Model:

Arome from Meteo France

Updated:
4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 BST
Resolution:
0.025° x 0.025°
Parameter:
Temperature at 2 metres above the ground
Description:
Cluster of Ensemble Members:
20 members of an ensemble run are divided into different clusters which means groups with similar members according to the hierarchical "Ward method" The average surface pressure of all members in each cluster are computed and shown as isobares. The number of members in each cluster determines the probability of the forecast (see percentage)
Dendrogram:
A dendrogram shows the multidimensional distances between objects in a tree-like structure. Objects that are closest in a multidimensional data space are connected by a horizontal line forming a cluster. The distance between a given pair of objects (or clusters) are indicated by the height of the horizontal line. [http://www.statistics4u.info/fundstat_germ/cc_dendrograms]. The greater the distance the bigger the differences.
Arome:
Arome
The Arome forecasting system is a blend of the best components from the Méso-NH model, the Aladin model, and the IFS/Arpège 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).