Model:

GDAS: "Global Data Assimilation System"

Güncelleme:
4 times per day, from 00:00, 06:00, 12:00 and 18:00 UTC
Greenwich Mean Time:
12:00 UTC = 15:00 EET
Resolution:
0.25° x 0.25°
Parametre:
Yükseltgenmiş Indeks
Tarife:

Yükseltgenmiş Indeks (LI), 500 milibara( yaklaşık 5.5000m veya 18,000 fit) ulaşan ve 500mbar’daki çevresel sıcaklık ile gerçek sıcaklığın farkı ile bulunan, yükselen hava kütlesinin sıcaklığı olarak tanımlanır. Eğer Yükseltgenmiş Indeks büyük negatif bir sayı ise, yükselen hava kütlesi etrafına oranla daha sıcaktır ve yükselmeye devam eder. Gökgürültüsü ve orajlar hızla yükselen hava ile beslenirler, bu yüzden Yükseltgenmiş Indeks atmosferin üretebileceği potansiyel yıldırım ve şimşek riski açısından iyi bir ölçektir.

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).