Model:

ECMWF: Global weather forecast model from the "European Centre for Medium-Range Weather Forecasts". ECMWF is now running its own Artificial Intelligence/Integrated Forecasting System (AIFS) as part of its experiment suite. These machine-learning-based models are very fast, and they produce a 10-day forecast with 6-hourly time steps in approximately one minute.

Updated:
4 times per day, from 3:30, 09:30, 15:30 and 21:30 UTC
Greenwich Mean Time:
12:00 UTC = 00:00 NZST
Resolution:
0.25° x 0.25°
Parameter:
Wind at 500 hPa
Description:
This map shows the average wind vector at 500 hPa for every modeled gridpoint (ca. 80 km). Based on the average SLP of about 1010 hPa the equivalent pressure altitude for 500 hPa would be at about 500m a.s.l. (ca. 3000 ft). This map is very useful for gliders and hang-gliders, if their airfield or starting pad is at a low altitude. (wind-converter)
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).