Model:

Ensemble forecast charts of several different numerical weather prediction (NWP) models

Updated:
2 times per day, from 05:00 and 17:00 UTC
Greenwich Mean Time:
12:00 UTC = 07:00 EST
Resolution:
Parameter:
CAPE and vertical velocity at 700 hPa
Description:
The Convectively Available Potential Energy (CAPE) map - updated every 6 hours - shows the modelled convectively available potential energy. CAPE represents the amount of buoyant energy (J/kg) available to accelerate a parcel vertically, or the amount of work a parcel does on the environment. The higher the CAPE value, the more energy available to foster storm growth. The potential energy can be converted to kinetic energy reflected in upward motion.
It should be remembered that CAPE represents potential energy, and will only be used should a parcel be lifted to the level of free convection. When values are above 3500 j/kg and storms do develop, they may build rapidly and quickly become severe. Often these storms are referred to as "explosive storms" by chasers and professionals. In a high CAPE environment storms that develop can usually be seen by the human eye as rising rapidly. Higher CAPE typically involves stronger storms with a higher chance of large hail and other severe weather. Note that CAPE is usually of lesser importance than the vertical shear environment for tornadoes. The probability of large hail increases with CAPE, given at least moderate shear(values around 500-1000 J/kg are sufficient).
CAPE is very sensitive to small differences in the moisture and temperature profiles. While the maps indicate 1000 J/kg CAPE at some location, a skew-T thermodynamic diagram at that location may indicate 500-1500 J/kg. (Source: The Lightning Wizard)
Table 1: Characteristic values for CAPE
CAPE value Convective potential
0 Stable
0-1000 Marginally Unstable
1000-2500 Moderately Unstable
2500-3500 Very Unstable
3500 + Extremely Unstable
Spaghetti plots:
are a method of viewing data from an ensemble forecast.
A meteorological variable e.g. pressure, temperature is drawn on a chart for a number of slightly different model runs from an ensemble. The model can then be stepped forward in time and the results compared and be used to gauge the amount of uncertainty in the forecast.
If there is good agreement and the contours follow a recognisable pattern through the sequence then the confidence in the forecast can be high, conversely if the pattern is chaotic i.e resembling a plate of spaghetti then confidence will be low. Ensemble members will generally diverge over time and spaghetti plots are quick way to see when this happens.

Spaghetti plot. (2009, July 7). In Wikipedia, The Free Encyclopedia. Retrieved 20:22, February 9, 2010, from http://en.wikipedia.org/w/index.php?title=Spaghetti_plot&oldid=300824682
NWP:
Numerical weather prediction uses current weather conditions as input into mathematical models of the atmosphere to predict the weather. Although the first efforts to accomplish this were done in the 1920s, it wasn't until the advent of the computer and computer simulation that it was feasible to do in real-time. Manipulating the huge datasets and performing the complex calculations necessary to do this on a resolution fine enough to make the results useful requires the use of some of the most powerful supercomputers in the world. A number of forecast models, both global and regional in scale, are run to help create forecasts for nations worldwide. Use of model ensemble forecasts helps to define the forecast uncertainty and extend weather forecasting farther into the future than would otherwise be possible.

Wikipedia, Numerical weather prediction, http://en.wikipedia.org/wiki/Numerical_weather_prediction(as of Feb. 9, 2010, 20:50 UTC).