Model:

Ververst:

4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC

Greenwich Mean Time:

12:00 UTC = 13:00 MET

Resolutie:

0.25° x 0.25°

Parameter:

Geopotentiaalhoogte en Temperatuur op 500 hPa

Beschrijving:

Op deze kaart herkent men duidelijk de lange golven (met troggen/ruggen). Zij bepalen voor een belangrijk deel het weer aan de grond ter plaatse. (droog, warm/ nat, koud). De lange golven sturen/hangen nauw samen met de kleinere synoptische verstoringen zoals fronten, depressies en buienlijnen. Daardoor geven hoogtekaarten een goed overzicht van de dynamiek in de atmosfeer.

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.

GDAS

The Global Data Assimilation System (GDAS) is the system used by the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) model to place observations into a gridded model space for the purpose of starting, or initializing, weather forecasts with observed data. GDAS adds the following types of observations to a gridded, 3-D, model space: surface observations, balloon data, wind profiler data, aircraft reports, buoy observations, radar observations, and satellite observations.

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).