Modello:

Aggiornato:

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

Greenwich Mean Time:

12:00 UTC = 13:00 CET

Risoluzione:

0.068025° x 0.068025°

Parametro:

Geopotential height (tens of m) at 925 hPa (solid line) and Temperature (°C) at 925 hPa (coloured, dashed line)

Descrizione:

This chart helps to identify areas of densely packed isotherms (lines of equal temperature) indicating a front. Aside from this you can use the modeled temperature in 925 hPa (2000 ft a.s.l.) to make a rough estimate on the expected maximum temperature in 2m above the ground. However, this method does not apply to (winter) inversions.

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)

Dendrogramma:

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.

FMI:

At the Finnish Meteorological Institute, results from several numerical weather prediction models are utilized. Most of all, these include products from the European Centre of Medium Range Forecasts (ECMWF), located in Reading in the United Kingdom. For shorter range forecasts, more detailed forecasts are produced in-house using a limited area models (LAMs) called HIRLAM and HARMONIE, which are being developed by FMI as an international co-operation programme with a number of European countries.

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).