Model:

Updated:

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

Greenwich Mean Time:

12:00 UTC = 12:00 GMT

Resolution:

0.1° x 0.1°

Parameter:

Sea Level Pressure in hPa

Description:

The surface chart (also known as surface synoptic chart) presents the distribution of the atmospheric pressure observed at any given station on the earth's surface reduced to sea level. You can read the positions of the controlling weather features (highs, lows, ridges or troughs) from the distribution of the isobars (lines of equal sea level pressure). The isobars define the pressure field. The pressure field is the dominating player in the weather system. Additionally, this map helps you to identify synoptic-scale waves and gives you a first estimate on meso-scale fronts.

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.

HIRLAM:

HIRLAMThe international HIRLAM project is a continuing effort to develop and maintain a state of the art high resolution limited area model for operational use in the participating institutes. By 2001 HIRLAM research developments had outstripped the operational HIRLAM system at KNMI through a substantial increase in model resolution and many improvements in the model formulation.

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).