. Okazaki^, S. J. Greybush, E. E. Clothiaux, and F. Zhang, 2021: Ensemble-Based Assimilation of Satellite All-Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017). Geophys. Res. Lett., 48, 24, doi:10.1029/2021GL096410.
  13. Okazaki, A.^, T. Miyoshi, K. Yoshimura, S. J. Greybush, and F. Zhang, 2021: Revisiting online and offline data assimilation comparison for paleoclimate reconstruction: an idealized OSSE study. J. Geophys. Res. Atmos., 126, 16, doi:10.1029/2020JD034214.
  14. Nystrom, R. G.*, S. J. Greybush, X. Chen, and F. Zhang, 2021: Potential for new constraints on tropical cyclone surface exchange coefficients through simultaneous ensemble-based state and parameter estimation. Mon. Wea. Rev., 149, 2213-2230, doi:10.1175/MWR-D-20-0259.1.
  15. Ssentongo, P., C. Fronterre, A. Geronimo, S. J. Greybush, P. M. Mbabazi, J. Muvawala, S. Nahalamba, P. O. Omadi, B. T. Opar, S. A. Sinnar, Y. Wang^, A. J. Whalen, L. Held, C. Jewell, A. J. B. Muwanguzi, H. Greatrex, M. N. Norton, P. Diggle, and S. J. Schiff, 2021: Tracking and Predicting the African COVID-19 Pandemic. Proceedings of the National Academies of Science, 118 (28) e2026664118, doi:10.1073/pnas.2026664118.
  16. Naegele, S. M.*, T. C. McCandless, S. J. Greybush, G. S. Young, S. E. Haupt, and M. Al-Rasheedi, 2020: Climatology of Wind Variability for the Shagaya Region in Kuwait. Renewable and Sustainable Energy Reviews, 133, 110089, doi:10.1016/j.rser.2020.110089.
  17. Hermoso, A.^, V. Homar, S. J. Greybush, and D. J. Stensrud, 2020: Tailored ensemble prediction systems: application of seamless scale bred vectors. J. Meteor. Soc. Japan, 98, doi:10.2151/jmsj.2020-053.
  18. Gillespie, H. E.*, S. J. Greybush, and R. J. Wilson, 2020: An investigation of the encirclement of Mars by dust in the 2018 global dust storm using the Ensemble Mars Atmosphere Reanalysis System (EMARS). J. Geophys. Res. Planets, 125, e2019JE006106, doi:10.1029/2019JE006106.

    19. 2014-2019

  19. Eipper, D. T.^, S. J. Greybush, G. S. Young, S. Saslo*, T. D. Sikora, R. D. Clark, 2019: Lake-Effect Snowbands in Baroclinic Environments. Weather and Forecasting, 34, 1657-1674. https://doi.org/10.1175/WAF-D-18-0191.1.
  20. Greybush, S. J., E. Kalnay, R. J. Wilson, R. N. Hoffman, T. Nehrkorn, M. Leidner, J. Eluszkiewicz, H. E. Gillespie*, M. Wespetal^, Y. Zhao^, M. Hoffman, P. Dudas, T. McConnochie, A. Kleinboehl, D. Kass, D. McCleese, and T. Miyoshi, 2019: The Ensemble Mars Atmosphere Reanalysis System (EMARS) Version 1.0. Geoscience Data Journal, https://doi.org/10.18113/D3W375.
  21. Greybush, S. J., H. E. Gillespie*, and R. J. Wilson, 2019: Transient eddies in the TES/MCS Ensemble Mars Atmosphere Reanalysis System (EMARS). Icarus, 317, 158-181, https://doi.org/10.1016/j.icarus.2018.07.001.
  22. Eipper, D. T.^, G. S. Young, S. J. Greybush, S. Saslo*, T. D. Sikora, and R. D. Clark, 2018: Predicting the Inland Penetration of Long-Lake-Axis Parallel Snowbands. Weather and Forecasting, 33, 1435-1451. https://doi.org/10.1175/WAF-D-18-0033.1.
  23. Navarro, T.^, F. Forget, E. Millour, S. J. Greybush, E. Kalnay, and T. Miyoshi, 2017: The Challenge of Atmospheric Data Assimilation on Mars. Earth and Space Science, 4, 690-722. https://doi.org/10.1002/2017EA000274.
  24. Kotsuki, S., S. J. Greybush, and T. Miyoshi, 2017: Can We Optimize the Assimilation Order in the Serial Ensemble Kalman Filter? A Study with the Lorenz-96 Model. Monthly Weather Review, 145, 4977-4995. https://doi.org/10.1175/MWR-D-17-0094.1.
  25. Saslo, S.*, and S. J. Greybush, 2017: Prediction of Lake-Effect Snow Using Convection-Allowing Ensemble Forecasts and Regional Data Assimilation. Weather and Forecasting, 32, 1727-1744. https://doi.org/10.1175/WAF-D-16-0206.1.
  26. Greybush, S. J., S. Saslo*, and R. Grumm, 2017: Assessing the Ensemble Predictability of Precipitation Forecasts for the January 2015 and 2016 East Coast Winter Storms. Weather and Forecasting, 32, 1057-1078. https://doi.org/10.1175/WAF-D-16-0153.1.
  27. Yang, X.^, R. Siddique, S. Sharma^, S. J. Greybush, and A. Mejia, 2017:Postprocessing of GEFS Precipitation Ensemble Reforecasts over the U.S. Mid-Atlantic Region. Monthly Weather Review, 145, 1641-1658. https://doi.org/10.1175/MWR-D-16-0251.1.
  28. Waugh, D. W., A. Toigo, S. Guzewich, S. J. Greybush, R. J. Wilson, and L. Montabone, 2016: Martian Polar Vortices: Comparison of Reanalyses. JGR-Planets, 121, 9, 1770-1785, doi: 10.1002/2016JE005093.
  29. Zhao, Y.^, S. J. Greybush, R. J. Wilson, R. N. Hoffman, and E. Kalnay, 2015: Impact of assimilation window length on diurnal features in a Mars atmospheric analysis. Tellus A, 67, 26042, doi: 10.3402/tellusa.v67.20642.
  30. Navarro, T.^, F. Forget, E. Millour, and S. J. Greybush, 2014: Detection of detached dust layers in the Martian atmosphere from their thermal signature using assimilation. Geophys. Res. Lett., 41, 19, 6620-6626, doi: 10.1002/2014GL061377.A.

