<div class="eI0">
  <div class="eI1">Model:</div>
  <div class="eI2"><h2>COSMO (Consortium for Small-scale Modeling)</h2></div>
 </div>
 <div class="eI0">
  <div class="eI1">Zaktualizowano:</div>
  <div class="eI2">27 times per day, from 00:00, 03:00, 06:00, 09:00, 12:00, 15:00, 18:00, 21:00 UTC</div>
 </div>
 <div class="eI0">
  <div class="eI1">Czas uniwersalny:</div>
  <div class="eI2">12:00 UTC = 13:00 CET</div>
 </div>
 <div class="eI0">
  <div class="eI1">Rozdzielczo&#347;&#263;:</div>
  <div class="eI2">0.0625&deg; x 0.0625&deg;</div>
 </div>
 <div class="eI0">
  <div class="eI1">parametr:</div>
  <div class="eI2">Precipitation in mm (or litres per square metres)</div>
 </div>
 <div class="eI0">
  <div class="eI1">Opis:</div>
  <div class="eI2">
The precipitation map - updated every 6 hours - shows the modeled precipitation in mm.
The precipitation areas are encircled 
by isohyets - lines with equal amounts of precipitation. However, modeling precipitation is 
still not very reliable. If you compare the modeled results with observed values you will 
realize that the model is nothing better than a first order approach. Yet this chart is of some 
use for forecasters.<br>
Note: Based on international convention meteorologists use the metric system. 100 mm of 
precipitation is equivalent to roughly 4 inches.
    
  </div>
 </div>
 <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>
   </div>
  </div>
 <div class="eI0">
  <div class="eI1">COSMO-DE:</div>
<a href="http://www.cosmo-model.org/" target="_blank">COSMO</a> <br>
  <div class="eI2">The COSMO-Model is a nonhydrostatic limited-area atmospheric prediction model. It has been designed for both operational numerical weather prediction (NWP) and various scientific applications on the meso-β and meso-γ scale. The COSMO-Model is based on the primitive thermo-hydrodynamical equations describing compressible flow in a moist atmosphere. The model equations are formulated in rotated geographical coordinates and a generalized terrain following height coordinate. A variety of physical processes are taken into account by parameterization schemes. <br> The basic version of the COSMO-Model (formerly known as Lokal Modell (LM)) has been developed at the Deutscher Wetterdienst (DWD). The COSMO-Model and the triangular mesh global gridpoint model GME form – together with the corresponding data assimilation schemes – the NWP-system at DWD, which is run operationally since end of 1999. The subsequent developments related to the model have been organized within COSMO, the Consortium for Small-Scale Modelling. COSMO aims at the improvement, maintenance and operational application of the non-hydrostatic limited-area modelling system, which is now consequently called the COSMO-Model. </b>
</div></div>
 <div class="eI0">
  <div class="eI1">NWP:</div>
  <div class="eI2">Numeryczna prognoza pogody - ocena stanu atmosfery w przysz&#322;o&#347;ci na podstawie znajomo&#347;ci warunk&oacute;w pocz&#261;tkowych oraz si&#322; dzia&#322;aj&#261;cych na powietrze. Numeryczna prognoza oparta jest na rozwi&#261;zaniu r&oacute;wna&#324; ruchu powietrza za pomoc&#261; ich dyskretyzacji i wykorzystaniu do oblicze&#324; maszyn matematycznych.<br>
Pocz&#261;tkowy stan atmosfery wyznacza si&#281; na podstawie jednoczesnych pomiar&oacute;w na ca&#322;ym globie ziemskim. R&oacute;wnania ruchu cz&#261;stek powietrza wprowadza si&#281; zak&#322;adaj&#261;c, &#380;e powietrze jest ciecz&#261;. R&oacute;wna&#324; tych nie mo&#380;na rozwi&#261;zać w prosty spos&oacute;b. Kluczowym uproszczeniem, wymagaj&#261;cym jednak zastosowania komputer&oacute;w, jest za&#322;o&#380;enie, &#380;e atmosfer&#281; mo&#380;na w przybli&#380;eniu opisać jako wiele dyskretnych element&oacute;w na kt&oacute;re oddzia&#322;ywaj&#261; rozmaite procesy fizyczne. Komputery wykorzystywane s&#261; do oblicze&#324; zmian w czasie temperatury, ci&#347;nienia, wilgotno&#347;ci, pr&#281;dko&#347;ci przep&#322;ywu, i innych wielko&#347;ci opisuj&#261;cych element powietrza. Zmiany tych w&#322;asno&#347;ci fizycznych powodowane s&#261; przez rozmaitego rodzaju procesy, takie jak wymiana ciep&#322;a i masy, opad deszczu, ruch nad g&oacute;rami, tarcie powietrza, konwekcj&#281;, wpływ promieniowania s&#322;onecznego, oraz wp&#322;yw oddziaływania z innymi cz&#261;stkami powietrza. Komputerowe obliczenia dla wszystkich element&oacute;w atmosfery daj&#261; stan atmosfery w przysz&#322;o&#347;ci czyli prognoz&#281; pogody.<br>
W dyskretyzacji r&oacute;wna&#324; ruchu powietrza wykorzystuje si&#281; metody numeryczne r&oacute;wna&#324; r&oacute;&#380;niczkowych cz&#261;stkowych - st&#261;d nazwa numeryczna prognoza pogody.<br>
<br>Zobacz Wikipedia, Numeryczna prognoza pogody, <a href="http://pl.wikipedia.org/wiki/Numeryczna_prognoza_pogody" target="_blank">http://pl.wikipedia.org/wiki/Numeryczna_prognoza_pogody</a> (dost&#281;p lut. 9, 2010, 20:49 UTC).<br>
</div></div>
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