Model:

Updated:

4 times per day, from 08:00, 14:00, 20:00, and 00:00 UTC

Greenwich Mean Time:

12:00 UTC = 00:00 NZST

Resolution:

0.1° x 0.1° (Europe)

0.5° x 0.5°

0.5° x 0.5°

Parameter:

Geopotential height Temperature at 500 hPa

Description:

Geopotential height at 500 hPa (solid line)

Temperature at 500 hPa (colored, dashed)

The maps show the predominant tropospheric waves (trough or ridge). They virtually control the ''weather'' (dry, warm / wet, cold) and the long waves drive the smaller synoptic waves. Thus, this upper-level chart illustrates the dynamics of our atmosphere.

Temperature at 500 hPa (colored, dashed)

The maps show the predominant tropospheric waves (trough or ridge). They virtually control the ''weather'' (dry, warm / wet, cold) and the long waves drive the smaller synoptic waves. Thus, this upper-level chart illustrates the dynamics of our atmosphere.

Arpège:

Arpège

ARPEGE uses a set of primitive equations with a triangular spectral truncation on the horizontal, with a variable horizontal resolution, with a finite elements representation on the vertical and a “sigma-pressure” hybrid vertical coordinate. It also utilizes a temporal two time level semi-implicit semi-lagrangian scheme. The horizontal resolution of the ARPEGE model is around 7.5km over France and 37km over the Antipodes. It has 105 vertical levels, with the first level at 10m above the surface and an upper level at around 70km. Its time step is of 360 seconds.

ARPEGE uses a set of primitive equations with a triangular spectral truncation on the horizontal, with a variable horizontal resolution, with a finite elements representation on the vertical and a “sigma-pressure” hybrid vertical coordinate. It also utilizes a temporal two time level semi-implicit semi-lagrangian scheme. The horizontal resolution of the ARPEGE model is around 7.5km over France and 37km over the Antipodes. It has 105 vertical levels, with the first level at 10m above the surface and an upper level at around 70km. Its time step is of 360 seconds.

NWP:

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.

Wikipedia, Numerical weather prediction, http://en.wikipedia.org/wiki/Numerical_weather_prediction(as of Feb. 9, 2010, 20:50 UTC).

Wikipedia, Numerical weather prediction, http://en.wikipedia.org/wiki/Numerical_weather_prediction(as of Feb. 9, 2010, 20:50 UTC).