<div class="eI0">
  <div class="eI1">Model:</div>
  <div class="eI2"><h2>MERRA (MODERN-ERA RETROSPECTIVE ANALYSIS FOR RESEARCH AND APPLICATIONS)</h2></div>
 </div>
 <div class="eI0">
  <div class="eI1">Zaktualizowano:</div>
  <div class="eI2">hourly to monthly from 1980 to last month</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">0.5&deg; x 0.65&deg;</div>
 </div>
 <div class="eI0">
  <div class="eI1">parametr:</div>
  <div class="eI2">Sea Level Pressure in hPa (solid lines) and equivalent potential temperature at 700 hPa (dashed and coloured)</div>
 </div>
 <div class="eI0">
  <div class="eI1">Opis:</div>
  <div class="eI2">

The equivalent potential temperature map - updated every 6 hours - shows the modelled equivalent 
potential temperature at the 850hPa level. The equivalent potential temperature is commonly referred 
to as Theta-e (&#952;e). &#952;e is the temperature of a parcel of air after it was lifted until 
it became saturated with water vapour (adibatically). When this parcel becomes saturated and 
condensation begins, the process of condensation releases latent heat into the surrounding air. 
This latent heat further warms the air making the air even more buoyant. We refer to this as a moist 
adiabatic or saturated adiabatic process. Moist adiabatic expansion increases the instability of the parcel. 
If this process of moist adiabatic expansion continues, all of the water may condense out of the rising 
parcel and precipitate out, yielding a dry parcel, and is dropped adiabatically to an atmospheric pressure of 
1000 hPa. The potential temperature of that new dry parcel is called the equivalent potential temperature 
(&#952;e) of the original moist parcel
<BR>
In meteorology &#952;e is used to indicate areas with unstable and thus positively buoyant air. The &#952;e of 
an air parcel increases with increasing temperature and increasing dewpoint as for the latter more latent 
heat that can be released. Therefore, in a region with adequate instability, areas of relatively high &#952;e 
(called &#952;e ridges) are often the burst points for thermodynamically induced thunderstorms and MCS's. 
&#952;e ridges can often be found in those areas experiencing the greatest warm air advection and moisture advection.
(source: <a href="http://www.theweatherprediction.com" target="_blank">the weather prediction</a>
Keep in mind that if a strong cap is in place, convective storms will not occur even if &#952;e is high.
<BR>
As different origins of airmasses largely determine their own &#952;e,
one can use this parameter as a marker. Fronts are easily seen as steep gradients in
&#952;e. The boundary layer &#952;e shows where fronts are located near the surface,
while 700 hPa &#952;e shows where they are near the 3000 m level. In winter it occurs
often that warm fronts do not penetrate into the heavy, cold airmass near the surface.
    
  </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>