In this presentation we show how these two different concepts - a parametric, regression-type approach and the analog method - can be combined in a way that leverages the respective advantages. Predictive distributions of precipitation amounts are obtained using the CSGD method, and quantile forecasts derived from it are then used together with ensemble forecasts of temperature and wind speed to find historical dates where these quantities were similar. The corresponding, observed snowfall amounts on these dates can then be used to compose an ensemble that represents the uncertainty about future snowfall. We demonstrate this approach with reforecast data (Hamill et al. 2012) from the Global Ensemble Forecast System (GEFS) and NOHRSC snowfall analyses.
Hamill, T.M., Bates, G.T., Whitaker. J.S., Murray D.R., Fiorino, M.., Galarneau, Jr., T.J., Zhu, Y. , and Lapenta, W. (2013): NOAA's second-generation global medium-range ensemble reforecast data set. Bull Amer. Meteor. Soc., 94, 1553-1565.
Scheuerer, M. and Hamill, T.M. (2015): Statistical post-processing of ensemble precipitation forecasts by fitting censored, shifted Gamma distributions. Monthly Weather Review, 143(11), 4578-4596.