Model:

Updated:

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

Greenwich Mean Time:

12:00 UTC = 17:00 IST

Resolution:

0.068025° x 0.068025°

Parameter:

Geopotential height Temperature at 100 hPa

Description:

Geopotential height at 100 hPa (solid line)
Temperature at 100 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.

FMI:

At the Finnish Meteorological Institute, results from several numerical weather prediction models are utilized. Most of all, these include products from the European Centre of Medium Range Forecasts (ECMWF), located in Reading in the United Kingdom. For shorter range forecasts, more detailed forecasts are produced in-house using a limited area models (LAMs) called HIRLAM and HARMONIE, which are being developed by FMI as an international co-operation programme with a number of European countries.

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).