<div class="eI0"> <div class="eI1">Model:</div> <div class="eI2"><h2><a href="http://www.knmi.nl/" target="_blank" target="_blank">HARMONIE 40</a>(HARMONIE-AROME Cy40) from the Netherland Weather Service</h2></div> </div> <div class="eI0"> <div class="eI1">Güncelleme:</div> <div class="eI2">4 times per day, from 06:00, 12:00, 18:00, and 00:00 UTC</div> </div> <div class="eI0"> <div class="eI1">Greenwich Mean Time:</div> <div class="eI2">12:00 UTC = 15:00 EET</div> </div> <div class="eI0"> <div class="eI1">Resolution:</div> <div class="eI2">0.025° x 0.037°</div> </div> <div class="eI0"> <div class="eI1">Parametre:</div> <div class="eI2">Fog Stability Index</div> </div> <div class="eI0"> <div class="eI1">Tarife:</div> <div class="eI2"> This is a stability index for fog formation. It is from 2WW/TN-79/008, "A New Technique for Forecasting the Occurence of Fog and Low Stratus Ceiling by Use of a Flow Chart".<br> The equation for the index is:<br> <b><i>Fog Stability Index</i> = 2*(t<sub>s</sub> - t<sub>850</sub> + t<sub>s</sub> - t<sub>ds</sub> ) + W<sub>850 </sub>=</b><br> =4t<b><sub>s</sub> - 2(t<sub>850</sub> + t<sub>ds</sub>) + W<sub>850</sub></b><br> <table width="200" cellspacing="0" cellpadding="0" border="0"> <tr height="30" bgcolor="#E5E5E5"><!-- Row 1 --> <td colspan="3"><font size="3" face="Arial, Helvetica" color="#0000FF">Fog risk (FSI)</td> </tr> <tr height="30"><!-- Row 2 --> <td width="33%" valign="top"><center>high</center></td> <td width="33%" valign="top"><center>middle</center></td> <td width="33%" valign="top"><center>low</center></td> </tr> <tr height="30"><!-- Row 2 --> <td width="33%" valign="top"><center>FSI < 31</center></td> <td width="33%" valign="top"><center>31 < FSI < 55 </center></td> <td width="33%" valign="top"><center>FSI > 55</center></td> </tr> </table> </div> </div> <div class="eI0"> <div class="eI1">HARMONIE:</div> <div class="eI2"><a href="http://www.knmi.nl/" target="_blank">HARMONIE-AROME</a> The non-hydrostatic convection-permitting HARMONIE-AROME model is developed in a code cooperation of the HIRLAM Consortium with Météo-France and ALADIN, and builds upon model components that have largely initially been developed in these two communities. The forecast model and analysis of HARMONIE-AROME are originally based on the AROME-France model from Météo-France (Seity et al, 2011, Brousseau et al, 2011) , but differ from the AROME-France configuration in various respects. A detailed description of the HARMONIE-AROME forecast model setup and its similarities and differences with respect to AROME-France can be found in (Bengtsson et al. 2017). [From: HIRLAM (2017)]<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>