Model:

GDAS: "Global Data Assimilation System"

последнее обновление:
4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC
Greenwich Mean Time:
12:00 UTC = 15:00 MSK
Resolution:
0.25° x 0.25°
параметер:
Lifted Index
Description:

The Lifted Index (LI) is defined as a rising parcel's temperature when it reaches the 500 millibars level (at about 5,500m or 18,000 feet asl), subtracted from the actual temperature of the environmental air at 500 mbar. If the Lifted Index is a large negative number, then the parcel will be much warmer than its surroundings, and will continue to rise. Thunderstorms are fueled by strong rising air, thus the Lifted Index is a good measurement of the atmosphere's potential to produce severe thunderstorms.

The Lifted Index (LI)
RANGE IN K
COLOR
AMOUNT OF INSTABILITY
THUNDERSTORM PROBABILITY
more than 11
BLUE
Extremely stable conditions
Thunderstorms unlikely
8 to 11
LIGHT BLUE
Very stable conditions
Thunderstorms unlikely
4 to 7
GREEN
Stable conditions
Thunderstorms unlikely
0 to 3
LIGHT GREEN
Mostly stable conditions
Thunderstorm unlikely
-3 to -1
YELLOW
Slightly unstable
Thunderstorms possible
-5 to -4
ORANGE
Unstable
Thunderstorms probable
-7 to -6
RED
Highly unstable
Severe thunderstorms possible
less than -7
VIOLET
Extremely unstable
Violent thunderstorms, tornadoes possible

GDAS
The Global Data Assimilation System (GDAS) is the system used by the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) model to place observations into a gridded model space for the purpose of starting, or initializing, weather forecasts with observed data. GDAS adds the following types of observations to a gridded, 3-D, model space: surface observations, balloon data, wind profiler data, aircraft reports, buoy observations, radar observations, and satellite observations.
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).