Model:

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:

Fog Stability Index

Description:

This is a stability index for fog formation. It is from 2WW/TN-79/008, "A New Technique for Forecasting the Occurence of Fog and Low Stratus Ceiling by Use of a Flow Chart".
The equation for the index is:
Fog Stability Index = 2*(t_s - t₈₅₀ + t_s - t_ds ) + W₈₅₀ =
=4t_s - 2(t₈₅₀ + t_ds) + W₈₅₀

Fog risk (FSI)
high	middle	low
FSI < 31	31 < FSI < 55	FSI > 55

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).