<div class="eI0">
  <div class="eI1">Modelo:</div>
  <div class="eI2"><h2><a href="http://www.emc.ncep.noaa.gov/gmb/gdas/" target="_blank">GDAS</a>: "Global Data Assimilation System"</h2></div>
 </div>
 <div class="eI0">
  <div class="eI1">Actualiza&ccedil;&atilde;o:</div>
  <div class="eI2">4 times per day, from 00:00, 06:00, 12:00 and 18:00 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">0.25&deg; x 0.25&deg;</div>
 </div>
 <div class="eI0">
  <div class="eI1">par&acirc;metro:</div>
  <div class="eI2">Sea Level Pressure in hPa </div>
 </div>
 <div class="eI0">
  <div class="eI1">Descri&ccedil;&atilde;o:</div>
  <div class="eI2">
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.
    
  </div>
 </div>
 <div class="eI0">
  <div class="eI1">Spaghetti plots:</div>
  <div class="eI2">
are a method of viewing data from an ensemble forecast.<br>
A meteorological variable e.g. pressure, temperature is drawn on a chart for a number of slightly different model runs from an ensemble. The model can then be stepped forward in time and the results compared and be used to gauge the amount of uncertainty in the forecast.<br>
If there is good agreement and the contours follow a recognisable pattern through the sequence then the confidence in the forecast can be high, conversely if the pattern is chaotic i.e resembling a plate of spaghetti then confidence will be low. Ensemble members will generally diverge over time and spaghetti plots are quick way to see when this happens.<br>
<br>Spaghetti plot. (2009, July 7). In Wikipedia, The Free Encyclopedia. Retrieved 20:22, February 9, 2010, from <a href="http://en.wikipedia.org/w/index.php?title=Spaghetti_plot&amp;oldid=300824682" target="_blank">http://en.wikipedia.org/w/index.php?title=Spaghetti_plot&amp;oldid=300824682</a>
   </div>
  </div>
 <div class="eI0">
  <div class="eI1">GDAS</div>
  <div class="eI2">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.
</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 previsões do tempo nacionais. O uso de previsões 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>