Michael Scheuerer

Image of Michael Scheuerer


Research Scientist


Attribution and Predictability Assessments




(303) 497-4281



I received my graduate degree and Ph.D. in mathematics with an emphasis on spatial statistics. Since then I have focused on statistical applications in meteorology.

Research Interests

  • Probabilistic weather forecasting
  • Forecast verification



  • Scheuerer, M., and Hamill, T.M. (2019): Probabilistic forecasting of snowfall amounts using a hybrid between a parametric and an analog approach. Monthly Weather Review. 147(3), 1047-1064.
  • Scheuerer, M., and Hamill, T.M. (2018): Generating calibrated ensembles of physically realistic, high-resolution precipitation forecast fields based on GEFS model output. Journal of Hydrometeorology, 19(10), 1651-1670.
  • Worsnop, R.P., Scheuerer, M., Hamill, T.M., and Lundquist J.K. (2018): Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing. Wind Energy Science, 3, 371-393.
  • Scheuerer, M., Hamill, T.M., Whitin, B., He, M. and Henkel A. (2017): A method for preferential selection of dates in the Schaake shuffle approach to constructing spatio-temporal forecast fields of temperature and precipitation. Water Resources Research, 53(4), 3029-3046.
  • Scheuerer, M., Gregory, S., Hamill, T.M. and Shafer, P.E. (2017): Probabilistic precipitation type forecasting based on GEFS ensemble forecasts of vertical temperature profiles. Monthly Weather Review, 145(4), 1401-1412.