Model:

GDAS: "Global Data Assimilation System"

Updated:
4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC
Greenwich Mean Time:
12:00 UTC = 07:00 EST
Resolution:
0.25° x 0.25°
Parameter:
Dew-point at 2m in hPa/h
Description:
The dew-point is the temperature air would have to be cooled to in order for saturation to occur. The dew-point temperature assumes there is no change in air pressure or moisture content of the air. Dew-point does not change with temperature of the air; very much different from relative humidity.

The dew-point can be used to forecast low temperatures. The low will rarely fall far below the observed dew-point value in the evening (unless a front brings in a different air mass). Once the temperature drops to the dew-point, latent heat must be released to the atmosphere for the condensation process to take effect. This addition of heat offsets some or all of further cooling.
GDAS
The Global Data Assimilation System (GDAS) is the system used by the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) model to place observations into a gridded model space for the purpose of starting, or initializing, weather forecasts with observed data. GDAS adds the following types of observations to a gridded, 3-D, model space: surface observations, balloon data, wind profiler data, aircraft reports, buoy observations, radar observations, and satellite observations.
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).