Modello:

NCMRWF(National Centre for Medium Range Weather Forecasting from India)

Aggiornato:
1 times per day, from 00:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 CET
Risoluzione:
0.125° x 0.125° (India, South Asia)
Parametro:
Cloud cover (low,middle,high,total)
Descrizione:
Clouds are vertically divided into three levels: low, middle, and high. Each level is defined by the range of levels at which each type of clouds typically appears.

Level Polar Region Temperate Region Tropical Region
High Clouds 10,000-25,000 ft
(3-8 km)
16,500-40,000 ft
(5-13 km)
20,000-60,000 ft
(6-18 km)
Middle Clouds 6,500-13,000 ft
(2-4 km)
6,500-23,000 ft
(2-7 km)
6,500-25,000 ft
(2-8 km)
Low Clouds Surface-6,500 ft
(0-2 km)
Surface-6,500 ft
(0-2 km)
Surface-6,500 ft
(0-2 km)


The types of clouds are:

High clouds: Cirrus (Ci), Cirrocumulus (Cc), and Cirrostratus (Cs). They are typically thin and white in appearance, but can appear in a magnificent array of colors when the sun is low on the horizon.

Middle clouds: Altocumulus (Ac), Altostratus (As). They are composed primarily of water droplets, however, they can also be composed of ice crystals when temperatures are low enough.

Low clouds: Cumulus (Cu), Stratocumulus (Sc), Stratus (St), and Cumulonimbus (Cb) are low clouds composed of water droplets.
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).