Modèle:

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

Mise à jour:
1 times per day, from 00:00 UTC
Greenwich Mean Time:
12:00 UTC = 13:00 CET
Résolution:
0.125° x 0.125° (India, South Asia)
Paramètre:
Geopotential height (tens of m) at 925 hPa (solid line) and Temperature (°C) at 925 hPa (coloured, dashed line)
Description:
This chart helps to identify areas of densely packed isotherms (lines of equal temperature) indicating a front. Aside from this you can use the modeled temperature in 925 hPa (2000 ft a.s.l.) to make a rough estimate on the expected maximum temperature in 2m above the ground. However, this method does not apply to (winter) inversions.
Cluster of Ensemble Members:
20 members of an ensemble run are divided into different clusters which means groups with similar members according to the hierarchical "Ward method" The average surface pressure of all members in each cluster are computed and shown as isobares. The number of members in each cluster determines the probability of the forecast (see percentage)
Dendrogramme:
A dendrogram shows the multidimensional distances between objects in a tree-like structure. Objects that are closest in a multidimensional data space are connected by a horizontal line forming a cluster. The distance between a given pair of objects (or clusters) are indicated by the height of the horizontal line. [http://www.statistics4u.info/fundstat_germ/cc_dendrograms]. The greater the distance the bigger the differences.
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:
La prévision numérique du temps (PNT) est une application de la météorologie et de l'informatique. Elle repose sur le choix d'équations mathématiques offrant une proche approximation du comportement de l'atmosphère réelle. Ces équations sont ensuite résolues, à l'aide d'un ordinateur, pour obtenir une simulation accélérée des états futurs de l'atmosphère. Le logiciel mettant en œuvre cette simulation est appelé un modèle de prévision numérique du temps.


Prévision numérique du temps. (2009, décembre 12). Wikipédia, l'encyclopédie libre. Page consultée le 20:48, février 9, 2010 à partir de http://fr.wikipedia.org/w/index.php?title=Pr%C3%A9vision_num%C3%A9rique_du_temps&oldid=47652746.