Model:

Updated:

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

Greenwich Mean Time:

12:00 UTC = 13:00 BST

Resolution:

0.01° x 0.01°

Parameter:

Soaring Index

Description:

The Soaring Index map - updated every 6 hours - shows the modelled lift rate by thermals (convective clouds). The index is based on weather information between 5 000 feet (1 524 metres) and 20 000 feet (6 096 metres) and is expressed in Kelvin.
Table 1: Characteristic values for Soaring Index for soaring

Soaring Index	Soaring Conditions
Below -10   -10 to 5   5 to 20   Above 20	Poor   Moderate   Good   Excellent*

Table 2: Critical values for the Soaring Index

Soaring Index	Convective potential
15-20	Isolated showers, 20% risk for thunderstorms
20-25	Occasionally showers, 20-40% risk for thunderstorms
25-30	Frequent showers, 40-60% risk for thunderstorms.
30-35	60-80% risk for thunderstorms.
35 +	>80% risk for thunderstorms

Arome:

Arome
The Arome forecasting system is a blend of the best components from the Méso-NH model, the Aladin model, and the IFS/Arpège data assimilation software. Its focus is on the numerical prediction of intense convective systems over mainland France by 2008. Other important weather phenomena will also begin to be reliably forecast, thanks to a high (kilometric) spatial resolution and the use of regional observing systems. The Arome software is designed to be accessible to a wide research community.

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).