Modello:

Aggiornato:

2 times per day, from 05:00 and 17:00 UTC

Greenwich Mean Time:

12:00 UTC = 13:00 CET

Risoluzione:

Parametro:

Cloud cover (low,middle,high,total)

Descrizione:

Clouds are vertically divided into three levels: low, middle, and high. Each level is defined by the range of levels at which each type of clouds typically appears.

Level	Polar Region	Temperate Region	Tropical Region
High Clouds	10,000-25,000 ft (3-8 km)	16,500-40,000 ft (5-13 km)	20,000-60,000 ft (6-18 km)
Middle Clouds	6,500-13,000 ft (2-4 km)	6,500-23,000 ft (2-7 km)	6,500-25,000 ft (2-8 km)
Low Clouds	Surface-6,500 ft (0-2 km)	Surface-6,500 ft (0-2 km)	Surface-6,500 ft (0-2 km)

The types of clouds are:

High clouds: Cirrus (Ci), Cirrocumulus (Cc), and Cirrostratus (Cs). They are typically thin and white in appearance, but can appear in a magnificent array of colors when the sun is low on the horizon.

Middle clouds: Altocumulus (Ac), Altostratus (As). They are composed primarily of water droplets, however, they can also be composed of ice crystals when temperatures are low enough.

Low clouds: Cumulus (Cu), Stratocumulus (Sc), Stratus (St), and Cumulonimbus (Cb) are low clouds composed of water droplets.

Spaghetti plots:

are a method of viewing data from an ensemble forecast.
A meteorological variable e.g. pressure, temperature is drawn on a chart for a number of slightly different model runs from an ensemble. The model can then be stepped forward in time and the results compared and be used to gauge the amount of uncertainty in the forecast.
If there is good agreement and the contours follow a recognisable pattern through the sequence then the confidence in the forecast can be high, conversely if the pattern is chaotic i.e resembling a plate of spaghetti then confidence will be low. Ensemble members will generally diverge over time and spaghetti plots are quick way to see when this happens.

Spaghetti plot. (2009, July 7). In Wikipedia, The Free Encyclopedia. Retrieved 20:22, February 9, 2010, from http://en.wikipedia.org/w/index.php?title=Spaghetti_plot&oldid=300824682

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).