<div class="eI0">
  <div class="eI1">Mod&egrave;le:</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>
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 <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>
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 <div class="eI0">
  <div class="eI1">Greenwich Mean Time:</div>
  <div class="eI2">12:00 UTC = 13:00 CET</div>
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 <div class="eI0">
  <div class="eI1">R&eacute;solution:</div>
  <div class="eI2">0.25&deg; x 0.25&deg;</div>
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 <div class="eI0">
  <div class="eI1">Param&egrave;tre:</div>
  <div class="eI2">Temperature at 2 metres above the ground</div>
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  <div class="eI1">Description:</div>
  <div class="eI2">
    
  </div>
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 <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>
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 <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.
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 <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>
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