Model:

ICON(ICOsahedral Nonhydrostatic general circulation model) from the German Weather Service

Ανανέωση:
2 times per day, from 00:00 and 12:00 UTC
Μέσος χρόνος Γκρίνουιτς:
12:00 UTC = 15:00 EEST
Resolution:
0.02° x 0.02°
Παράμετρος:
Relative Humidity at 850 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 850 hPa - equivalent to ca. 5000 ft a.s.l. - indicates the areas of frontal lifting and thus the active zones of the current weather.
ICON-D2:
ICON-D2 The ICON dynamical core is a development initiated by the Max Planck Institute for Meteorology (MPI-M) and the Opens external link in current windowGermany Weather Service (DWD). This dynamical core is designed to better tap the potential of new generations of high performance computing, to better represent fluid conservation properties that are increasingly important for modelling the Earth system, to provide a more consistent basis for coupling the atmosphere and ocean and for representing subgrid-scale heterogeneity over land, and to allow regionalization and limited area implementations.
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).