<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° x 0.125° (India, South Asia)</div> </div> <div class="eI0"> <div class="eI1">Parameter:</div> <div class="eI2">Maximumtemperatuur op 2 m hoogte</div> </div> <div class="eI0"> <div class="eI1">Beschrijving:</div> <div class="eI2"> Deze kaart toont de berekende maximumtemperatuur van het <a href="http://www.emc.ncep.noaa.gov/gmb/moorthi/gam.html" target="_blank">GFS</a>-model voor 6 - 12 en voor 12 - 18 UTC. Deze waarde wijkt vaak iets af van de werkelijkheid, maar gekoppeld aan: <br> 1. de temperatuur op 850 hPa<br> 2. waarnemingen<br> 3. de ervaring van een meteoroloog,<br> is een zeer bruikbare verwachting van de maximumtemperatuur mogelijk. </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">Dendrogram:</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">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>