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Th 28.05 10 GMT

Jet stream/SLP CPTEC/BRAMS Model

Model:

BRAMS(Brazilian developments on the Regional Atmospheric Modelling System)

Updated:
4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 BST
Resolution:
0.5° x 0.5°
Parameter:
Sea level pressure and Wind at 300 hPa
Description:
Sea level pressure and Wind at 300 hPa
BRAMS:
BRAMS
The BRAMS Brazilian developments on the Regional Atmospheric Modelling System is a project originaly developed by ATMET, IME/USP, IAG/USP and CPTEC/INPE, funded by FINEP (Brazilian Funding Agency), aimed to produce a new version of RAMS tailored to the tropics. The main objective is to provide a single model to Brazilian Regional Weather Centers. The BRAMS/RAMS model is a multipurpose, numerical prediction model designed to simulate atmospheric circulations spanning in scale from hemispheric scales down to large eddy simulations (LES) of the planetary boundary layer. After the version 4.2 the code is developed only by CPTEC/INPE team developers. The BRAMS uses the Cathedral model, but code developed between releases is restricted to an exclusive group of software developers. The software is under CC-GNU GPL license and some parts of code may receives other restricted licenses. The BRAMS incorporate a tracer transport model and chemical model (CCATT) and becomes a unified version, BRAMS 5.x.
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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