Modelo:

GME (Global weather forecast model) from the German Weather Service

Actualizado:
2 times per day, from 10:00 and 23:00 UTC
Tiempo medio de Greenwich:
12:00 UTC = 13:00 CET
Resolutión:
0.25° x 0.25°
Parámetro:
Mean relative humidity between ca. 3000 and 6000 m above the ground
Descripción:
This map presents the mean relative humidity between about 3000 and 6000m a.s.l. - equivalent to the atmospheric layer between 10,000 and 20,000 ft. This is the atmospheric region where middle and high stratus clouds form. They are typically fringing a warm ridge along the anticyclonic sector of a frontal zone. In general, middle and high stratus clouds are a good indicator for the run of the jet stream. Mean Relative Humidity in the layer between about 600 and 3000 m above ground
GME:
GME is the first operational weather forecast model which uses an icosahedral-hexagonal grid covering the globe. In comparison to traditional grid structures like latitude-longitude grids the icosahedral-hexagonal grid offers the advantage of a rather small variability of the area of the grid elements. Moreover, the notorious "pole-problem" of the latitude-longitude grid does not exist in the GME grid.
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).