Modelo:

ECMWF: Global weather forecast model from the "European Centre for Medium-Range Weather Forecasts". ECMWF is now running its own Artificial Intelligence/Integrated Forecasting System (AIFS) as part of its experiment suite. These machine-learning-based models are very fast, and they produce a 10-day forecast with 6-hourly time steps in approximately one minute.

Actualizado:
4 times per day, from 3:30, 09:30, 15:30 and 21:30 UTC
Tiempo medio de Greenwich:
12:00 UTC = 07:00 MGZ
Resolutión:
0.25° x 0.25°
Parámetro:
Mean relative humidity between ca. 600 and 3000m above the ground level
Descripción:
This map presents the average relative humidity between about 600 and 3000m above the ground - equivalent to the atmospheric layer between 2000 and 10000ft. Although this map is by far not as important as the 'RH 700 hPa' or the 'RH 925 hPa', it gives some hints on cloud formation especially between these two pressure altitudes.
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).