<div class="eI0">
  <div class="eI1">Modell:</div>
  <div class="eI2"><h2>MERRA (MODERN-ERA RETROSPECTIVE ANALYSIS FOR RESEARCH AND APPLICATIONS)</h2></div>
 </div>
 <div class="eI0">
  <div class="eI1">Aktualisierung:</div>
  <div class="eI2">hourly to monthly from 1980 to last month</div>
 </div>
 <div class="eI0">
  <div class="eI1">Greenwich Mean Time:</div>
  <div class="eI2">12:00 UTC = 13:00 MEZ</div>
 </div>
 <div class="eI0">
  <div class="eI1">Aufl&ouml;sung:</div>
  <div class="eI2">0.5&deg; x 0.65&deg;</div>
 </div>
 <div class="eI0">
  <div class="eI1">Parameter:</div>
  <div class="eI2">Vertikalwind in 500 hPa</div>
 </div>
 <div class="eI0">
  <div class="eI1">Beschreibung:</div>
  <div class="eI2">
Die vertikale Bewegung der Luft bestimmt sehr stark das Wetter vor Ort.
W&auml;hrend aufsteigende Luftbewegungen (negative Werte in dieser Karte) 
Wolken und Niederschlag erzeugen k&ouml;nnen, sorgen absinkende Luftbewegungen
(positive Werte in dieser Karte) f&uuml;r eine Wolkenaufl&ouml;sung und 
sonnigeres Wetter. Bei mit sehr starker Geschwindigkeit aufsteigender 
Luft k&ouml;nnen Gewitter und Unwetter entstehen. Weiteren Aufschluss
dar&uuml;ber liefert auch die Karte "Vertikalwind 925 hPa", aus der man
erkennen kann, ob auch in einer tieferen Luftschicht schon Aufsteigen 
vorherrscht. Aus der Multiplikation der Werte (hPa/h) mit ungef&auml;hr 0,30 
ergibt sich der Vertikalwind in cm/s. Der Vertikalwind ist das Ergebniss
von Vorticity- und Temperaturadvektion.
    
  </div>
 </div>
 <div class="eI0">
  <div class="eI1">MERRA:</div>
  <div class="eI2">The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle. Previous long-term reanalyses of the Earth's climate had high levels of uncertainty in precipitation and inter-annual variability. The GEOS-5 data assimilation system used for MERRA implements Incremental Analysis Updates (IAU) to slowly adjust the model states toward the observed state. The water cycle benefits as unrealistic spin down is minimized. In addition, the model physical parameterizations have been tested and evaluated in a data assimilation context, which also reduces the shock of adjusting the model system. Land surface processes are modeled with the state-of-the-art GEOS-5 Catchment hydrology land surface model. MERRA thus makes significant advances in the representation of the water cycle in reanalyses.</br>
</div></div>
<div class="eI0">
  <div class="eI1">Reanalyse:</div>
  <div class="eI2">Retrospective-analyses (or reanalyses) integrate a variety of observing systems with numerical models to produce a temporally and spatially consistent synthesis of observations and analyses of variables not easily observed. The breadth of variables, as well as observational influence, make reanalyses ideal for investigating climate variability. The Modern Era-Retrospective Analysis for Research and Applications supports NASA's Earth science objectives, by applying the state-of-the-art GEOS-5 data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.<br></div></div>
</div>