Model:
557WW: "557th Weather Wing Ensemble" The US Air Force’s 557th Weather Wing creates the Global Ensemble Prediction Suite (GEPS) twice per day by ingesting 63 global forecast model runs produced by three operational numerical modeling centers and creating tailored statistical ensemble forecasts. Products include probabilities for precipitation and snowfall, and means/standard deviations of temperature, wind, pressure, height, and relative humidity. 240 hours of one-degree gridded forecast output is produced at 6 hour intervals on the 00Z and 12Z cycle.
Updated:
2 times per day, from 06:00 and 18:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 CET
Parameter:
Precipitation in mm (or litres per square metres)
Description:
The precipitation map - updated every 6 hours - shows the modeled precipitation in mm.
The precipitation areas are encircled
by isohyets - lines with equal amounts of precipitation. However, modeling precipitation is
still not very reliable. If you compare the modeled results with observed values you will
realize that the model is nothing better than a first order approach. Yet this chart is of some
use for forecasters.
Note: Based on international convention meteorologists use the metric system. 100 mm of
precipitation is equivalent to roughly 4 inches.
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.
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).