Model:

Arome from Meteo France

Ανανέωση:
4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC
Μέσος χρόνος Γκρίνουιτς:
12:00 UTC = 15:00 EEST
Resolution:
0.025° x 0.025°
Παράμετρος:
Relative Humidity at 925 hPa
Description:
This chart shows the relative humidity at Pa. In the forefield of a trough line as well as at and near fronts (Jets), warmer less dense air is forced to ascend. As the ascending air cooles, the relative humidity increases, eventually resulting in condensation and the formation of clouds.This process is known as frontal lifting.
High relative humidity at 925 hPa - equivalent to ca. 2000 ft a.s.l. - indicates the areas of frontal lifting and thus the active zones of the current weather.
Arome:
Arome
The Arome forecasting system is a blend of the best components from the Méso-NH model, the Aladin model, and the IFS/ArpΓ¨ge data assimilation software. Its focus is on the numerical prediction of intense convective systems over mainland France by 2008. Other important weather phenomena will also begin to be reliably forecast, thanks to a high (kilometric) spatial resolution and the use of regional observing systems. The Arome software is designed to be accessible to a wide research community.
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).