Model:

Osvježeno:

4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC

Greenwich Mean Time:

12:00 UTC = 13:00 GMT

Razlučivost:

0.1° x 0.1° (Europe)
0.5° x 0.5°

Parametar:

Geopotential height Temperature at 500 hPa

Opis:

Geopotential height at 500 hPa (solid line)
Temperature at 500 hPa (colored, dashed)

The maps show the predominant tropospheric waves (trough or ridge). They virtually control the ''weather'' (dry, warm / wet, cold) and the long waves drive the smaller synoptic waves. Thus, this upper-level chart illustrates the dynamics of our atmosphere.

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.

Arpège:

Arpège
ARPEGE uses a set of primitive equations with a triangular spectral truncation on the horizontal, with a variable horizontal resolution, with a finite elements representation on the vertical and a “sigma-pressure” hybrid vertical coordinate. It also utilizes a temporal two time level semi-implicit semi-lagrangian scheme. The horizontal resolution of the ARPEGE model is around 7.5km over France and 37km over the Antipodes. It has 105 vertical levels, with the first level at 10m above the surface and an upper level at around 70km. Its time step is of 360 seconds.

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).