Model:

GDAS: "Global Data Assimilation System"

Osvježeno:
4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 GMT
Razlučivost:
0.25° x 0.25°
Parametar:
Cloud cover (low,middle,high,total)
Opis:
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.
GDAS
The Global Data Assimilation System (GDAS) is the system used by the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) model to place observations into a gridded model space for the purpose of starting, or initializing, weather forecasts with observed data. GDAS adds the following types of observations to a gridded, 3-D, model space: surface observations, balloon data, wind profiler data, aircraft reports, buoy observations, radar observations, and satellite observations.
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).