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Αρχείο - GDAS - Height/Temp. 500 hPa P

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Πεμ 28.03 13 UTC

Height/Temp. 500 hPa GDAS Reanalysis

Model:

GDAS: "Global Data Assimilation System"

Ανανέωση:
4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC
Μέσος χρόνος Γκρίνουιτς:
12:00 UTC = 14:00 EET
Resolution:
0.25° x 0.25°
Παράμετρος:
Geopotential height Temperature at 500 hPa
Description:
Geopotential height at 500 hPa (solid line)
Temperature at 500 hPa (colored, dashed)

The maps show the predominant tropospheric waves (trough or ridge). They virtually control the ''weather'' (dry, warm / wet, cold) and the long waves drive the smaller synoptic waves. Thus, this upper-level chart illustrates the dynamics of our atmosphere.
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).



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