<div class="eI0">
  <div class="eI1">Modelo:</div>
  <div class="eI2"><h2><a href="http://brams.cptec.inpe.br/" target="_blank" target="_blank">BRAMS</a>(Brazilian developments on the Regional Atmospheric Modelling System)</h2></div>
 </div>
 <div class="eI0">
  <div class="eI1">Actualiza&ccedil;&atilde;o:</div>
  <div class="eI2">4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC</div>
 </div>
 <div class="eI0">
  <div class="eI1">Greenwich Mean Time:</div>
  <div class="eI2">12:00 UTC = 12:00 WET</div>
 </div>
 <div class="eI0">
  <div class="eI1">Resolution:</div>
  <div class="eI2">0.5&deg; x 0.5&deg;</div>
 </div>
 <div class="eI0">
  <div class="eI1">par&acirc;metro:</div>
  <div class="eI2">Precipitation in mm (or litres per square metres)</div>
 </div>
 <div class="eI0">
  <div class="eI1">Descri&ccedil;&atilde;o:</div>
  <div class="eI2">
The precipitation map - updated every 6 hours - shows the modeled precipitation in mm.
The precipitation areas are encircled 
by isohyets - lines with equal amounts of precipitation. However, modeling precipitation is 
still not very reliable. If you compare the modeled results with observed values you will 
realize that the model is nothing better than a first order approach. Yet this chart is of some 
use for forecasters.<br>
Note: Based on international convention meteorologists use the metric system. 100 mm of 
precipitation is equivalent to roughly 4 inches.
    
  </div>
 </div>
 <div class="eI0">
  <div class="eI1">Cluster of Ensemble Members:</div>
  <div class="eI2">
20 members of an ensemble run are divided into different clusters which means groups with similar members according to the hierarchical "Ward method"
The average surface pressure of all members in each cluster are computed and shown as isobares.
The number of members in each cluster determines the probability of the forecast (see percentage)
   </div>
  </div>
 <div class="eI0">
  <div class="eI1">Dendrograma:</div>
  <div class="eI2">
A dendrogram shows the multidimensional distances between objects in a tree-like structure.  Objects that are closest in a multidimensional data space are connected by a horizontal line forming a cluster. The distance between a given pair of objects (or clusters) are indicated by the height of the horizontal line.
[http://www.statistics4u.info/fundstat_germ/cc_dendrograms]. The greater the distance the bigger the differences.
   </div>
  </div>
 <div class="eI0">
  <div class="eI1">BRAMS:</div>
  <div class="eI2"><a href="http://brams.cptec.inpe.br/" target="_blank">BRAMS</a> <br>
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.
</div></div>
 <div class="eI0">
  <div class="eI1">NWP:</div>
  <div class="eI2">A previs&atilde;o num&eacute;rica do tempo usa o estado instant&acirc;neo da atmosfera como dados de entrada para modelos matem&aacute;ticos da atmosfera, com vista &agrave; previs&atilde;o do estado do tempo.<br>
Apesar dos primeiros esforços para conseguir prever o tempo tivessem sido dados na d&eacute;cada de 1920, foi apenas com o advento da era dos computadores que foi possível realiz&aacute;-lo em tempo real. A manipulaç&atilde;o de grandes conjuntos de dados e a realizaç&atilde;o de c&aacute;lculos complexos para o conseguir com uma resoluç&atilde;o suficientemente elevada para produzir resultados úteis requer o uso dos supercomputadores mais potentes do mundo. Um conjunto de modelos de previs&atilde;o, quer &agrave; escala global quer &agrave; escala regional, s&atilde;o executados para criar previsþes do tempo nacionais. O uso de previsþes com modelos semelhantes ("model ensembles") ajuda a definir a incerteza da previs&atilde;o e estender a previs&atilde;o do tempo bastante mais no futuro, o que n&atilde;o seria possível conseguir de outro modo.<br>
<br>Contribuidores da Wikip&eacute;dia, "Previs&atilde;o num&eacute;rica do tempo," Wikip&eacute;dia, a enciclop&eacute;dia livre, <a href="http://pt.wikipedia.org/w/index.php?title=Previs%C3%A3o_num%C3%A9rica_do_tempo&amp;oldid=17351675" target="_blank">http://pt.wikipedia.org/w/index.php?title=Previs%C3%A3o_num%C3%A9rica_do_tempo&oldid=17351675</a> (accessed fevereiro 9, 2010). <br>
</div></div>
</div>