<div class="eI0">
  <div class="eI1">Model:</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">последнее обновление:</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 = 15:00 MSK</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">параметер:</div>
  <div class="eI2">Wind 10 meters above the ground</div>
 </div>
 <div class="eI0">
  <div class="eI1">Description:</div>
  <div class="eI2">
This chart displays the modeled average wind vector in 10 m above the 
ground for every grid point of the model (ca. every 80 km). In general, the 
actual observed wind velocity at 10 m above ground is a little bit 
lower than the modeled one. However, usually the computed wind velocity 
is pretty close to the reality. Therefore this chart is very useful for sailors, 
gliders, hang gliders and balloon pilots. (<a href="javascript:NeuFenster()">wind-converter</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">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.<br>
<br>Wikipedia, Numerical weather prediction, <a href="http://en.wikipedia.org/wiki/Numerical_weather_prediction" target="_blank">http://en.wikipedia.org/wiki/Numerical_weather_prediction</a>(as of Feb. 9, 2010, 20:50 UTC).<br>
</div></div>
</div>