<div class="eI0">
  <div class="eI1">Model:</div>
  <div class="eI2"><h2><a href="http://www.ncmrwf.gov.in/" target="_blank" target="_blank">NCMRWF</a>(National  Centre  for  Medium  Range  Weather  Forecasting from India)</h2></div>
 </div>
 <div class="eI0">
  <div class="eI1">Ververst:</div>
  <div class="eI2">1 times per day, from 00:00 UTC</div>
 </div>
 <div class="eI0">
  <div class="eI1">Greenwich Mean Time:</div>
  <div class="eI2">12:00 UTC = 13:00 MET</div>
 </div>
 <div class="eI0">
  <div class="eI1">Resolutie:</div>
  <div class="eI2">0.125&deg; x 0.125&deg; (India, South Asia)</div>
 </div>
 <div class="eI0">
  <div class="eI1">Parameter:</div>
  <div class="eI2">Dauwpunt op 2 meter hoogte</div>
 </div>
 <div class="eI0">
  <div class="eI1">Beschrijving:</div>
  <div class="eI2">
Het dauwpunt is de temperatuur, waartoe de lucht bij gelijkblijvende
luchtdruk en vochthoeveelheid afgekoeld moet worden, om verzadiging (mist)
te krijgen.<br>
Het dauwpunt levert verschillende gegevens op.<br>
<ul>
<li> Passeren tijdens de nachtperiode geen fronten dan geeft het dauwpunt
van de avond ongeveer de minimumtemperatuur van de nacht aan. 
<li> Ligt de avondtemperatuur dicht bij het dauwpunt dan is mistvorming
waarschijnlijk. 
<li> Uit het verschil tussen temperatuur en dauwpunt kan via een
vuistregel de wolkenbasis worden bepaald  ( (temperatuur-dauwpunt)&times;120 in
meters ). 
<li> Verder geeft het dauwpunt aanwijzingen over de droogeigenschappen en
de comfortzones voor mens en dier. Vanaf een dauwpunt van circa 20 graden
wordt het weer als drukkend en benauwd ervaren. 
</ul>

    
  </div>
 </div>
 <div class="eI0">
  <div class="eI1">NCMRWF:</div>
  <div class="eI2"><a href="http://www.ncmrwf.gov.in/" target="_blank">NCMRWF</a> <br>
This modeling system is an up-graded version of NCEP GFS (as per 28 July 2010). A general description of the modeling system can be found in the following link:<br>
http://www.ncmrwf.gov.in/t254-model/t254_des.pdf<br>
An brief overview of GFS is given below. <br>
------------------------------------------------------ <br>
Dynamics: Spectral, Hybrid sigma-p, Reduced Gaussian grids  <br>
Time integration: Leapfrog/Semi-implicit <br>
Time filter: Asselin <br>
Horizontal diffusion: 8th<br>
 order wavenumber dependent <br>
Orography: Mean orography <br>
Surface fluxes: Monin-obhukov Similarity <br>
Turbulent fluxes: Non-local closure <br>
SW Radiation; RRTM <br>
LW Radiation: RRTM <br>
Deep Convection: SAS <br>
Shallow convection: Mass-flux based <br>
Grid-scale condensation: Zhao Microphysics <br>
Land Surface Processes: NOAH LSM <br>
Cloud generation: Xu and Randal <br>
Rainfall evaporation: Kessler <br>
Air-sea interaction: Roughness length by Charnock <br>
Gravity Wave Drag and mountain blocking: Based on Alpert <br>
Sea-Ice model: Based on Winton <br>
----------------------------------------------- <br>
</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>