Model:

Ανανέωση:

1 times per day, from 00:00 UTC

Μέσος χρόνος Γκρίνουιτς:

12:00 UTC = 14:00 EET

Resolution:

0.125° x 0.125° (India, South Asia)

Παράμετρος:

Sea Level Pressure in hPa (solid lines) and equivalent potential temperature at 700 hPa (dashed and coloured)

Description:

The equivalent potential temperature map - updated every 6 hours - shows the modelled equivalent potential temperature at the 850hPa level. The equivalent potential temperature is commonly referred to as Theta-e (θe). θe is the temperature of a parcel of air after it was lifted until it became saturated with water vapour (adibatically). When this parcel becomes saturated and condensation begins, the process of condensation releases latent heat into the surrounding air. This latent heat further warms the air making the air even more buoyant. We refer to this as a moist adiabatic or saturated adiabatic process. Moist adiabatic expansion increases the instability of the parcel. If this process of moist adiabatic expansion continues, all of the water may condense out of the rising parcel and precipitate out, yielding a dry parcel, and is dropped adiabatically to an atmospheric pressure of 1000 hPa. The potential temperature of that new dry parcel is called the equivalent potential temperature (θe) of the original moist parcel
In meteorology θe is used to indicate areas with unstable and thus positively buoyant air. The θe of an air parcel increases with increasing temperature and increasing dewpoint as for the latter more latent heat that can be released. Therefore, in a region with adequate instability, areas of relatively high θe (called θe ridges) are often the burst points for thermodynamically induced thunderstorms and MCS's. θe ridges can often be found in those areas experiencing the greatest warm air advection and moisture advection. (source: the weather prediction Keep in mind that if a strong cap is in place, convective storms will not occur even if θe is high.
As different origins of airmasses largely determine their own θe, one can use this parameter as a marker. Fronts are easily seen as steep gradients in θe. The boundary layer θe shows where fronts are located near the surface, while 700 hPa θe shows where they are near the 3000 m level. In winter it occurs often that warm fronts do not penetrate into the heavy, cold airmass near the surface.

NCMRWF:

NCMRWF
This modeling system is an up-graded version of NCEP GFS (as per 28 July 2010). A general description of the modeling system can be found in the following link:
http://www.ncmrwf.gov.in/t254-model/t254_des.pdf
An brief overview of GFS is given below.
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Dynamics: Spectral, Hybrid sigma-p, Reduced Gaussian grids
Time integration: Leapfrog/Semi-implicit
Time filter: Asselin
Horizontal diffusion: 8th
order wavenumber dependent
Orography: Mean orography
Surface fluxes: Monin-obhukov Similarity
Turbulent fluxes: Non-local closure
SW Radiation; RRTM
LW Radiation: RRTM
Deep Convection: SAS
Shallow convection: Mass-flux based
Grid-scale condensation: Zhao Microphysics
Land Surface Processes: NOAH LSM
Cloud generation: Xu and Randal
Rainfall evaporation: Kessler
Air-sea interaction: Roughness length by Charnock
Gravity Wave Drag and mountain blocking: Based on Alpert
Sea-Ice model: Based on Winton
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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).