Model:
GDAS: "Global Data Assimilation System"
Updated:
4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC
Greenwich Mean Time:
12:00 UTC = 12:00 GMT
Resolution:
0.25° x 0.25°
Parameter:
Geopotential in 850 hPa (solid, black lines) and Temperature advection in K/6h (colored lines)
Description:
The map "T-Adv 850" shows the advection of cold or warm air at 850 hPa
level. Negative values indicate cold advection, while positive values
indicate warm air advection. Advection of warm or cold air causes the
geopotential height to respectively rise or drop, producing vertical rising
and sinking motion of air. There is, however, not a direct relationship
between temperature advection and resultant vertical motion in the
atmosphere since other lifting and sinking mechanisms can complicate the
picture, e.g. vorticity advection (see "V-Adv maps").
In weather forecasting, temperature advection maps are often used to locate
the postion of wam and cold fronts. Cold advection is common behind cold
fronts, while warm advection is common behind warm fronts and ahead of cold
fronts. Higher in the atmosphere temperature advection is getting less
pronounced, as horizontal much more uniform in temperature and the flow is
more zonal.
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).