Multi-model ensembles provide weather forecasters with a wide range of potential solutions. These data, if properly displayed, provide a more probabilistic approach to forecasting relative to the currently employed single model deterministic approaches currently used. Model diagnostics, such as quasi-geostrophic and frontogenetic computations are often used to validate or improve upon a single forecast from a single deterministic model.

With multi-model ensembles, diagnostics on each forecast member becomes prohibitive, as does the examination of individual forecasts from each ensemble member. Therefore, new display concepts must be employed to maximize the utility of ensembles. In this paper we present several display concepts to assist forecasters in using ensemble forecast data in an operational setting. Traditional spaghetti plots of one or more significant contours are displayed along with the dispersion of all members about the ensemble mean. Consensus forecasts are provided for fields such as mean sea-level pressure, heights, and temperatures. Fields such as quantitative precipitation and the 850 hPa zero Celsius isotherms are displayed using probabilistic methods. All of the displays are focused on providing the forecaster with an efficient means to visualize the envelope of solutions and the higher probability outcome for a particular weather situation.

In this paper, an examination is made of the East Coast Winter storm of 3-4 December 2000. The deterministic forecasts from the operational NCEP stepped terrain (Eta) and the aviation run of the NCEP global spectral model (AVN) are compared to forecasts from the NCEP short-range ensembles forecasts (SREF). Using ensemble probabilistic, consensus, and spaghetti display concepts, it will be shown how these data can be used to improve forecasts associated with a winter storm.