Modelo:

Actualização:

1 times per day, from 00:00 UTC

Greenwich Mean Time:

12:00 UTC = 12:00 WET

Resolution:

0.125° x 0.125° (India, South Asia)

parâmetro:

Wet bulb potential temperature (θw) in C

Descrição:

The ThetaW map - updated every 6 hours - shows the modelled wet bulb potential temperature at the 850hPa level. The theta w (θw) areas are encircled by isotherms - lines connecting locations with equal wet bulb potential temperature. When an air parcel, starting from a certain pressure level, is lifted dry adiabatically until saturation and subsequently is brought to a level of 1000 hPa along a saturated adiabat it reaches what is called the saturated potential wet-bulb temperature: θw. As long as an air parcel undergoes an adiabatisch process, be it either dry or saturated, and in both descending and ascending motions θw does not change. Even when precipitation is evaporating adiabatically θw does not change, therefore θw is "conservative".
An air mass is defined as a quantity of air with a horizontal extent of several hundred or thousand kilometres and a thickness of several kilometres, which is homogeneous in thermal characteristics. Such an air mass may form when air has been over an extensive and homogeneous part of the Earth's surface during a considerable amount of time. This is the so-called source area. In due time, by means of radiative exchange processes and contact with the Earth's surface, an equilibrium develops which is evident from the fact that θw has approximately the same value in the entire air mass both horizontally and vertically, Hence θw can be used to characterise an air mass, with both sensible and latent heat are accounted for.
Depending on possible source areas several main air mass types can be distinguished: polar air (P), midlatitude air (ML) and (sub)tropical air (T). Also, but these are less important arctic air (A) and equatorial air (E). These five main types can be subdivided in continental air (c) and maritime air (m).

Table 1: Characteristic values for θw at 850 hPa (in °C) for various air masses.

Summer		Winter
cA < 7	mA < 9	cA < -5	mA < -7
cP 7 - 12	mP 6 - 12	CP -6 – 2	mP -3 - 5
CML 11 – 16	mML 11 - 16	CML 1 – 8	mML 3 - 9
cT 15 - 19	mT 14 - 19	CT 8 – 14	mT 8 - 16
cE > 17	mE > 18	cE > 14	mE > 16

If the θw distribution is considered on a pressure surface, preferably 850 hPa, then extensive areas with a small or no gradient can be observed. These areas of homogeneous θw values may be associated with air masses. Often various homogeneous areas are separated from one another by relatively narrow transformation zones displaying a strong gradient. Here frontal zones intersect with the pressure surface. Generally speaking a surface front is located where at 850 hPa the 'warm boundary' of the zone with the large θw gradient is present.(Source: Wageningen University)

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
-----------------------------------------------

NWP:

A previsão numérica do tempo usa o estado instantâneo da atmosfera como dados de entrada para modelos matemáticos da atmosfera, com vista à previsão do estado do tempo.
Apesar dos primeiros esforços para conseguir prever o tempo tivessem sido dados na década de 1920, foi apenas com o advento da era dos computadores que foi possível realizá-lo em tempo real. A manipulação de grandes conjuntos de dados e a realização de cálculos complexos para o conseguir com uma resolução suficientemente elevada para produzir resultados úteis requer o uso dos supercomputadores mais potentes do mundo. Um conjunto de modelos de previsão, quer à escala global quer à escala regional, são executados para criar previsões do tempo nacionais. O uso de previsões com modelos semelhantes ("model ensembles") ajuda a definir a incerteza da previsão e estender a previsão do tempo bastante mais no futuro, o que não seria possível conseguir de outro modo.

Contribuidores da Wikipédia, "Previsão numérica do tempo," Wikipédia, a enciclopédia livre, http://pt.wikipedia.org/w/index.php?title=Previs%C3%A3o_num%C3%A9rica_do_tempo&oldid=17351675 (accessed fevereiro 9, 2010).