<div class="eI0">
  <div class="eI1">Mod&egrave;le:</div>
  <div class="eI2"><h2><a href="http://www.meteo.be" target="_blank">ALARO</a>: "Data Source: Royal Meteorological Institute of Belgium (RMI) "</h2></div>
 </div>
 <div class="eI0">
  <div class="eI1">Mise &agrave; jour:</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 = 13:00 CET</div>
 </div>
 <div class="eI0">
  <div class="eI1">R&eacute;solution:</div>
  <div class="eI2">0.053&deg; x 0.053&deg;</div>
 </div>
 <div class="eI0">
  <div class="eI1">Param&egrave;tre:</div>
  <div class="eI2">Sea Level Pressure in hPa </div>
 </div>
 <div class="eI0">
  <div class="eI1">Description:</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">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">Dendrogramme:</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">NWP:</div>
  <div class="eI2">La pr&eacute;vision num&eacute;rique du temps (PNT) est une application de la m&eacute;t&eacute;orologie et de l'informatique. Elle repose sur le choix d'&eacute;quations math&eacute;matiques offrant une proche approximation du comportement de l'atmosph&egrave;re r&eacute;elle. Ces &eacute;quations sont ensuite r&eacute;solues, &agrave; l'aide d'un ordinateur, pour obtenir une simulation acc&eacute;l&eacute;r&eacute;e des &eacute;tats futurs de l'atmosph&egrave;re. Le logiciel mettant en &oelig;uvre cette simulation est appel&eacute; un mod&egrave;le de pr&eacute;vision num&eacute;rique du temps.<br><br>
<br>Pr&eacute;vision num&eacute;rique du temps. (2009, d&eacute;cembre 12). Wikip&eacute;dia, l'encyclop&eacute;die libre. Page consult&eacute;e le 20:48, f&eacute;vrier 9, 2010 &agrave; partir de <a href="http://fr.wikipedia.org/w/index.php?title=Pr%C3%A9vision_num%C3%A9rique_du_temps&oldid=47652746" target="_blank">http://fr.wikipedia.org/w/index.php?title=Pr%C3%A9vision_num%C3%A9rique_du_temps&oldid=47652746</a>.<br>
</div></div>
</div>