BRAMS(Brazilian developments on the Regional Atmospheric Modelling System)
4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 BST
Sea Level Pressure in hPa
The surface chart (also known as surface synoptic chart) presents the distribution of
the atmospheric pressure observed at any given station on the earth's surface
reduced to sea level.
You can read the positions of the controlling weather features (highs, lows, ridges or
troughs) from the distribution of the isobars (lines of equal sea level pressure).
The isobars define the pressure field. The pressure field is the dominating player in
the weather system.
Additionally, this map helps you to identify synoptic-scale waves and gives you a first
estimate on meso-scale fronts.
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.
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).