Modelo:

Actualização:

1 times per day, at 17:00 UTC

Greenwich Mean Time:

12:00 UTC = 12:00 WET

Resolution:

1.0° x 1.0°

parâmetro:

Geopotential in 500 hPa (solid, black lines) and Vorticity advection in 10⁵/(s*6h) (colored lines)

Descrição:

The two types of vorticity advection are positive (PVA) and negative vorticity advection (NVA). The closed circles in the figure show the 500 hPa absolute vorticity lines, the others the 500 hPa height lines. When an air parcel is moving from an area higher vorticity to an area lower vorticity this is called: PVA (red color). The other way around is called: NVA (blue color). PVA is associated with upper-air divergence, i.e. upward vertical motion. NVA is associated with down ward vertical motion. Therefore, PVA  at 500 hPa is strongest above a surface low, while NVA at 500 hPa is strongest above a surface high.
In operational meteorology Vorticity advection maps are used to identify areas with vertical air motion to see where clouds, precipitation or clear conditions are likely to occur. Keep in mind, however, that PVA is not the same as upward vertical motion. Here temperature advection is important too.

CFS:

The CFS model is different to any other operational weather forecasting model you will see on Weatheronline.
Developed at the Environmental Modelling Center at NCEP (National Centers for Environment Prediction) in the USA, the CFS became operational in August 2004.
The systems works by taking reanalysis data (NCEP Reanalysis 2) and ocean conditions from GODAS (Global Ocean data Assimilation). Both of these data sets are for the previous day, and so you should be aware that before initialisation the data is already one day old.
Four runs of the model are then made, each with slightly differing starting conditions, and from these a prediction is made.
Caution should be employed when using the forecasts made by the CFS. However, it is useful when monitored daily in assessing forecasts for the coming months, the confidence levels in these forecasts and in an assessment of how such long range models perform.
A description of the CFS is given in the following manuscript.
S. Saha, S. Nadiga, C. Thiaw, J. Wang, W. Wang, Q. Zhang, H. M. van den Dool, H.-L. Pan, S. Moorthi, D. Behringer, D. Stokes, M. Pena, S. Lord, G. White, W. Ebisuzaki, P. Peng, P. Xie , 2006 : The NCEP Climate Forecast System. Journal of Climate, Vol. 19, No. 15, pages 3483.3517.
http://cfs.ncep.noaa.gov/

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).