The National Blend of Global Models (NBM) combines statistically calibrated objective guidance from a wide variety of Numerical Weather Prediction (NWP) systems. The blended fields are compatible with the NWS's National Digital Forecast Database (NDFD) and serve the needs of the entire weather enterprise.

MDL's Statistical Modeling Branch (SMB) applies the Model Output Statistics (MOS) technique to output from the NWS's Global Forecast System (GFS). This statistically calibrated objective guidance includes a wide variety of weather elements and time projections and serves the entire weather enterprise.

MDL's SMB applies the MOS technique to output from the NWS's North American Mesoscale Forecast System (NAM). This statistically calibrated objective guidance includes a wide variety of weather elements and time projections and serves the entire weather enterprise.

MDL's SMB applies the Ensemble Kernel Density MOS (EKDMOS) technique to output from the North American Ensemble Forecast System (NAEFS). This guidance provides accurate and reliable probabilistic guidance for the temperature suite of weather elements.

MDL's SMB applies the MOS technique to output from the European Centre for Medium-Range Weather Forecasting's (ECMWF) models. This statistically calibrated objective guidance includes a wide variety of weather elements and time projections and is provided within NOAA.

SREF Winter Guidance (SWinG) uses output from the Short Range Ensemble Forecast system (SREF) to produce reliable and accurate probability distributions of weather elements at a set of stations. Unlike traditional Model Output Statistics (MOS), SWinG uses statistical postprocessing methods that work with short samples. The most important of these techniques is a modified form of Bayesian Model Averaging (BMA).