Modell:

ECMWF: Global weather forecast model from the "European Centre for Medium-Range Weather Forecasts". ECMWF is now running its own Artificial Intelligence/Integrated Forecasting System (AIFS) as part of its experiment suite. These machine-learning-based models are very fast, and they produce a 10-day forecast with 6-hourly time steps in approximately one minute.

Aktualisierung:
4 times per day, from 3:30, 09:30, 15:30 and 21:30 UTC
Greenwich Mean Time:
12:00 UTC = 14:00 MESZ
Auflösung:
0.25° x 0.25°
Parameter:
Sea Level Pressure in hPa (solid lines) and equivalent potential temperature at 700 hPa (dashed and coloured)
Beschreibung:
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 (θe). θe 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 (θe) of the original moist parcel
In meteorology θe is used to indicate areas with unstable and thus positively buoyant air. The θe 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 θe (called θe ridges) are often the burst points for thermodynamically induced thunderstorms and MCS's. θe ridges can often be found in those areas experiencing the greatest warm air advection and moisture advection. (source: the weather prediction Keep in mind that if a strong cap is in place, convective storms will not occur even if θe is high.
As different origins of airmasses largely determine their own θe, one can use this parameter as a marker. Fronts are easily seen as steep gradients in θe. The boundary layer θe shows where fronts are located near the surface, while 700 hPa θe 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.
NWP:
Numerische Wettervorhersagen sind rechnergestützte Wettervorhersagen. Aus dem Zustand der Atmosphäre zu einem gegebenen Anfangszeitpunkt wird durch numerische Lösung der relevanten Gleichungen der Zustand zu späteren Zeiten berechnet. Diese Berechnungen umfassen teilweise mehr als 14 Tage und sind die Basis aller heutigen Wettervorhersagen.

In einem solchen numerischen Vorhersagemodell wird das Rechengebiet mit Gitterzellen und/oder durch eine spektrale Darstellung diskretisiert, so dass die relevanten physikalischen Größen, wie vor allem Temperatur, Luftdruck, Windrichtung und Windstärke, im dreidimensionalen Raum und als Funktion der Zeit dargestellt werden können. Die physikalischen Beziehungen, die den Zustand der Atmosphäre und seine Veränderung beschreiben, werden als System partieller Differentialgleichungen modelliert. Dieses dynamische System wird mit Verfahren der Numerik, welche als Computerprogramme meist in Fortran implementiert sind, näherungsweise gelöst. Aufgrund des großen Aufwands werden hierfür häufig Supercomputer eingesetzt.


Seite „Numerische Wettervorhersage“. In: Wikipedia, Die freie Enzyklopädie. Bearbeitungsstand: 21. Oktober 2009, 21:11 UTC. URL: http://de.wikipedia.org/w/index.php?title=Numerische_Wettervorhersage&oldid=65856709 (Abgerufen: 9. Februar 2010, 20:46 UTC)