Model:

последнее обновление:

4 times per day, from 3:30, 09:30, 15:30 and 21:30 UTC

Greenwich Mean Time:

12:00 UTC = 15:00 MSK

Resolution:

0.25° x 0.25°

параметер:

Geopotential in 500 hPa (solid, black lines) and Temperature advection in K/6h (colored lines)

Description:

The map "T-Adv 500" shows the advection of cold or warm air at 500 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.

GFS: upcoming NCEP model upgrades

The Global Forecast System (GFS) is a global numerical weather prediction computer model run by NOAA. This mathematical model is run four times a day and produces forecasts up to 16 days in advance, but with decreasing spatial and temporal resolution over time it is widely accepted that beyond 7 days the forecast is very general and not very accurate.

The resolution of the model horizontally, it divides the surface of the earth into 20 kilometre grid squares; vertically, it divides the atmosphere into 64 layers and temporally, it produces a forecast for every 3rd hour for the first 240 hours, after that they are produced for every 6th hour.

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).