    31. 2007-2013

  31. Greybush, S. J., E. Kalnay, M. J. Hoffman, and R. J. Wilson, 2013: Identifying Martian atmospheric instabilities and their physical origins using bred vectors. Q. J. R. Meteorol. Soc., 139, 639653, doi: 10.1002/qj.1990.
  32. Lee, S.-J., J. Lee, S. J. Greybush, M. Kang, and J. Kim, 2013: Spatial and Temporal Variation in PBL Height over the Korean Peninsula in the KMA Operational Regional Model. Advances in Meteorology, 2013, 16 pp., doi: 10.1155/2013/381630.
  33. Greybush, S. J., E. Kalnay, K. Ide, T. Miyoshi, T. McConnochie, M. J. Hoffman, R. N. Hoffman, and R. J. Wilson, 2012: Ensemble Kalman Filter Data Assimilation of Thermal Emission Spectrometer (TES) Profiles into a Mars Global Circulation Model. J. Geophys. Res. Planets, 117, E11008, doi: 10.1029/2012JE004097.
  34. Greybush, S. J., E. Kalnay, T. Miyoshi, K. Ide, and B. Hunt, 2011: Balance and Ensemble Kalman Filter Localization Techniques. Mon. Wea. Rev., 139, 511522, doi: 10.1175/2010MWR3328.1.
  35. Lee, S.-J., D. F. Parrish, S.-Y. Park, W.-S. Wu, S. J. Greybush, W.-J. Lee, and S. J. Lord, 2011: Effects of 2-m air temperature assimilation and a new near-surface observation operator on the NCEP Gridpoint statistical-interpolation system. Asia-Pacific J. Atmos. Sci., 47, 4, 353376, doi: 10.1007/s13143-011-0022-y.
  36. Hoffman, M. J., S. J. Greybush, R. J. Wilson, G. Gyarmati, R. N. Hoffman, E. Kalnay, K. Ide, E. J. Kostelich, T. Miyoshi, and I. Szunyogh, 2010: An ensemble Kalman filter data assimilation system for the martian atmosphere: Implementation and simulation experiments. Icarus, 209, 470481, doi: 10.1016/j.icarus.2010.03.034.
  37. Greybush, S., S. E. Haupt, and G. S. Young, 2008: The Regime Dependence of Optimally Weighted Ensemble Model Consensus Forecasts, Weather and Forecasting, 23, 11461161, doi: 10.1175/2008WAF2007078.1.
  38. Root, B., P. Knight, G. Young, S. Greybush, R. Grumm, R. Holmes, and J. Ross, 2007: A Fingerprinting Technique for Major Weather Events. J. Appl. Meteor. Climatol., 46, 10531066, doi: 10.1175/JAM2509.1.

Return to Top